APPARATUS, SYSTEMS AND METHODS OF NON-INVASIVE THERMAL INTERROGATION

Abstract

Several non-invasive sensors are adapted for placement on the surface of an object with a volume containing an internal region. The object's internal region has internal properties defined by corresponding internal parameters and an internal temperature distribution that is a function of these internal parameters and surface thermal signals. Each non-invasive sensor includes a heat flow sensor with one or more heat flow sensor output terminals to provide a measured heat transfer signal for the object's surface, and a temperature sensor with one or more temperature sensor output terminals to provide a measured temperature signal for the object's surface.The systems include one or more of the sensors that perform non-invasive object detection, which includes the accurate and rapid determination of an internal temperature distribution of the internal region of the object, as well as one or more of other internal properties of the object.

Description

THERMAL INTERROGATION APPARATUS, SYSTEMS AND METHODS 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ NON-INVASIVE Background of the Invention Temperature sensors and other thermal sensing systems are important in many different technological fields and applications. Of particular importance are temperature sensors and other thermal detection systems that are non-invasive. The technology in this application is applied to non-invasive thermal interrogation devices, systems and methods that provide required reliability, accuracy, cost, complexity, size, ease of manufacture, ease of use, computing time, processing power, response and improved applicability across different industries. Non-invasive thermal interrogation (NITI) provides non-destructive testing and monitoring using thermal detection. Non-invasive thermal interrogation (NITI) is performed using simultaneous combinations of surface temperature signals and surface heat transfer signals (e.g., heat flux). When measured at the same time on an object or system surface, surface temperature and surface heat flux signals could be used to non-invasively determine internal parameters (e.g. thermal conductivity, density, capacity thermal resistance, convection coefficient, ready-state thermal resistance, etc.) and the internal temperature distribution (e.g., an internal temperature profile) of the internal region of the object or system. Typically, the internal temperature distribution of the object or system is a function of the internal parameters. Depending on the object or system undergoing the NITI and / or NITI application, the internal parameters may vary. Internal parameters and internal temperature distribution are defined as the internal properties of the object or system. Because NITI allows for non-destructive testing and monitoring of an object or system whenever thermal signals are present, NITI could be used in many diverse applications. In cases where sufficient thermal signals are not present, these may be generated on the surface of the object or system. 7AQC ίη / ίΖΠΖ / Ε / ΥΙΛΙ Summary of the Invention At least some examples provide a system for non-invasive detection of an object having a volume with a surface and an internal region. The system comprises a non-invasive sensor that includes: a thermal flow sensor having one or more thermal flow sensor output terminals, and a temperature sensor having one or more temperature sensor output terminals. The non-invasive sensor could be placed on or near the surface of the object. The internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution. The control circuitry, coupled with one or more of the thermal flow sensor output terminals and one or more of the temperature sensor output terminals, is adapted to: receive a measured temperature signal from the temperature sensor at one or more specified times; receiving a measured heat flow signal from the heat flow sensor at one or more of the specified times; determining a measurement of heat transfer leaving or entering the object at the surface based on the measured heat flux signal at one or more of the specified times; determining a value for each of the internal parameters at one or more of the specified times; determining an internal temperature distribution of the internal region of the object at one or more of the specified times as a function of the measured temperature signal, the measured heat flux signal, and the values ​​of the internal parameters; and generating information indicating the internal temperature distribution of the internal region of the object at one or more of the specified times. At least some examples provide a system for non-invasive detection of an object having a volume with a surface and an internal region. The system includes a non-invasive sensor which in turn includes: a thermal flow sensor having one or more thermal flow sensor output terminals, and a temperature sensor having one or more temperature sensor output terminals. The non-invasive sensor is adapted to be placed on or near the surface of the object, and the internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution. The control circuitry, coupled with one or more of the thermal flow sensor output terminals and one or more of the temperature sensor output terminals, is adapted to: receive a measured temperature signal from the temperature sensor at one or more specified times; receiving a measured heat flow signal from the heat flow sensor at one or more of the specified times; determining estimated values ​​for one or more of the internal parameters at one or more of the specified times based on the measured temperature signal and the measured heat flux signal; and generating information indicating one or more of the determined estimated values ​​for the internal parameters at one or more of the specified times. At least some examples provide a system for non-invasive detection of an object having a volume with a surface and an internal region. The system comprises a first non-invasive thermal flow sensor-temperature sensor pair and a second non-invasive thermal flow sensor-temperature sensor pair. Each of the first and second non-invasive heat flow sensor-temperature sensor pairs includes a heat flow sensor having one or more heat flow sensor output terminals and a temperature sensor having one or more output terminals. temperature sensor. The first and second non-invasive heat flux sensor-temperature sensor pairs could be placed at different locations on or near the surface of the object. The internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution. The control circuitry, coupled with one or more of the thermal flow sensor output terminals and one or more of the temperature sensor output terminals of each of the first and second non-invasive pairs of thermal flow sensor -temperature sensor, is configured to: receive a first measured temperature signal from the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair at one or more specified times; receiving a first measured heat flow signal from the heat flow sensor at the first non-invasive heat flow sensor-temperature sensor pair at one or more of the specified times; receiving a second measured heat flow signal from the heat flow sensor in the second non-invasive heat flow sensor-temperature sensor pair at one or more of the specified times; determining a value for each of the internal parameters at one or more of the specified times; determining an internal temperature distribution at one or more of the specified times based on the measured temperature signals from the temperature sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs in one or more of the specified times, the measured heat flow signals from the heat flow sensors in the first and second non-invasive heat flow sensor-temperature sensor pairs at one or more of the specified times, and the values ​​of the internal parameters at one or more than the specified times; and generating information indicating the internal temperature distribution at one or more of the specified times. At least some examples provide a system for the non-invasive detection of an object having a volume with a surface and an internal region, comprising a first non-invasive pair of thermal flow sensor-temperature sensor and a second non-invasive pair of thermal flow sensor-temperature sensor. Each of the first and second non-invasive heat flow sensor-temperature sensor pairs includes a heat flow sensor having one or more heat flow sensor output terminals and a temperature sensor having one or more output terminals. temperature sensor. The first and second non-invasive heat flux sensor-temperature sensor pairs could be placed at different locations on or near the surface of the object. The internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution. The control circuitry, coupled with one or more of the thermal flow sensor output terminals and one or more of the temperature sensor output terminals of each of the first and second non-invasive pairs of thermal flow sensor -temperature sensor, is configured to: receive a first measured temperature signal from the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair at one or more specified times; receiving a first measured heat flow signal from the heat flow sensor at the first non-invasive heat flow sensor-temperature sensor pair at one or more of the specified times; receiving a second measured temperature signal from the temperature sensor in the second non-invasive thermal flow sensor-temperature sensor pair at one or more of the specified times; receive a second 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ heat flow measurement signal from the heat flow sensor in the second non-invasive heat flow sensor-temperature sensor pair at one or more of the specified times; determining an initial value for each of the internal parameters at one or more of the specified times; determining one or more internal parameters of the object at one or more of the specified times based on the measured temperature signals from the temperature sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs in one or more of the specified times and the measured heat flow signals from the heat flow sensors in the first and second non-invasive heat flow sensor-temperature sensor pairs at one or more of the specified times, and the values ​​of the internal parameters at one or more of the specified times; and generating information indicating one or more internal parameters of the object at one or more of the specified times. At least some examples provide a non-invasive sensor that could be placed on or near a surface of an object having a volume with an internal region, where the internal region of the object has internal properties indicated by corresponding internal parameters and a temperature distribution. internal. The non-invasive sensor comprises a non-invasive heat flow sensor-temperature sensor pair that includes a heat flow sensor having one or more heat flow sensor output terminals to provide a measured heat flow signal for the surface of the object, and a temperature sensor having one or more temperature sensor output terminals for providing a measured temperature signal for the surface of the object. The thermal flow sensor and the temperature sensor are configured to undergo the same thermal conditions. At least some examples provide a non-invasive sensor that could be placed on or near a surface of an object that has a volume with a surface and an internal region. The non-invasive sensor comprises a first non-invasive thermal flow sensor-temperature sensor pair and a second non-invasive thermal flow sensor-temperature sensor pair. Each of the first and second non-invasive heat flow sensor-temperature sensor pairs includes a heat flow sensor having one or more heat flow sensor output terminals and a temperature sensor having one or more output terminals. temperature sensor. The first and second non-invasive thermal flux sensor-temperature sensor pairs are adapted to be placed at different locations on or near the surface of the object, where the internal region of the object has internal properties indicated by corresponding internal parameters and a distribution of internal temperature. Additional aspects, features and advantages of the technology presented in this application will be clear from the following description of examples, which will be read in conjunction with the accompanying drawings. Brief Description of the Figures An example of a heat flow sensor having a thickness t, a width W, and a length H is shown in Figure 1 according to an exemplary heat flow sensor embodiment. A cross section of a differential thermopile including a thermal resistance layer is shown in Figure 2A according to an exemplary embodiment. A cross section of a differential thermopile that includes a thermal resistance layer is shown in Figure 2B and could be easier to manufacture according to an example embodiment. An example is shown in Figure 3 where heat flow is imposed across a junction, and heat flow is generally restricted to conduction through the contact sites. A cross section of an example CHFT+ embodiment is shown in Figure 4 that includes a heat flux sensor and a temperature sensor placed on a surface of an object with unknown internal properties where 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ a heater (the external thermal device) is placed on the thermal flow sensor. A cross-section of an exemplary CHFT- embodiment is shown in Figure 5, which includes a heat flux sensor and a temperature sensor placed on a surface of an object with unknown internal properties. A cross section of an exemplary CHFT embodiment is shown in Figure 6A, which includes a heat flow sensor, a temperature sensor, and an insulation piece on the heat flow sensor and the temperature sensor (i.e., the pair of thermal flow-temperature sensors). A cross section of an exemplary CHFT embodiment is shown in Figure 6B, which includes a heat flow sensor, a temperature sensor, and an insulation piece on the heat flow sensor and the temperature sensor (i.e., the pair of thermal flux-temperature sensors) as well as a portion of the surrounding target area. A cross section of an exemplary CHFT embodiment is shown in Figure 6C, which includes a heat flow sensor, a temperature sensor, and an insulation piece in and surrounding the heat flow sensor and the temperature sensor (i.e. that is, the pair of thermal flow sensors (temperature). A cross section of an exemplary CHFT+ embodiment that includes a thermal flow sensor, a temperature sensor, and an external thermal device (e.g., a heater) is shown in Figure 7A. A cross section of an exemplary CHFT+ embodiment is shown in Figure 7B that includes a thermal flow sensor, a temperature sensor, and an external thermal device (e.g., a heater) that provides a thermal event to the pair of temperature sensors. thermal flow-temperature. An example CHFT+ embodiment is shown in Figure 7C which includes a temperature sensor, a thermal flow sensor, a heater, and the corresponding output terminals. A cross section of an exemplary CHFT+ embodiment is shown in Figure 7D that includes a thermal flow sensor, a temperature sensor, and an external thermal device (e.g., a heater), where the temperature sensor is located between the thermal flow sensor and external thermal device. A cross section of an exemplary CHFT+ embodiment is shown in Figure 7E that includes a thermal flow sensor, a temperature sensor, and an external thermal device (e.g., a heater), where the temperature sensor is located within the thermal flow sensor. A cross section of an exemplary CHFT+ embodiment that includes a heat flow sensor, a temperature sensor, and an external thermal device (e.g., a heater) is shown in Figure 7F, where the heat flow sensor and the sensor of temperature are separated by a substrate. A cross section of an exemplary CHFT+ embodiment that includes a heat flow sensor, a temperature sensor, and an external thermal device (e.g., a heater) is shown in Figure 7G, where the heat flow sensor and the sensor Temperature sensors are separated by a substrate and the temperature sensor is surrounded by thermally compatible materials. A function block diagram illustrating an example NITI system for performing NITI with a CHFT- is shown in Figure 8. A function block diagram illustrating an example NITI system for performing NITI with a CHFT+ is shown in Figure 9. A flow chart is shown in Figure 10 outlining example non-limiting procedures performed by the control circuitry in an example NITI system that includes a NITI sensor to determine one or more internal properties of an object, including a internal temperature distribution of the object at one or more specified times using the measured heat flux, the measured temperature, and the determined values ​​of internal parameters of the object. A flowchart showing example procedures for a parameter estimation scheme performed by the control circuitry in a NITI system is shown in Figure 11. A cross-section of an example DUO (parallel sensor pairs) CHFT+ (with heater) modality placed on a surface of an object with unknown internal properties is shown in Figure 12. A cross section of an example DUO (parallel sensor pairs) CHFT- modality with different amounts of thermal insulation at each sensor node is shown in Figure 13. Figure 14 shows a cross section of an example DUO (parallel sensor pairs) CHFT- modality with one CHFT- node incorporating thermal insulation while the other is exposed. Figure 15 shows a cross-section of an example CHFT+ / - DUO (parallel sensor nodes) sensing modality, where one sensor node incorporates a CHFT+ and another incorporates a CHFT-. A cross section of an example DUO (parallel sensor pairs) CHFT- modality is shown in Figure 16 where no sensor node has thermal insulation. A function blog diagram is shown in Figure 17 illustrating an example NITI system for performing NITI with two non-invasive pairs of thermal flow temperature sensors operating in parallel to determine one or more internal properties of an object. A flow chart showing example procedures related to a differential basis data processing method performed by the control circuitry is shown in Figure 18A. A flowchart showing example procedures related to a differential basis data processing method performed by the control circuitry under ready state conditions is shown in Figure 18B. A flow chart showing example procedures related to a quotient arithmetic basis data processing method performed by the control circuitry is shown in Figure 1 9A. A flowchart showing example procedures related to an arithmetic quotient base data processing method performed by the control circuitry under ready state conditions is shown in Figure 19B. Shown in Figure 20 is a flow diagram outlining example non-limiting procedures for an example DUO NITI modality using two non-invasive pairs of heat flow-temperature sensors to determine one or more / AQCLn / LZnZ / E / YIAI parameters. internals of an object. Shown in Figure 21 is a flow chart outlining exemplary non-limiting procedures for an exemplary DUO NITI modality using two non-invasive pairs of heat-temperature flux sensors to determine an internal temperature distribution of an object. An example application to blood perfusion (flow) in tissue is shown in Figure 22. A graph showing the ability of the parameter estimation scheme to determine an optimal perfusion value (í¥) when used with experimental data is shown in Figure 23. Shown in Figure 24 is a graph illustrating an example of a match between a calculated sensor (outlet) temperature curve and a measured sensor (inlet) temperature for an exemplary modality of CHFT+ blood perfusion. Shown in Figure 25 is a graph illustrating an example of a mismatch between a calculated sensor (outlet) temperature curve and a measured sensor (inlet) temperature for an exemplary modality of CHFT+ blood perfusion. A graph illustrating the difference sensitivity of the sensor (output) temperature curve calculated with the internal parameters versus time in the blood perfusion application is shown in Figure 26. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ A graph showing the results of an example DUO CHFT+ modality and an example periodic CHFT+ modality when used to measure the perfusion rate of a perfusion pseudo tissue is shown in Figure 27. Shown in Figure 28 is a graph showing the results of an example CHFT+ (Active Thermometry) modality when used to measure the core temperature of perfused pseudo tissue. A graph showing the results of an example CHFT- (Passive Thermometry) modality when used to measure the core temperature of the perfusion pseudo tissue is shown in Figure 29. A graph showing the results of an example CHFT+ ZFIF (Zero Thermal Flow Thermometry) modality when used to measure the core temperature of perfusion pseudo tissue is shown in Figure 30. Another application of the technology to determine one or more parameters related to the fluid or liquid flowing in a pipe or other conduit is shown in Figure 31. A graph showing an example correlation developed with experimental measurements for fluid flow in a copper pipe is shown in Figure 32. Figure 33 shows a graph that shows the capacity of the parameter estimation scheme in the 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ determination of the optimal value of convection coefficient (h) when used with experimental data. A graph showing an example of a match between a calculated sensor (outlet) temperature curve and a measured sensor (inlet) temperature for an example fluid flow CHFT+ in a copper tubing embodiment is shown in Figure 34. A graph showing the results of an example CHFT+ (Active Thermometry) modality when used to measure the internal temperature of fluid flow within a copper pipe is shown in Figure 35. A graph showing the results of an example DUO CHFT+ / - modality (a sensor node with a heater and without a sensor node) when used to measure the internal temperature of the fluid flow within a copper pipe. A graph showing the results of an example DUO CHFT+ / - modality (a sensor node with a heater and without a sensor node) when used to measure the internal temperature of the fluid flow within a CPVC pipe. 7«QC Ln / Lznz / E / YIAI Description of Examples Some specific examples will be discussed later. It will be appreciated that the invention is not limited to these particular examples. The following description indicates the example modalities for purposes of explanation and without limitation. Although it will be appreciated by those skilled in the art that other example modalities could be used apart from these specific details. In some instances, detailed descriptions of well-known methods, interfaces, circuits, and devices are omitted so as not to confuse the description with unnecessary details. The individual blocks are shown in some Figures. Those skilled in the art will appreciate that the functions of those blocks could be implemented using individual hardware circuits, using software programs and data in conjunction with a suitably programmed digital microprocessor or general purpose computer, and / or using applications from a set of specific integrated circuits (ASIC), and / or using one or more digital signal processors (DSP). The software program instructions and / or data may be stored on a non-transitory computer-readable storage medium, one or more clouds, one or more servers, and when the instructions are executed by a computer or other suitable processor control, the computer or processor performs the functions associated with those instructions. The term signal is used herein to 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ include any signal that transfers energy and / or information from one position or region to another in an electrical, electronic, electromagnetic, magnetic or mechanical form (for example, ultrasonic signals). Signals could be conducted from one position or region to another by electrical or magnetic conductors, although the term signals could also include a form of light signals and other electromagnetic forms of signals and other signals transferred across non-conductive regions due to the effects electrical, electronic, electromagnetic, magnetic, or elastic. Signals include analog and digital signals. An analog electrical signal includes information in the form of a continuously variable physical quantity such as voltage. A digital electrical signal includes information in the form of discrete values ​​of a physical characteristic, which could also be, for example, voltage. A component, layer, or other structure is thermally conductive or thermally conductive if it sufficiently conducts thermal energy (e.g., thermal energy transferred by conduction, radiation, and / or convection) from one location or region to another so that operations in the other position or region can be affected by the thermal energy. The term detection means obtaining information from a physical stimulus and therefore, detection includes actions such as detection, measurement and so on. Thermal sensing is the detection of a thermal stimulus such as heat, temperature, or random kinetic energy of molecules, atoms, or smaller components of matter. A thermal sensor is an electronic device that performs thermal detection and generates signals related to thermal energy. If thermal energy includes the information, then a thermal sensor or combinations of thermal sensors that detect thermal energy might be able to detect the information. Depending on the context, the different forms and / or types of thermal energy and related thermal signals, as used in this application, could be considered as heat transfer, heat transfer signals, temperature and temperature signals. Unless the context indicates otherwise, the terms circuitry and circuit refer to structures in which one or more electronic components have sufficient electrical connections to operate together or in a related manner. In some instances, a circuit set item may include more than one circuit. An item of circuitry that includes a processor may sometimes be separated into hardware and software components; In this context, the term software refers to stored data that controls the operation of the processor or that is input by the processor while it operates, and the term hardware refers to components that store, transmit, and operate based on the data. The circuitry may be described in terms of its operation or other characteristics. For example, the circuitry that performs the control operations is sometimes referred to as the control circuitry, and the circuitry that performs the processing operations is sometimes referred to as the processing circuitry. In general, sensors, processors and other items could be included in a system in which they are operated, automatically or partially automatically. The term system refers to a combination of two or more parts or components that can perform an operation together. A system could be characterized by its operation. An integrated structure is a structure with electrical components and connections produced by microfabrication or similar processes. An integrated structure could be, for example, in or on a substrate on which it was produced or another suitable supporting structure. Other components could be on the same support structure with an integrated structure, such as discrete components produced by other types of processes. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ Typically, thermal-based detection and monitoring are only performed with temperature sensors and / or temperature signals. For example, for the purpose of determining the internal temperature of an object or system, invasive temperature probes are inserted to a prescribed depth of interest. One example uses invasive temperature probes that are inserted into thermowells to measure the temperature of the internal flow within a pipe or conduit. Typically, placement of the thermowell requires complicated procedures where the surface of the pipe or conduit is perforated and / or otherwise penetrated for the purpose of placing the thermowell within the internal fluid flow. A temperature sensor (e.g., thermocouple, resistance temperature device (RTD), thermistor, thermometer, etc.) is then inserted into the thermowell unprotected from liquid flow. Due to the thermal capacity of the thermowell, the response time of the temperature sensors within them is decreased. Additionally, because the walls of the thermowell could conduct heat out of (or into) the pipe or conduit, the accuracy of the temperature sensor could be negatively impacted. Typically, this procedure in measuring fluid flow temperature is more accurate than, for example, measuring surface temperature measurements of pipe or conduit. However, due to the invasive nature of this technology, typically, a number of design considerations are made prior to use. These design considerations can become complicated and costly for many applications. For example, thermowell material and / or design characteristics could differ depending on the application and the need to adhere to extensive standards (e.g., American Society for Testing and Materials (ASTM) standards). Additionally, the invasive nature of thermowells results in complicated long-term maintenance, for example, due to corrosion and / or prolonged exposure to a large flow of energy fluid that can cause structural stress and vibration. Another example of thermally based detection of the place where invasive probes are used for internal temperature measurement of the object and / or system is the central body temperature measurement. For example, in healthcare, current methods used and accepted as accurate methods of real-time core body temperature measurement are, for example, esophageal, rectal, and pulmonary artery baseline temperature measurements. All of these methods use invasive and often uncomfortable probes that are placed in different locations within the body. Due to their invasive nature, these methods can lead to infection and / or other complications. The invasive nature of these methods also limits the scope of where and when measurements can be made. For example, invasive probes are rarely used unless patients have undergone anesthesia or other similar procedures. Invasive probes are also not suitable for wearable technologies or devices. Given the limitations of invasive internal temperature measurement technologies, an alternative procedure could be to take internal temperature measurements of an object or system based on surface and / or external temperature readings (e.g., ambient temperature). However, this procedure typically results in inaccurate measurements and may require complex hardware and software systems in an attempt to determine internal temperature measurements based on these non-invasive temperature measurements. In some embodiments, multiple temperature sensors could be used on or near a surface of the object or system and / or internally within a device that is placed on or near the surface of the object or system. In addition, one or more thermally calibrated components (eg, insulation pieces, accurate temperature sensors, etc.) might be required. This also gives rise to complicated and / or complex measurement systems. Other modalities could include one or more control systems, one or more heaters, one or more coolers, and / or multiple temperature sensors. These modalities could be designed, for example, to create and determine an environment of 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ zero thermal flow for internal temperature measurement. Typically, these non-invasive procedures are slow and inaccurate especially under changing or extreme thermal conditions. Additionally, in some cases, for accurate internal temperature measurements, sensor and / or device placement could be limited to specific areas on an object or system surface. For example, with respect to core body temperature measurement, the placement of the sensor and / or device could be limited to certain ancillary locations on the body (eg, the armpit or forehead). Additionally, due to the complexity of the hardware, the modalities could be associated with large form factors, resulting in inconvenience for many applications. For example, with respect to core body temperature measurement, large form factors are impractical for portable or wearable applications. With regard to non-invasive measurement of internal pipe or conduit temperature, large form factors could prevent mounting of the sensor and / or device in certain locations, for example, between the pipe surface and the surrounding thermal insulation. Finally, the complexity of these systems could cause manufacturing difficulty as well as increased manufacturing or fabrication costs. Other thermal-based sensing applications could use the temperature-based signals to determine internal fluid flow via thermal anemometry. This procedure requires an internal probe for the purpose of taking fluid flow measurements that correspond to the temperature signals measured through established correlations. In contrast, thermal dispersion flow meters are non-invasive systems that use temperature sensors on the surface of a pipe or duct between which a heater provides thermal energy to the surface of the pipe / duct. The temperature difference between the temperature sensors placed before and after the heating element is correlated with the internal fluid flow rate. However, thermal dispersion flow meters do not work adequately with pipes made of thermally insulating materials. Additionally, these are susceptible to inaccuracies when used under different conditions because the specific amount of thermal energy (i.e., heat transfer) entering the pipe or duct through the heater is unknown and can only be estimated with assumptions. underlying. In this way, thermal dispersion flow meters are typically calibrated for specific conditions and use cases. Other thermal-based technologies could be used to predict (e.g., analytically determine) object or system surface heat transfer (e.g., heat flux) using surface and / or internal temperature measurements. These techniques could further be used to determine the internal properties of an object or system based on the expected surface heat transfer (e.g., heat flux) and surface or internal temperature signals. However, these techniques could have a number of limitations such as poor precision, low resolution, long processing time, and noise amplification due to mathematical integration required when determining heat transfer (e.g., flow rate). thermal) of the measured temperature signals. For example, the determined surface heat transfer (e.g., heat flux) of an object or system could be compared to the measured surface heat transfer (e.g., by means of a heat flux sensor) for the purpose of determining the internal properties of the object or system. Again, due to the limitations of baseline temperature measurements predicting heat transfer (e.g., heat flux), the values ​​determined by these techniques for the internal properties of an object or system could be inaccurate and impractical for its application. Additionally, when these techniques are used, there could be a mismatch between the measured temperature (e.g., surface temperature), from which surface heat transfer is determined, and the measured heat transfer (e.g., flow rate). thermal surface) of an object or system. For example, a mismatch could occur when the heat transfer (e.g., heat flux) measured at the surface of the object or system, for example, by a heat flux sensor, is not the same as the heat transfer (for example, heat flow) that occurs or occurs at the location of the surface temperature sensor. This may be caused, for example, by a surface temperature sensor that is located in proximity to a heat flow sensor where it is not subjected to the same thermal conditions (e.g., heat transfer and / or temperature) experienced by the thermal flow sensor. In other examples, a temperature sensor could be located on or near a heat flow sensor although at a location outside the detection area of ​​the heat flow sensor, which could also cause measurement mismatch. Similar problems could arise when using a temperature sensor that is located, for example, in or near a heat flux sensor detection area even though it causes inadequate contact between the heat flux sensor and object / system surfaces such as result, for example, of its design (e.g. thickness) and / or materials. In this example, the mismatch occurs because the measured temperature is not an accurate representation of the surface temperature and / or the measured heat transfer does not represent the reality of what is occurring at the surface of the object / system and / or is being experienced by the temperature sensor. In other examples, the materials used to construct the heat flux sensor and the temperature sensor and / or their environments could be sufficiently different (e.g., different thermal resistance values) and could cause a non-uniform response to uniform thermal conditions. . This can also cause a mismatch between the outputs of the thermal flow sensor and the temperature sensor. In another example, a thin film thermocouple, which is an exemplary thin temperature sensor, could be located in a thermal flux sensor sensing area where adequate contact is established between the thermal flux sensor and the object surfaces. / system. In this case, although the thin-walled thermocouple temperature sensor does not create any of the example problems described above (e.g., inadequate contact due to thickness) and is subject to the same thermal conditions (e.g., transfer of heat and / or temperature) than the thermal flow sensor, it could experience thermal drift where the measured temperature is inaccurate due to thermal energy being conducted to or from (i.e., leaving or entering) the junction or joint of the thermocouple by means of the thermocouple materials and / or the output terminals (for example, the thermocouple leads). In these cases, the measured temperature could be lower or greater than the actual temperature experienced in or near the thermal flux sensor detection area. All of these non-limiting and exemplary conditions are possible problems for the accurate determination of the internal properties of an object or system when using thermally based sensing technologies. One problem with using heat transfer measurements (eg, heat flux) in thermal-based sensing technologies is inefficiency. Heat transfer is conventionally understood and explained as a consequence of temperature gradients. This conventional procedure could lead to inefficient and imprecise heat transfer (eg heat flux) measurement techniques as well as general confusion between heat transfer (eg heat flux) and temperature differences. For example, a mode for measuring heat transfer might use one or more temperature sensors, eg, thermocouples, RTDs, negative or positive temperature coefficient (NTC) sensors, thermistors, etc., on either side of some kind. of insulation material (i.e., the thermal resistance layer to create a heat flux stratified gauge, a one-dimensional (i.e., flat) type of flat gauge. In this example method, the determination (for example, the average) of the absolute temperature on either side of the insulating material is measured, and the difference between them is used to determine the amount of heat transfer that occurs through the insulating material with a calibrated or otherwise determined value of thermal resistance. In another exemplary procedure, a thermocouple could be placed on either side (eg, top and bottom) of a calibrated insulating material (ie, the thermal resistance layer), forming a thermocouple pair. The thermocouple pair could be positioned so that, when connected in series, the output of the thermocouple pair is a differential voltage that is indicative (eg, proportional) of the temperature difference across the thermal resistance layer and of the heat transfer (e.g., heat flow) that occurs through the thermal resistance layer. These example procedures could result in large, expensive, inaccurate, slow heat flow devices (ie, heat flow channels) that could require multiple calibrations and could be difficult to manufacture. Another shortcoming in thermally based detection techniques is the failure to determine or otherwise account for thermal contact resistance. This leads to erroneous surface temperature measurement which could influence the accuracy of thermal base detection and monitoring. However, it could be difficult and confusing to model and / or determine the thermal contact resistance when performing thermal base detection. This is in part due to the complexity and inaccuracies associated with determining thermal contact resistance using only temperature signals and / or methods that predict heat transfer based on temperature signals. The technology described in this application solves these technical problems and provides the following exemplary technical benefits, most importantly, in addition to surface temperature measurement, the technology described in this application provides transfer measurement of heat (eg, heat flux) entering or leaving the surface of the object and / or system as a part of a thermal-based detection and / or monitoring routine (ie, technique). This measure of heat transfer (for example, heat flux) is used as a direct input and / or boundary condition in one or more thermal mathematical models that might differ for different applications. Measurement of heat transfer (eg, heat flux) as an input and / or direct boundary condition, enables accurate and robust thermal detection and monitoring techniques (ie, interrogation). The technology performs heat transfer measurement (for example, heat flow) by means of one or more heat flow sensors. For the purpose of this application, the term heat flow sensor refers to a sensor designed to measure heat transfer (for example, heat flow) using the differential voltage output signals that are a consequence of heat transfer. (i.e. thermal energy) flowing through the sensor. A non-limiting example of a heat transfer measurement is heat flux which is defined as the amount of heat energy entering or leaving a surface per unit area per unit time and can be measured in SI units of W / m2. Typically, a heat flow sensor has a calibration constant (i.e., sensitivity value) that directly relates the differential voltage output signals from the heat flow sensor to heat transfer (for example, heat flow thermal) that are presented through it. A calibration constant might vary with sensor operating temperature, the effects of which can be accounted for by means of a given calibration curve that specifies a calibration constant as a function of sensor operating temperature. Regarding this application, it is important to note the distinctions between a heat flow sensor and a heat flow device, a heat flow channel, etc. Typically, a thermal flow sensor is thin and has a fast response time as a result of its design. This provides exemplary benefits including increased accuracy, smaller form factor, and robust measurement capability that are not realized by other heat transfer measurement technologies. Additionally, the technology described in this application guarantees, regardless of the proximity of the temperature sensor to the heat flow sensor (for example, close to, in or near the detection area of ​​the heat flow sensor, etc.) , that there is no mismatch between the measured temperature (e.g., surface temperature) and the measured heat transfer (e.g., surface heat flux) of an object or system (i.e., heat flux sensor and heat flux sensor). of temperature are subjected or subjected to the same thermal conditions). For example, where possible, the temperature sensor could be located in or near the thermal flux sensor detection area while maintaining adequate contact between the thermal flux sensor and the surfaces of the object / system and, if applicable, the design of possible effects related to thermal bypass and / or thermal homogeneity of the materials used for construction. In other exemplary embodiments, the temperature sensor could be located in or near (e.g., adjacent) the heat flow sensor and / or the heat flow sensor sensing area and could be surrounded by and / or in contact with materials. that guarantee the same thermal conditions (for example, heat and / or temperature transfer) between the thermal flow sensor and the temperature sensor. Another primary benefit of the technology in this application is the ability to easily and quickly determine the thermal contact resistance between a temperature sensor and the surface of the object or system. This improves the accuracy and validity of thermal detection and monitoring, especially in example applications where the effects of thermal contact resistance are not noticeable and / or unpredictable. Another main benefit of the technology in this application is the non-invasive use and simplicity. For example, the extensive design considerations or precautions that are required for invasive beam technologies are not necessary. Furthermore, the technology is not restricted to applications where invasion is permissible. Additional benefits of the technology in this application include minimal processing time and reduced processing power required. This benefit is in part attributed to the use of a thermal flow boundary condition as well as the incorporation of rapid and refined thermal contact resistance determination methods. The reduced need for calibration of sensors designed for the measurement of heat transfer (e.g., heat flux) is another benefit. For example, the technology in this application typically only requires a calibration constant (i.e., sensitivity value) for the measurement of heat transfer by a thermal flux sensor. The technology in this application is based on the simultaneous use of thermal flow and temperature sensors to determine, in a non-invasive manner, one or more internal properties of an object and / or system. The objects and / or systems are not limited to solid objects but also include, for example, fluid (e.g., water, air, etc.) or other materials, for example, metallurgical powder, epoxies, carbon fiber composite materials , etc. For simplicity, the term object as used in this application includes a system. For example, a pipe with a fluid flowing inside it is an object. The term non-invasive thermal interrogation (NITI) is used herein to refer to sensor technology based on simultaneous combinations of surface heat flux and surface temperature measurements. When placed on an object, a NITI sensor measures one or more simultaneous combinations of surface heat transfer (e.g., heat flux) and surface temperature signals that are converted to a digital form and processed to determine one or more internal properties of the object. For a given measurement, the term simultaneous combination as used in this application refers to one or more of the surface heat transfer (e.g., heat flux) and surface temperature signals that are measured within a time range. (i.e. within a specific amount of time). A time range could include a single time (that is, a specified time). For simplicity, the term specified time as used in this application is defined to include a range of time (i.e., within a specified amount of time) as well as a single time. Example non-limiting applications of NITI technology include but are not limited to: measuring the internal temperature distribution of an object (e.g., mammal, non-mammalian, meat, pipe / conduit, power transformer, wooden boards / wood, wall, machine, battery, etc.), the measurement of internal parameter of an object (e.g., mammal, non-mammal, meat, pipe / conduit, power transformer, wood / timber boards, wall, machine, battery, etc.), measuring tissue blood perfusion (flow), preventing and / or monitoring tissue ulcer, detecting and / or monitoring hemorrhage, detecting and / or monitoring contusion, measuring of tissue hydration, measurement of metabolic heat generation, monitoring of athlete performance, measurement of caloric expenditure, sleep monitoring, circadian rhythm monitoring, prediction and / or detection of mammalian ovulation, monitoring and / or prevention of heat stroke, detection and / or monitoring of sickle cell anemia, detection and / or monitoring of anemia, cardiovascular health, monitoring of skin flap and / or graft, prediction of diseases, monitoring and / or detection (for example, Alzheimer's, Parkinson's, cancer, etc.), measuring flow velocity in pipes and / or conduits, measuring energy in pipes and / or ducts, pipe / duct freeze prevention, pipe / duct defrosting, HVAC freeze / thaw detection, HVAC system monitoring, HVAC refrigerant level monitoring, leak detection (e.g. , pipe / duct water leakage, HVAC refrigerant leakage, etc.), hot water heater monitoring, heat exchanger monitoring, corrosion detection and / or measurement (e.g., corrosion of pipe / duct, etc.), the detection and / or measurement of incrustations (for example, the encrustations of pipe / duct, etc.), the detection of the flow level, the presence and / or detection of motion, the monitoring of semiconductor hardware, heat dissipation performance monitoring, thermal interconnect material monitoring, thermal resistance measurement, building insulation measurement, density, thermal capacity, volumetric thermal capacity, thermal conductivity , thermal inertia, thermal effusivity, thermal diffusivity, etc., from the measurement of objects and / or materials (for example, metallurgical powder, epoxides, carbon fiber composite materials, etc.), measurement of content of hydration / water, convective heat transfer coefficient measurement, heat transfer advection coefficient measurement, heat treatment, thermal sanitation, thermal processing, thermal comfort, thermal operation of buildings, precision agriculture, smart farms, food processing , object freezing, object defrosting, metallurgical processing, 3D printing, object quality control, smart buildings, efficiency monitoring, object overheating prevention, fault detection and / or object prediction / prevention (e.g. machine , gearbox, compressor, fan, electromechanical system, / AQCLn / LZnZ / E / YIAI etc.), advanced temperature control, battery performance monitoring (e.g. battery over-health time status lithium-ion, etc.), battery calorimetry, Internet of Things (IoT), wearable or wearable sensors, predictive analytics, prescription analytics, descriptive analytics, artificial intelligence, and research and development. The term, internal temperature distribution of the internal region of an object (i.e., internal temperature distribution) as used in this application, includes a single temperature at a specified depth in the object at one or more specified times, multiple temperatures as a function of the depth in the object at one or more of the specified times, a single average temperature at a specific depth in the object at one or more specified times, multiple average temperatures as a function of the depth of the object at one or more more than the specified times, a single higher or lower temperature at the object at one or more specified times, multiple higher or lower temperatures at the object at one or more of the specified times, a single higher or lower average temperature lowest average temperature at the object at one or more specified times, or multiple average highest or lowest temperatures at the object at one or more of the times 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ specified. Furthermore, the internal temperature distribution of the internal region of the object is defined that includes measurements of the object's surface temperature. For example, the internal temperature distribution could be evaluated at the surface of the object (i.e., depth (x) of 0) at one or more specified times. The term, internal parameters of the internal region of an object (i.e., internal parameters) as used in this application includes one or more thermal, physical, mechanical, etc. characteristics of the object. For example, the internal parameters of the object could include the thermal conductivity of the object, the density of the object, the thermal heat capacitance of the object, the volumetric heat capacity of the object, the thermal diffusivity of the object, the thermal inertia of the object, the effusivity thermal resistance of the object, the ready-state thermal resistance of the object, the internal or external convection coefficient of the object, the internal or external advection coefficient of the object, the thickness of the object, the volume of the object, the mass of the object, the area in cross section of the object, the porosity of the object, the state of the object (e.g. liquid, solid, gas, etc.), the depth of interest of the surface of the object, etc. some internal parameters could be based on the combination of internal parameters (for example, an arithmetic quotient and / or product of two or more internal parameters). Furthermore, not all internal parameters of an object could be used and / or required for a NITI modality and / or application. For simplicity, the term internal parameters as used in this application includes one or more internal parameters that are necessary and / or desired for the NITI modality being performed for the object (i.e., the corresponding internal parameters). NITI SENSOR EXAMPLE MODALITIES Exemplary sensor embodiments for NITI (i.e., NITI sensors) include one or more heat flow sensors and one or more temperature sensors. A heat flow sensor and a temperature sensor that are subjected to the same thermal conditions (e.g., heat transfer and / or temperature) and take simultaneous measurements at one or more specified times are referred to as a flow sensor pair. thermal-temperature (i.e. a pair of sensors). A NITI sensor could also include an external thermal device that is used with a control circuitry intended for NITI. In other exemplary sensor embodiments, an optional external thermal device creates a source of thermal energy on one side of an NITI sensor that travels through the NITI sensor and toward an object for which measurements are being taken. In other example embodiments, an optional external thermal device creates a thermal energy sink (ie, heat sink) on one side of an NITI sensor that causes heat transfer from an object for which measurements are being taken. , through the NITI sensor, and to the heat sink, an external thermal device could be a heater and / or cooler (for example, a Peltier device) that is used with control circuitry intended for the NITI to create a thermal event (heating and / or cooling) so that simultaneous different combinations of heat transfer signals (for example, heat flux) and temperature on an object surface, acquired (for example, measurements) can be generated and processed. ). An external thermal device could operate in any mode (ready, periodic, cycle, etc.). In some example embodiments, an external thermal device could be used to provide a periodic condition of temperature (eg, sinusoidal) and / or heat flux at the surface of the object with respect to time. In addition, the exemplary embodiments use phase angle determination techniques with one or more of the NITI techniques described to determine one or more internal properties of the object. Typically, the external thermal device is adapted to provide the thermal event to the area surrounding the entire pair of heat flow sensors where, at a minimum, the entire sensing area of ​​the heat flow sensor is subjected to the thermal event . In other example embodiments, the external thermal device could be adapted to provide the thermal event to the area surrounding the entire heat flux-temperature sensor pair, as well as the surface areas of the object surrounding or surrounding the temperature sensor pair. heat flow-temperature sensor. In other example embodiments, an external thermal device could provide a thermal event to multiple heat-temperature flow sensor pairs. In other example embodiments, for example, when the object undergoing interrogation has a non-planar (eg, curved) surface, an external thermal device could be designed to provide a thermal event to the area that includes a pair of thermal flux sensors. -temperature and not to the surface of the surrounding object, In other exemplary sensor embodiments, an external thermal device could be used with control circuitry that is intended for the NITI to eliminate heat transfer that occurs between the object and NITI sensor surfaces. For example, an external thermal device (e.g., a heater) could apply or remove heat (i.e., thermal energy) at the surface of the object and could create a zero heat flow environment between the contacting surfaces of the object. and NITI sensor. In a zero heat flux environment, the heat flux sensor component of the NITI sensor outputs and maintains a minimum voltage (e.g., 0) and, when in ready-state conditions, the corresponding measured surface temperature. by the NITI sensor on the surface of the object is indicative of the internal temperature distribution of the internal region of the object. With respect to the exemplary NITI system and / or sensor embodiments described below, the term CHFT+ / - refers to the combined heat flux and temperature sensor (i.e., the heat flux temperature sensor pair) and CHFT. + or indicates the use of an external thermal device (e.g., heater, Peltier device, etc.) that is used with a set of control circuitry that is intended or not intended for NITI, respectively. The term DUO NITI refers to NITI system and / or sensor modalities with multiple (e.g. two) NITI sensors (e.g. CHFT+ or CHFT-) operating in parallel. Example DUO NITI modalities could use, for example, differential and / or quotient arithmetic basis data processing methods to simplify and make NITI measurements more robust. Additionally, the term DUO CHFT+ refers to the example DUO NITI modalities that only use two or more parallel CHFT+ modalities. Similarly, the term DUO CHFT- refers to example DUO NITI modalities that only use two or more parallel CHFT- modalities. The term DUO CHFT+ / - refers to DUO NITI example modes that use at least one CHFT+ example mode and at least one CHFT- example mode operating in parallel. As related for this application, the terms CHFT+, CHFT-, DUO CHFT+ / -, DUO CHFT+, and DUO CHFT- are non-limiting examples of NITI sensor modalities that could be used in non-NITI systems, some of which are described later. Although heat flow devices, heat flow channels etc. could be used for NITI, heat flow sensors are preferred for the reasons described above. All types of heat flow sensors (i.e. heat flow calibrators, heat flow gauges, heat flow transducers, heat flow meters, heat flow meters, heat flow calibrators, heat flow gauges, etc.) that are manufactured using a variety of methods and technologies (e.g., thin film technologies, thick film technologies, thermopile technologies, differential thermopile technologies, thermoelectric technologies, heat effect technologies Seebeck, Seebeck cross-effect technologies, splice soldering technologies, microelectromechanical system (MEMS) base technologies, nanoelectromechanical system (NEMS) base technologies, complementary metal oxide semiconductor (CMOS) base technologies, technologies additive manufacturing technologies, screen printing technologies, inkjet technologies, textile sensor technologies, wire wound technologies, RTD based technologies, NTC based technologies, thermistor based technologies, semiconductor based technologies, etc. ) could be used for the NITI. In some example embodiments, one or more of the heat flow sensors are based on differential thermopile technology as described by ASTM E2684 and as further discussed in ASTM E2683. A differential thermopile is a type of passive electronic transducer that converts thermal energy into electrical energy (e.g., voltage and / or current). Typically, a differential thermopile is composed of several thermocouples connected in series or, less commonly, in parallel. Typically, thermocouples (i.e., thermocouple joints or junctions) are located on either side of one or more materials (i.e., the thermal resistance layer). Individual thermocouples (i.e., thermocouple joints or junctions) measure the temperature differential from their junction point to the point at which the thermocouple voltage output is measured. When connected in series, the voltage output of two thermocouples on either side of a thermal resistance layer (i.e., a differential thermocouple pair or thermocouple pair) is typically a differential voltage that is related (e.g. , is proportional) to the temperature difference across (e.g., across) the thermal resistance layer and to the heat transfer (e.g., heat flow) that occurs through the thermal resistance layer. thermal resistance. The addition of more pairs of thermocouples in series increases the magnitude of the differential voltage output, consequently resulting in a higher sensitivity of the thermal flux sensor. The differential voltage output is also affected by the thermocouple materials used (i.e. thermoelectric). Therefore, for a given temperature difference across a thermal resistance layer, some thermocouple materials may cause a higher differential voltage output than others. In this way, the selection of ternocouple material also impacts the sensitivity of the thermal flux sensor. Likewise, the materials and / or thickness used for the thermal resistance layer could affect the sensitivity of the thermal flux sensor as well as the response time of the thermal flux sensor. Differential thermopiles can be constructed with a single pair of thermocouples, composed of at least two thermocouple junctions or joints, or multiple pairs of thermocouples. Differential thermopiles do not measure absolute temperature, but instead generate a differential voltage output that is indicative of (e.g., proportional to) the local temperature difference or temperature gradient. This temperature gradient, as mentioned above, is a consequence of the heat transfer (e.g., heat flow) that occurs through the differential thermopile and / or the thermal resistance layer and, thus, indicates a measurement of the heat transfer (e.g., heat flux) that occurs across the differential thermopile and / or thermal resistance layer. An example differential thermopile for heat transfer measurements is constructed using thin film and polyimide materials (i.e., the thermal resistance layer) to create a thin heat flux sensor with accurate readings and a fast response time ( "1 second). Other examples could be differential thermopiles constructed by means of one or more electrically conductive through holes (i.e. VIAs) in a thermal resistance layer. Other examples could include devices that are based on differential thermopile technology although they are designed to convert thermal energy into electrical energy, for example, through thermal energy harvesting (e.g., thermoelectric generators (TEG)). In addition to harvesting or collecting thermal energy, these devices can be used as heat flow sensors since they can output a differential voltage indicative (e.g., proportional to) of heat transfer (i.e., thermal energy). that happens or is presented through the device. However, due to different design criteria, current TEG technology is often expensive and has a large form factor when compared to differential thermopiles that are designed for thermal flux sensor applications. Thus, the use of these devices can cause difficulty of use and / or inaccuracy of heat transfer measurements (for example, thermal flux) as well as a slow response time. Another example is textile-based heat flow sensors where a differential thermopile is constructed within the fabric or other materials designed to be used or otherwise in contact with or in proximity to, for example, the human body. For simplicity, the heat transfer measurement measured by heat flow sensors as used in this application is heat flow with units of W / m2. This is an example and non-limiting measurement of heat transfer that can be used for NITI and / or associated topics (e.g., thermal flux sensor design, effects of thermal contact resistance, methods of data processing, etc.). An example of a thermal flux sensor based on differential thermopile technology that has a thickness t, a width W, and a length H is shown in Figure 1. The detection area is defined by a width A and a length B , and the sensor outputs include thermal flux output voltage leads (i.e., output leads). A cross section of an example differential thermopile that includes a thermal resistance layer is shown in Figure 2A where k is the thermal conductivity of the thermal resistance layer, Ti is the hot temperature tip, T2 is the cold temperature joint, ΔΤ is the temperature difference between Ti and T2y equivalent to the temperature difference across the thermal resistance layer, and Δν is the differential voltage output between the pair of thermocouples connected in series and is directly indicative of ΔΤ (e.g. , proportional to), which is a consequence of q, the thermal flow that occurs or occurs through the thermal resistance layer. The greater the number of thermocouple pairs, the greater the sensitivity of the heat flux sensor (the greater the Δν for a given quantity of q). In this example, each temperature joint or junction is formed by connecting two different thermoelectric materials (e.g., Ml and M2) through the thermal resistance layer. Different thermoelectric materials could include materials that have different Seebeck coefficients for the purpose of generating a thermoelectric voltage (for example, copper and constantane, copper and nickel, copper and silver, antimony and tellurium, bismuth in series, positively doped and negatively doped materials, p-type semiconductor materials and n-type semiconductor materials, etc.) Another example of a differential thermopile is shown in Figure 2B that includes two different thermoelectric materials (i.e., MI and M2) as well as an electrical conductor (M3). In this example embodiment, M3 is used to connect MI and M2 in series through the thermal resistance layer. This exemplary differential thermopile configuration has exemplary benefits including lower manufacturing cost, higher sensitivity, greater design freedom, etc. and could be realized using one or more manufacturing technologies (e.g., MEMS base, NEMS base technologies, CMOS base technologies, additive base technologies, etc.). In other exemplary embodiments, manufacturing could further be simplified where M3 has been designed to be of the same material as MI or M2. When a thermocouple junction is formed by pressing two similar or dissimilar metallic materials together or when a temperature sensor is brought into contact with an object surface, only a small fraction of the nominal surface area is actually in contact due to the lack of flatness and roughness of the contact surfaces. If heat flow is imposed through the joint and / or contacting surfaces, the heat flow (i.e., thermal energy) is generally restricted to conduction through the contact sites. See example shown in Figure 3. The limited number and size of contact sites results in the actual contact area being significantly smaller than the apparent contact area. This limited contact area and the presence of gaps causes a thermal resistance referred to as contact resistance or thermal contact resistance (Re). The presence of thermal contact resistance (Re) affects the quality of temperature measurement. Specifically, the presence of thermal contact resistance (Rcj) between a temperature sensor, for example, of an example NITI embodiment and the surface of the object causes inaccurate temperature readings. In other words, the current surface temperature of an object differs from that measured by a temperature sensor even when proper contact and thermal bypass design has been achieved, for example, by means of thin-walled thermocouple technology. This inaccuracy is related to the amount of the thermal contact resistance (Re) present (typically, constant) and the thermal flow that occurs or occurs through it in a specified time. This relationship is expressed later, mathematically: Tyur / acelO — TicflsoríO—fenseríO * ΠΙ where the heat flux is defined to be positive when it enters the object and where: t is a specified time, qsensor(t) is the measured heat flux at the specified time, Tsensord) is the measured surface temperature of the sensor (i.e., the measured sensor temperature, the measured temperature) at the specified time, and Tsurfaced ) is the current surface temperature at the specified time. For this application, unless the context indicates otherwise, the thermal contact resistance (Re) between a temperature sensor of an exemplary NITI sensor embodiment and the surface of the object could be referred to as the contact resistance between the NITI sensor and the object surfaces. An example CHFT+ embodiment is shown in Figure 4 that includes a heat flux sensor and a temperature sensor placed on a surface of an object with unknown internal properties relative to an internal region of the object and where a heater (i.e. , the external thermal device) is placed on the thermal flow sensor. In this example, a thermal flow sensor contacts a temperature sensor which in turn contacts a surface of the object. Once again, the area 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ Limited contact between the temperature sensor and the surface of the object causes a thermal resistance between the temperature sensor and the surface temperature of the object and is shown as a thermal contact resistance (Re). Additionally, coatings (e.g., as a result of protective coatings, adhesives, etc.) on the temperature sensor may impact (e.g., may increase) the amount of thermal contact resistance (Re). present. The heat flux (q) is shown as a vector pointing towards the object and is defined to be positive in this direction. In this way, as indicated in equation [1], the current surface temperature of the object (Tsurface (t)) is determined using the measured temperature of the temperature sensor (Tsensor(t}), the measured heat flux of the thermal flow (qsensor(t)), and the thermal contact resistance (Re). In some example embodiments, an effort could be made to minimize the thermal contact resistance (Re) for the purpose of assuming a value of 0 in the equation [1].This could be done, for example, by using thermally conductive adhesives between the contact surfaces. In other exemplary embodiments, to obtain an accurate measurement of the current surface temperature (Tsurface(t;), an estimated value for the thermal contact resistance (Re) may need to be determined (e.g., measured). In some cases, the value of the estimated thermal contact resistance (Re) (i.e., the thermal contact resistance (Re)) could be determined to be negligible. In other cases, the value of the estimated thermal contact resistance (Re) could be determined using predetermined specifications, for example, from a manufacturing specification for an adhesive tape used to mount a NITI sensor. Example modalities are capable of taking precise or accurate NITI measurements of an object if performed in Ready or Transient State environments. The example embodiments use heat flux boundary conditions in their respective thermal mathematical models (heat flux is an input) which are more robust and accurate than temperature base boundary conditions. Example outputs include precise values ​​for the internal properties of an object such as an internal temperature distribution of the internal region of the object and / or one or more internal parameters of the object. Referring to Figure 5, an exemplary CHFT- embodiment includes a heat flux sensor and a temperature sensor placed on a surface of an object with unknown internal properties. An example application is in situations where there is some form of an external thermal event occurring, for example a CHFT- is placed in a motor where the external thermal event is heat. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ produced and emitted by the engine. Another application is where the CHFT- is placed in the body of a human or other animal, for example, an athlete exercising. In this last example, the combination of body heat dissipation and airflow moving through the CHFT corresponds to an external thermal event. Other external thermal events could be originated from a thermal or heat lamp, a fan, a heat sink, solar radiation, contact with other objects (for example, metal plates), etc., that are not used with a set of control circuits that is intended for NITI (i.e., an uncontrolled external thermal event). To limit heat flow noise and sporadic recording signals as a result of, for example, small environmental changes and / or other external stimuli, a thermal insulation piece (i.e., a thermal insulation layer or insulating piece) could be placed at the top of the CHFT- as shown in Figure 6A. This piece of insulation acts as a filter and only allows substantive heat flow and temperature signals to be detected by the CHFT-. Additionally, the thermal insulation piece can be used to control (i.e., limit, increase, etc.) the amount of thermal flux that occurs through the CHFT-. The thickness, material, form factor and size of the insulating piece depend on the application of the CHFT- that is being used among other factors. In some example embodiments, the thermal insulation could be embedded within a substrate or material on which the thermal flow sensor and / or temperature sensor is mounted. For example, air gaps or other areas with low thermal conductivity could be designed within a printed circuit board (e.g., a rigid and / or flexible material) that is used to position and electrically connect to the thermal flow sensor and / or the temperature sensor. Figure 6A shows an example where the thermal insulation piece is adapted to cover the entire pair of thermal flow-temperature sensors. In other example embodiments, as illustrated in Figure 6B, the insulating piece could also overlap the surface areas of the object that surround the heat flow sensor-temperature sensor pair. In some example embodiments, as illustrated in Figure 6C, the thermal insulation piece or additional thermal insulation could be specified to surround the heat flow sensor and / or the temperature sensor to minimize thermal loss. In some example embodiments, the thermal insulation materials could include metals or other thermally conductive materials that are designed to enhance and increase the amount of heat flow that occurs through the CHFT-. The insulation, filtering, and heat flow control techniques shown in Figures 6A-6C could optionally be used for some or all NITI sensor modalities. Referring to Figure 7A, exemplary CHFT+ embodiments include a thermal flow sensor, a temperature sensor, and an external thermal device, e.g., a heater, a cooler, a fluid flow channel, a fan, a heat lamp etc. which is used with a set of control circuitry that is intended for NITI. In particular, CHFT+ modes are useful when no external thermal events occur and, for the most part, ready-state conditions are maintained. However, these could also be used in situations where an uncontrolled external thermal event is occurring. With the external thermal device, the CHFT+ can generate a controlled thermal event that creates a transient response (i.e. different thermal signals). For example, the external thermal device may cycle power from the heater (i.e., an external thermal device) to provide a periodic thermal event on an object surface. When necessary, external thermal devices can be controlled to achieve standby conditions. In other example embodiments, a CHFT+ could include more than one external thermal device. By 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ For example, both the Peltier heater and the Peltier cooler could be used as external thermal devices for the purpose of creating thermal heat sources and thermal heat sinks as needed. As another example, a single Peltier device could be used as the external thermal device to achieve both thermal cooling and heating. In Figure 7A, a heater is illustrated as an example of an external thermal device. In this example, the heater (i.e., the external thermal device) is designed to provide the thermal event to the area surrounding the entire heat flux-temperature sensor pair, as well as the object surface areas surrounding the pair. of thermal flow sensors-temperature sensor. In Figure 7B, another example embodiment is illustrated where the heater (e.g., the external thermal device) is designed to provide the thermal event to the area surrounding the entire heat flux-temperature sensor pair only. A top view of an exemplary CHFT+ embodiment is shown in Figure 7C which includes a temperature sensor with output leads (i.e., an output terminal connection), a thermal flow sensor with output leads (output terminals). example output), and a heater (an example external thermal device) with power conductors (example power terminals). In this example, the output and power conductors are connected (e.g., soldered) to the corresponding output terminals of each component. In other exemplary embodiments, the output terminals could be connected to other terminals (e.g., electrically conductive pads) designed for through-hole or surface-mount devices, for example, by utilizing rigid printed circuit board technologies and / or flexible. In other exemplary CHFT+ embodiments, a heater could be constructed, for example, within a printed circuit board by means of trace patterns with a controlled resistance, shape and / or size that connect directly to a power source within the assembly. of circuits. This could facilitate manufacturing processes given the embedded aspect of this design. In some example NITI sensor embodiments, one or more temperature sensor output leads could be connected to a ground terminal and / or reference resistor that could be used as a part of the circuitry to take temperature measurements based on the resistance of the temperature sensor (e.g. thermistor). In other example embodiments, as illustrated in Figure 7D, the temperature sensor could be located on or near the opposite side of the thermal flow sensor detection area that is in contact with the surface of the object. In these example embodiments, the output of the temperature sensor could be assumed to be the same as the output of a temperature sensor as configured in Figure 7A. Above all, this is the case where the heat flow sensor has negligible thermal resistance as a result of its design (e.g., low thickness, high thermal conductivity, etc.) and / or where a heat flow condition is created. from scratch. In other exemplary embodiments, for example, embodiments where the thermal resistance of the heat flow sensor could not be negligible, one or more of the effects of the thermal resistance of the heat flow sensor could be modeled as a part of the contact resistance between the surfaces of temperature sensor and object. In other exemplary embodiments, for example, embodiments where the number of the heat flow sensor joints and the sensitivity of the heat flow sensor are precisely known, the output of the heat flow sensor could be used to determine the temperature difference through the heat flow sensor in real time so that the output could be combined with the temperature sensor in Figure 7D to determine the temperature between the heat flow sensor and the surface of the object. In other example embodiments, as illustrated in Figure 7E, the temperature sensor could be embedded within the heat flow sensor and / or the heat flow sensor detection area. In other example embodiments, as illustrated in Figure 7F, the heat flow sensor and the temperature sensor could be located on either side of a substrate while avoiding measurement mismatch. For example, the thermal flow sensor and the temperature sensor could be aligned on either side of a substrate (e.g., a flexible printed circuit board) so that the thermal flow sensor and / or the temperature sensor detection area heat flow around the temperature sensor on the opposite side. This could be achieved, for example, by placing the heat flux sensor below or on top of the temperature sensor i.e. on the opposite side of the substrate. In these example embodiments, the thermal flow sensor and / or the temperature sensor could further be surrounded by and / or be in contact with other thermally compatible materials (for example, materials with thermal resistances close to the temperature sensor / or thermal flow) to ensure a uniform flow of thermal energy (e.g. heat flow) through the thermal flow sensor and the temperature sensor. An example embodiment is illustrated in Figure 7G. The non-limiting features of the example embodiments illustrated in Figures 7D-7G could optionally be used in any of the NITI example embodiments, including the CHFT example embodiments. SYSTEM MODALITIES WITH ONE OR MORE PAIRS OF THERMAL FLOW-TEMPERATURE SENSORS TO DETERMINE ONE OR MORE INTERNAL PROPERTIES OF AN OBJECT An example NITI system for performing NITI using the CHFT- is illustrated in Figure 8. The CHFT- includes a temperature sensor and a heat flow sensor (ie, a heat flow-temperature sensor pair). In other exemplary embodiments, the CHFT could include more than one temperature sensor and / or more than one heat flow sensor (e.g., multiple pairs of heat flow-temperature sensors). The configuration of the temperature sensor and the thermal flow sensor between each other and the object could be, for example, as illustrated in any of Figures 5 and 6A6C. The analog signal outputs of the temperature sensor and the heat flow sensor corresponding to the analog signals of the measured temperature sensor and the measured heat flow sensor are provided by means of suitable communication paths (for example, electrical conductors) and They are converted into digital signals by the data acquisition circuitry (DAQ), which could include, for example, one or more analog-to-digital converters (ADC), microcontrollers, etc. The DAQ circuitry provides the digital signals from the measured temperature sensor and the heat flow sensor 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ measured via suitable communication paths (e.g., electrical conductors, radio signals, etc.) to the control circuitry for processing as described in more detail below. The control circuitry could include one or more appropriately configured computers, microprocessors, DSPs, FPGAs, or other data processors. The proper configuration of the control circuitry could be implemented in hardware, in software, or a combination. The control circuitry includes or is in communication with an output such as a display, a network, a cloud computing system, a communications device such as a cell phone, wearable technology, etc. The output could also be used for one or more control operations such as sensor activation and deactivation, remote monitoring, measurement start / stop, data logging, temperature control, power control, system failure monitoring, preventive maintenance monitoring, diagnostics, system performance, data entry, data visualization, analytics, etc. An example NITI system for performing NITI with a CHFT+ is illustrated in Figure 9. Like the CHFT-, the CHFT+ includes a temperature sensor and a heat flux sensor (i.e., a pair of heat flux-temperature sensors). In other example embodiments, the CHFT+ could include more than one temperature sensor and / or more than one heat flow sensor (e.g., multiple heat flow-temperature sensor pairs). Additionally, the CHFT+ includes an external thermal device such as the resistive heater shown. The configuration of the temperature sensor, the thermal flow sensor, and the external thermal device between each other and the object could be, for example, as illustrated in any of Figures 7A-7G. In other example embodiments, the CHFT+ could include more than one external thermal device (e.g., a heater and a cooler). The analog signal outputs of the temperature sensor and the heat flow sensor corresponding to the analog signals of the measured temperature sensor and the measured heat flow sensor are provided by means of suitable communication paths (for example, electrical conductors) and They are converted into digital signals by data acquisition circuitry (DAQ), which could include, for example, one or more analog-to-digital converters (ADC), microcontrollers, etc. The DAQ circuitry provides the digital signals from the measured temperature sensor and the measured heat flux sensor via suitable communication paths (e.g., electrical conductors, radio signals, etc.) to the control circuitry for the processing as described in more detail below. The control circuitry could include one or more appropriately configured computers, microprocessors, DSPs, FPGAs, or other data processors. The proper configuration of the control circuitry could be implemented in hardware, software, or a combination. The control circuitry includes or is in communication with an output such as a display, a network, a cloud computing system, a communications device such as a cell phone, wearable technology, etc. The output could also be used for one or more control operations such as sensor activation and deactivation, remote monitoring, measurement start / stop, external thermal device operation, data logging, temperature control, power monitoring, system failure monitoring, preventive maintenance monitoring, diagnostics, system performance, data entry, data visualization, analytics, etc. In this non-limiting example, the external thermal device is controlled using a relay (an example switch), and the relay is operated by a relay signal from the DAQ which in turn provides the relay signal based on the input of the control circuitry. A flow chart is shown in Figure 10 outlining example procedures performed by the control circuitry in an example non-limiting NITI system that includes an NITI sensor to determine one or more internal properties of an object, which includes an internal temperature distribution of the internal region of the object at one or more times specified using the measured heat flux, the measured temperature, and determined values ​​of internal parameters of the object. A measured temperature signal is received by the temperature sensor control circuitry at one or more specified times (SI step). The control circuitry also receives a measured heat flux signal from the measured heat flux sensor at one or more of the specified times to produce a measurement of the heat transfer leaving or entering the object at the surface (step S2 ). The control circuitry determines the values ​​of the internal parameters at one or more of the times specified in step S3 and determines an internal temperature distribution of the internal region of the object at one or more of the times specified based on the measured temperature signal, the measured heat flow signal, and the values ​​of the internal parameters in step S4. The control circuitry generates information (e.g., for the output) indicating the internal temperature distribution at one or more of the specified times (step S5). The control circuitry also generates information (for example, for output) that indicates one or more 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ of the internal parameters at one or more of the times specified in step S6. Optionally, the control circuitry could perform step S6 before step S5 and / or optionally could not perform step S4, step S5, and / or step S6. The control circuitry could optionally perform step S2 before step SI. In some example embodiments, the control circuitry could optionally perform step S3 before step S2 and / or step SI. Additional procedures could be used in additional example embodiments. For example, a thermal mathematical model (i.e., the thermal model) of the object is determined and appropriate initial and boundary conditions are prescribed for the purpose of solving a thermal mathematical solution (i.e., the mathematical solution). Thermal mathematical models and corresponding thermal mathematical solutions could be found in the heat transfer literature for more general cases, while models for more unique cases may need to be derived and solved. A variety of methods for the derivation and / or resolution of a thermal mathematical model could be used, including, but not limited to, analytical methods, finite difference methods, numerical methods, etc. Thermal mathematical models could be based on one-dimensional heat transfer or the 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ multi-dimensional (e.g. two-dimensional) heat transfer. For a more accurate, robust and consistent NITI, thermal mathematical model boundary conditions are defined that include a surface heat flux boundary condition that gives rise to a thermal mathematical solution (e.g. internal temperature distribution) for the object with a thermal flow inlet. A surface heat flux boundary condition can be used because the NITI sensor directly measures heat flux using, for example, a heat flux sensor on the surface of the object. In this way, the heat flux can be used directly in the thermal mathematical model (i.e., the heat flux boundary condition) which causes a heat flux input in the corresponding thermal mathematical solution (i.e., the mathematical solution). A detailed but still exemplary one-dimensional thermal mathematical model (i.e., a thermal model) is provided in Table 1 that includes, a partial differential equation (PDE), suitable boundary conditions, and an initial condition for a semi solid. -infinity (i.e., a semi-infinite half), an example object and a general case in the heat transfer literature. Table 1. Thermal model of a semi-infinite solid with a 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ thermal flux boundary condition PDE dT d2T di dx2 Boundary conditions di x = θ T -* 7% , x -»t» Initial condition T - Tu , t - 0 where: K = thermal conductivity of the object p = density of the object C = thermal capacity of the object a = thermal diffusivity of the object For a constant stage heat flux input occurring at the surface (x = 0) of the semi-infinite medium (object), the mathematical solution of the thermal model in Table 1 is found as: í PfJ —X*· Qocttsu.· üx x121 T(V) - Tn+----^LLexp(}—) κ Tíit k ¿\at where q-sensor, o is the constant stage heat flux input at the boundary. Using the Duhamel method of superposition (an example mathematical method), equation [2] can be derived for thermal flux inputs that change with time which is realistic from the NITI sensor output: 7«QC Ln / Lznz / E / YIAI where m indicates the measurement mth taken by the NITI sensor so that Tm(x, tm) refers to the internal temperature of the object at a depth of x and in the measurement mthwhich corresponds to a time specified (tm) . In this example, equation [3] represents the thermal mathematical solution, that is, the mathematical expression for the internal temperature distribution of the internal region of the object, for the example non-limiting thermal model specified in Table 1. Evaluating equation [3] on the surface (x = 0) and realizing that a = m 2 fsur / are.m—Tsurface.O f / (.Qsvusor, / —Q&'nsOr.;-!)—L-i X — -—— |4J where Tsurface,™ is the calculated surface temperature of the example object modeled in Table 1. Note that in this example, equation [4] is a function of the surface temperature of the object at state conditions prepared (Tsurface / θ) and is determined, for example, before or after a transient thermal event. Equation [4] is also a function of surface heat flux measurements at one or more specified times (qsensor,m) and the square root of the product of the thermal conductivity of the object (k), the density of the object (p), and the specific thermal capacity of the object (C). This internal parameter of the object (y'kpC} is commonly referred to as thermal inertia (i.e., thermal effusivity). The calculated object surface temperature that is determined in equation [4] may be used with a data processing method that could include, for example, one or more parameter estimation schemes. For NITI sensor output values ​​(i.e., heat flux and temperature) measured at one or more specified times, the data processing method could compare the measured sensor temperature against the calculated surface temperature that is found, at this For example, when using equation [4]. Among other things, this allows the determination of estimated values ​​for the corresponding internal parameters of the object; in this case, the internal parameter of the thermal inertia (i.e. thermal effusivity) of the object (^kpC) In other data processing methods, estimated values ​​for the internal parameters, in this example, of the thermal conductivity of the object (k), the density of the object (p), and the specific thermal capacity of the object (C) could be determined , individually. For example, for the case presented above, predetermined values ​​of density (p) and specific heat capacity (C) could be determined from reference materials such as a textbook or manufacturing specification, allowing the data processing method determines the estimated value for the thermal conductivity (k) based on the estimated value of the thermal inertia (i.e., thermal effusivity) of the object ° kpC- In other examples, a different thermal mathematical model could be developed with a corresponding thermal mathematical solution which, which is opposite to equation [4], distinguishes between each individual internal parameter when evaluated at a depth (x) in the object (e.g. x = 0). This would allow the determination of estimated values ​​for each individual internal parameter (e.g., k, p, C, etc.) when used with an appropriate data processing method. The control circuitry could also perform additional steps to improve the accuracy and / or expand the applications of NITI sensors. For example, as mentioned above, the measured sensor temperature is not the same as the actual surface temperature measurement of the object (e.g., semi-infinite solid) due to the presence of thermal contact resistance (Re) between the temperature sensor and the surface of the object. This causes a difference between the current surface temperature of the object and the measured sensor temperature. Thermal contact resistance (Re) could originate from materials that could be layered on the temperature sensor of a NITI sensor as well as the way it is adhered to the surface of the object. The smoothness / roughness of the object surface can also affect the thermal contact resistance (Re) as well as the overall accuracy of the NITI. Thus, a smooth surface might be preferred. Using adhesives (e.g. thermal paste, pressure sensitive adhesives, etc.) to mount the sensor could also affect the thermal contact resistance (Re). Figure 4 illustrates the thermal contact resistance (Re) referring to an example NITI embodiment. In mathematical form, the measured sensor temperature and the current surface temperature can be related by equation [1], shown here in the form of an index of: Tsurface.m—TnMisor.ni—1 -5J where the heat flux is defined to be positive when it enters the object. In an electrical engineering analogy, the thermal contact resistance (Re) could be modeled as a resistor and qsensor,m as the current. In this way, as current (qsensor,m) flows through the resistor (Re), a voltage drop (difference) is created. Here, the voltage difference is analogous to the temperature difference between the surface temperatures of the sensor (i.e., measured) and the object (i.e., current). In some cases, thermal effects associated with the materials used to mount the sensor also need to be considered. For example, one or more effects associated with, for example, the thermal conductivity of the mounting material (k), the density of the mounting material (p), and the specific thermal capacity of the material may need to be included and taken into account. assembly (C) for the thermal mathematical model used for the NITI. For a more accurate NITI, the effects of thermal contact resistance (Re) must be taken into account. Using equation [4] with equation [5] produces a calculated expression for the sensor temperature in equation [6]. TcidLUiLitL-iOa Ai'.lvi.’.' 0 ,ü X Ά ™ . _____________ 2 , + ? fe™, ¡ ~ JXj tr, ~ 6-1X. + ' / λ;,,., * «C vn-y / kfjc Instead of equation [4], equation [6] could be used in a data processing method and for example, if compared against the measured temperature output of the NITI sensor for the purpose of determining 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ the estimated values ​​for one or more internal parameters of the object. An example and non-limiting method for doing this is the definition of an objective function for minimization in a parameter estimation scheme. An example objective function could be defined as the root mean square error (RMSE) between the two different sensor temperature measurements using equation [7]. I M-1 RMSE — J (Tensor,™—í' I where Psurjace.rn 4 Qs<.'n.sor,m — 1^1 In this way, equation [7] can be rewritten as: YO------------------------------------------------- -------------------------------------------------- -------------------------------------------------- -------------------------------------------------- -------------------------------------------------- -------------------------------------------------- -------------------------------------------------- -------------------------------------------------- -------------------------------------------------- ----------------------------! , ^-1 1- 2 RMSE ~ IM, (T^ítr,m- (Tsurfac^m + q's^r.m * B))l . I 'm-1 where M is the total number of measurements taken by the NITI sensor with respect to a period of time (i.e., one or more specified times). It should be noted that depending on the modality, m might not always start at the value of 1 as shown in equation [7] and equation [9]. Similarly, the M-1 amount could also differ depending on the modality. For example, M-1 could be replaced by M-15 or M. In other example embodiments, Μ - 1 could be replaced by m + 30, m + 10, m + 5, etc. which defines the objective function for a specified number of measurements after the mth measurement. In other data processing methods, the derivative-based formulation of the objective function (e.g., equation [9]), for example, could be set equal to zero. The values ​​of the corresponding internal parameters and the thermal contact resistance (Re) that best meet this condition are the estimated determined values. As iterated above, a major component of accurate and practical NITI is the determination of thermal contact resistance (Re). For some cases, for example, low heat flux environments (e.g., zero heat flux conditions) or otherwise imperceptible thermal contact resistance (Re) conditions, the thermal contact resistance (Re) could be ignored or otherwise determined to have an estimated value of zero. Although for many cases, this is not an accurate assumption. In these cases, it may be necessary that an estimated value for the thermal contact resistance (Re), for example, has been determined in advance through prior measurement, which is determined as a part of a data processing method (e.g. for example, by means of a parameter estimation scheme), or is determined otherwise (for example, predetermined by the manufacturing specification). One way to determine an estimated value of thermal contact resistance (Re) is to include it as an unknown variable in a data processing method that could include a parameter estimation scheme. The combination of the corresponding internal parameter values ​​and the thermal contact resistance (Re) value that generate the best match between the calculated sensor temperature and the measured sensor temperature, i.e., the smallest error, could be considered to be the estimated determined values ​​(i.e., the optimal output values). For example, for the general and example case of the semi-infinite object presented above, for each attempted (e.g., guessed) value for S'k / >C, , a series of different values ​​Re is also attempted and entered in equation [6]. For each combination of attempted values ​​yjkpC, and Re, the result of equation [6] (i.e., the calculated sensor temperature) is compared against the measured sensor temperature as an output by the NITI sensor. This comparison can also be performed, for example, by means of an objective function such as the one defined in equation [7]. In this example, the combination of the attempted values ​​for the internal parameters (e.g. yíkpC. ) and the thermal contact resistance (Re) that generate the best match between the calculated sensor temperature and the measured sensor temperature, i.e. , the smallest error (e.g., the smallest RMSE value), could be considered to be the estimated determined values ​​(i.e., the optimal output values). However, this example procedure (i.e., a brute force data processing method) could be time consuming, especially when more accurate results are desired. Consequently, this procedure makes most NITI applications impractical. Although time consuming, this technique is more accurate and faster than a brute force data processing method that is based on a mathematical solution found using a temperature-based boundary condition. This is a result of the complexities and limitations of the temperature base boundary conditions. Another procedure is to determine the estimated values ​​of the corresponding internal parameters (e.g. ^ / T / T7, ) and the value of the thermal contact resistance (Re) by means of an optimization scheme. For example, an optimization scheme could be designed to minimize the objective function (e.g., equation [7]), e.g., by linearly varying combinations of the internal parameter values ​​(e.g., jkpC, ) and the value of thermal contact resistance (Re). This procedure might produce faster results when compared to the brute force data processing method described above although it might not be as accurate. A novel procedure for determining an estimated value for thermal contact resistance (Re) is determination (e.g., calculation) based on the internal properties of the object. Significantly, this reduces processing time and makes the technology more practical for many applications. This procedure takes advantage of the thermal contact resistance (Re) which is constant with respect to time. Thus, at any specified time or at any given measurement, the thermal contact resistance (Re) is equivalent to the thermal contact resistance (Re) at the previous or subsequent measurements or specified times. In mathematical form, this can be expressed as: Kc=«cf¡HOJ where n indicates the measurement mthtaken by the sensor NITI (total of N measurements over a period of time). Thus, for purposes of this non-limiting example, N = M. Additionally, the quantity n could differ depending on the modality. For example, n could be replaced by η - 1 or n + 1. Given this consistency, the thermal contact resistance (Re) at a specified time or measurement is equivalent to the average thermal contact resistance at 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ throughout the entire period of time for which these measurements are being taken and can be expressed as: VjV-1 p[HJc πN - 1 Furthermore, equation [5] can be rearranged as: «cfl=-----------;;-------L121 The combination of equation

[10] , equation

[11] , and equation

[12] produces: -1 tensor,n ~ / jur / 'gcejin_1ai|Ήο,, _ 45^71507,71l ‘Jc“ / V - 1 With respect to the example data processing method described above, inputting equation

[13] into equation [9], an example objective function of a parameter estimation scheme, results in: / AQCLn / LZnZ / E / YIAI It should be noted that, depending on the example modality, n might not always start at the value of 1 as shown in equation

[14] . Similarly, the quantity N -1 could also differ depending on the modality. For example, N - 1 could be replaced by N - 15 or N. In other example embodiments, N-l could be replaced by n + 30, n + 10, η + 5, etc., which defines equation

[13] for a specified number of measurements after the nth measurement. Compared to equation [9], this version of the example objective function in equation

[14] is largely independent of thermal contact resistance (Re). The only term that is dependent on the thermal contact resistance (Re) is Tsurface,o where, as a result of equation [5], it is defined as Tsensor.o qsensor,o x Re. It should be noted that, in many cases, the quantity qsensor, or x Re could be imperceptible or negligible. In cases where it is not negligible, better design is needed and the quantity qsensor, or xRe, might need to be taken into account. An example method of achieving this is by attempting (for example, guessing) an initial value for the thermal contact resistance (Re) before performing, in this example data processing method, a parameter estimation scheme. Regardless of the intended initial value, the parameter estimation scheme will determine the precise estimated value for the thermal contact resistance (Re) as well as the precise estimated values ​​for the internal parameters. As a part of a data processing method, using equation

[14] as the objective function in a parameter estimation scheme greatly reduces the time required to take NITI measurements. For comparable precision and using the same computer, the inventor determined that this data processing method could be completed in less than 1 second of processing time as compared to approximately 15 minutes when using a data processing method based on the brute force procedure described above for the same data set (75 seconds of data - 1 HZ sampling rate). Finally, another non-obvious procedure is the determination of an estimated value for the thermal contact resistance (Re) as a function of internal parameters and the total ready-state thermal resistance (Rciotai) of a given object. A non-limiting example of this is described below for a NITI example application. It should be noted that these procedures for the determination of thermal contact resistance (Re) are not limited to the specific method of data processing and / or NITI technique. Instead, they can be used as general expressions and procedures for the determination of thermal contact resistance (Re) without regard to the data processing method being used for the NITI and / or NITI application. A flowchart showing example non-limiting procedures for an example data processing method performed by the set is shown in Figure 11. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ of control circuits for the purpose of determining one or more internal properties of an object (i.e. internal properties) and an estimated thermal contact resistance (Re) between the object and sensor surfaces NITI. In this example, the data processing method includes a parameter estimation scheme. The measured surface temperature (i.e., the measured sensor temperature) for the object at one or more specified times, the measured surface heat flux for the object at one or more of the specified times, the initial values ​​for one or more of the internal parameters of the object (for example, R (the ready-state thermal resistance of the object), k, p, C, etc.) at one or more of the specified times, and an initial value for the thermal contact resistance ( D) are entered into a calculated sensor temperature equation (e.g., equation [6]) to generate a calculated sensor temperature for one or more of the specified times. In this example, a difference (e.g., error) is determined between the calculated sensor temperature for one or more of the specified times and the measured sensor temperature for one or more of the specified times. The difference is compared, for example, to a predetermined threshold and if it is larger than the threshold, then the difference is used to adjust one or more of the internal parameter values ​​and the value of the contact resistance / AQCLn / LZnZ / Thermal E / YIAI (Re) . For simplicity, one or more of the adjusted internal parameter values ​​and one or more of the internal parameter values ​​(i.e., unadjusted) are referred to, collectively, as updated values. Adjustment can be done in a number of different modes. For example, subsequent or subsequent values ​​of one or more of the internal parameters and the thermal contact resistance (Re) may be used without considering any trends or patterns originating from the values ​​of the internal parameter and the thermal contact resistance (Re) (Re)used previously. In other examples, adjustments can be made based on the historical difference (e.g., error) originating from the internal parameter and thermal contact resistance (Re) values ​​used previously. In a non-limiting example, if one value of k (e.g. ko) refers to a difference (i.e. error) of 100, and the next value, a larger value, used for k (e.g. k) refers to an error of 200, the control circuitry could try a value smaller than the original value of k (ko) given the increased difference (i.e., error) when using a larger value gue ko (ki) . Once the difference is less than or equal to the threshold or otherwise considered minimum, the control circuitry considers the corresponding values ​​used for the internal parameters and the thermal contact resistance (Re) to be the accurate estimated values. and optimal (that is, out). Then, using, for example, equation [3], the control circuitry generates information (e.g., for the output) that corresponds to one or more of the precise values ​​that indicate the internal temperature distribution of the internal region of the object. Additionally, if desired, the control circuitry generates information (e.g., for output) that corresponds to precise estimated values ​​indicating one or more of the internal parameters for the object such as R, k, p, C,^kpC. etc. and the thermal contact resistance (Re). The procedure just described is an example non-limiting NITI periodic method of data processing performed by control circuitry that could determine the internal parameters (eg, R, k, p, C, etc.) of the object, the thermal contact resistance (Rc) between the temperature sensor and object surfaces, the internal temperature distribution of the internal region of the object (eg, Tm(x, tm) ), etc. By post-processing the heat flux and temperature signals output from a NITI sensor placed on the surface of the object and while it might be subjected to a thermal event. For the CHFT+, this thermal event could be generated, for example, by an external thermal device used with the control circuitry. While the CHFT- is designed to operate, for example, under external thermal event environments such as body heat dissipation, engine block heat loss, convective cooling or heating, etc. which are not used with the control circuitry. Because this procedure can be performed so quickly by the control circuitry, the data processing can be performed in real time as the heat flow and temperature signals are being measured and provided as inputs to the control circuitry. With each additional measurement, the data processing method is repeated, values ​​for one or more of the internal properties of the internal region of the object (i.e., the internal properties) are determined and, for example, information is generated for the exit. Other methods (ie, techniques) of the NITI could be performed, for example, by modifying the thermal mathematical solution (eg, equation [3]) in different ways depending on the internal properties of interest. Non-limiting examples of modified thermal mathematical solution arrangements and corresponding NITI methods are provided below for different applications. Each of these applications has the corresponding thermal mathematical models. In general, depending on the NITI application and procedure used, different data processing methods could be used to determine estimated values ​​for one or more internal properties of an object. Some of these methods might use parameter estimation schemes while others might not and instead, for example, might rely on calculus. In other exemplary embodiments, various mathematical operations could be performed, for example, on the thermal mathematical solution (e.g., derivative operations, integral operations, etc.) to determine (e.g., by means of a data processing method ), one or more internal properties of an object. SYSTEM MODALITIES WITH ONE OR MORE PAIRS OF PARALLEL HEAT FLOW—TEMPERATURE SENSORS TO DETERMINE ONE OR MORE INTERNAL PROPERTIES OF AN OBJECT NITI example system modalities that acquire heat flux and object temperature measurements in parallel using multiple (at least two) NITI sensors (e.g., CHFT+ or CHFT-) are referred to as DUO NITI modalities. In addition to enabling simpler and more robust NITI of objects, DUO NITI modalities eliminate uncertainties that could be associated with the non-limiting example NITI system modalities and / or methods described above for the NITI system modalities. example CHFT+ and / or example CHFT-NITI. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ For the purpose of taking measurements in parallel, each NITI sensor in the exemplary DUO NITI embodiments could have different values ​​of heat flux detected by each heat flux sensor, which correspond to a difference in the amount of heat flux that occurs or occurs. at each NITI sensor location, which is also called a sensor node. This aspect of the DUO NITI example modalities is referred to as a differential heat flow environment. The following example modalities could be used to achieve this condition. Typically, as a result of the differential heat flow environment, the temperature measurements at each sensor node (i.e., node) also differ. One way to create a differential heat flow environment with an example DUO CHFT+ (multiple CHFT+ nodes) modality is by varying the amount of thermal energy provided by each external CHFT+ thermal device (e.g., heater). In the case of a heater, this can be achieved, for example, by differentiating the voltage provided to each heater, by differentiating the electrical resistance of each heater, by differentiating the energy density of each heater, etc., to create the environment of differential thermal flow required. A cross section of an example DUO (NITI parallel sensor nodes) CHFT+ (with heater) modality is shown in Figure 12. In this example embodiment, each NITI sensor (i.e., the sensor node or node) contains a pair of thermal flow temperature sensors and includes a heater (i.e., the external thermal device) as a result of being the CHFT+ nodes. If an external thermal device (e.g. heater) is not an option, desired or used, another way to create a differential heat flow environment is to place different amounts of thermal insulation at each sensor node. The insulation can be used to control (i.e., limit, increase, etc.) the amount of heat flux that occurs through the sensor node. Different amounts of thermal insulation can be achieved by means of different thickness and / or insulating materials. Thermal insulation could include metals or other thermally conductive materials designed to enhance and increase the amount of heat transfer that occurs through the sensor node. Additionally, the insulation could act as a filter and only allow substantive heat flow and temperature signals to be detected by the NITI sensor (e.g., CHFT+ or CHFT-). Insulation could also be used to protect the NITI sensor from external damage and / or external stimuli that could affect measurement quality. A cross-section of an example DUO (NITI Parallel Sensor Nodes) CHFT- modality is shown in Figure 13 with different amounts of thermal insulation in each sensor node to facilitate a differential heat flow environment. In exemplary NITI embodiments, the thermal insulation properties used in a sensor node do not need to be known, experimentally determined, or calibrated to take measurements of one or more internal properties of the object. Alternatively, for example, when signal noise might not be a problem, one CHFT- node could incorporate thermal insulation while exposing the other CHFT- node. The cross section of this example embodiment is shown in Figure 14. Another example embodiment in Figure 15 shows the cross section of a DUO CHFT+ / - system where one sensor node incorporates a CHFT+ and one sensor node incorporates a CHFT-. Yet another example embodiment of a cross section of a CHFT-DUO system is illustrated in Figure 16. This example embodiment might be appropriate in cases where external thermal events are specific to individual sensor nodes. For example, one sensor node is heated by a lamp while another is cooled by a fan. Another exemplary embodiment in which a differential heat flow environment is created includes the use of materials with a different thermal resistance for each pair of heat flow-temperature sensors. For example, a sensor node incorporates an example NITI modality (e.g., CHFT-) made with materials of high thermal resistance and a sensor node incorporates an example NITI modality (e.g., CHFT-) made with materials of high thermal resistance. a low thermal resistance. This difference in overall thermal resistance at each sensor node allows a differential thermal flow environment to be realized. Different thermal resistance could be introduced in exemplary NITI embodiments, for example, through conductive or insulating pathways / separations within one or more of the materials used for adhesion, connection, housing and / or contact with the thermal flow sensor. and / or the temperature sensor (for example a rigid and / or flexible printed circuit board, adhesives, substrates, etc.). In other exemplary embodiments, the heat flow sensor and / or the temperature sensor of a sensor node could be manufactured using materials of low thermal conductivity and / or a specified thickness while the heat flow sensor and / or the temperature sensor of another sensor node could be manufactured using high thermal conductivity materials and / or a different specified thickness. As a result of one or more of the parallel sensor nodes incorporated in the DUO NITI example embodiments, innovative signal measurement and data processing methods are possible in addition to performing the CHFT+ and CHFT- example methods described above. (where the sensor nodes are operated,independently). For general demonstration purposes, example non-limiting and differential methods of quotient arithmetic basis data processing are described below for the NITI DUO system when operating in differential heat flow environments. In this example, two NITI sensor nodes (i.e., sensor nodes) are modeled by being placed on a given object, where the internal properties of the object are assumed, in this example, to be uniform across the two sensor node locations. sensor. This results in the following example independent equations at each sensor node (nodes 1 and 2): Τν·.™. “«Μ,™,.··. ,Γ X + « * I 'A.™,·) ! + v-n : , X ~ t¡ ,) j | 1 5 | ’,r. - < ,r X = Lnrrruul + « X ! + X Ψ G ,r. ~ f 1 ) I > M where Tintemai is the internal temperature (i.e., the internal temperature distribution) of the object, and ψ is a response function that takes into account the transient effects of heat transfer from the object on one or more specified times. Typically, ψ is derived for each thermal model, independently, and could be a function of one or more internal parameters. This way, 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ this is unique, typically for a given NITI application and the corresponding thermal model. In some example DUO NITI embodiments, initial values ​​for one or more of the internal parameters may need to be determined at one or more specified times for purposes related to the response function (ψ). These initial values ​​could be predetermined (e.g., from a textbook, reference material, etc.), estimated (e.g., by a data processing method), or otherwise determined. In some example embodiments, the initial values ​​are not changed and are held constant for one or more of the specified times. In other example embodiments, the initial values ​​could be updated or otherwise adjusted at one or more specified times. In a ready-state form, equation

[15] and equation

[16] reduce to: / ót'fLscrl.m—T’ / nternaLm 'Mseníorl.m TÍfníürL'.nt—Inter ηιιί,ιη. f $ Feel 2,m ¢^ + ¾) M ¢^ + ¾) [18| 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ It is noted that equation

[17] and equation

[18] do not include the response function (ψ) that takes into account the transient effects of the heat transfer of the object. Thus, these are not typically limited to specific NITI applications and corresponding thermal models. An example general differential basis data processing method for the NITI DUO system includes determining the difference between equation

[15] and equation

[16] which results in: |19] Reordering: ( A’me.crtr I ^.+:::+:.+1+1,,11-2ynrz rn ^c‘¿) | ^5,.+1+0+1.11—Q.fc.w») +0 Σ / ί-j At / i'irn>url.j—9-l)—^^Sc'TisurZj— L / -l ) Equation

[19] and equation

[20] represent general example forms of the differential basis data processing method of the DUO NITI system where transient effects are taken into account and two sensor nodes are used in parallel. Under ready-state conditions, equation

[20] reduces to: Tveuwri,m—TsenwrZ.ni—Qsensorljn ^Sensorí.m + ^12^ l-H Reordering: Qxensarl „m ^r?1) (^5++-150+2,^1—ys¿-rL-w2,m 9,S'en.™r 1 ,m ^Έϋτίχι>ν2,ιη In this example data processing method, when the thermal contact resistances at each sensor node (Reí and RC2) are known, Equation

[20] and Eq. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ

[22] can be used to determine the ready-state thermal resistance (R'> of the object on which it is based, and thus, is indicative of, the internal parameters of the object. Consequently, if desired, the thermal resistance of Prepared state (R) of the object could be used to determine one or more internal parameters of the object when values ​​are determined (e.g., default, estimated, etc.) for one or more other internal parameters. Non-limiting examples of this are provided later. If an estimated value for the thermal contact resistance at a sensor node (Rd and / or Reo) is unknown, this can be determined (for example, by the example procedures CHFT+ or CHFT- described above) or can be determined in another way (for example, 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ using the default values). When it is determined that the thermal contact resistances in each sensor node (Reí and Rc2) are imperceptible, equation

[20] is reduced to: ^11 ___Lfnjorl.m ~ LenjoriUn__________________________________ fl.Seiwori.n—?,() + X ~ i(-i ) — Σ, = !XVKGh—and equation

[22] reduces to: T _ T π '' V.S'ftfnxrjr 1 ,T7i When the thermal contact resistances in each sensor node are equal (Rc= Reí = Rc2). Equation

[22] reduces to: i,m Ge’nsorz.mr·»-» « Totoi — ~ ~ =[2>] Se n.so-1 1. t r Sensor 2, m where RTotai is the total ready-state thermal resistance of the object and: «Ίν / αί = + Re[^1 An example and general arithmetic quotient basis data processing method for the DUO NITI system includes determining the arithmetic quotient between equation

[15] and equation

[16] which results in: —Qi’ettsan. / nx —mental _ (^St-nsori.O + Σ / -1 mrl .i *—G1)) p? QjfenitirZ.m ^Cz) Turn it / G / Sii.n.wi’.fl + Σ / i ^íicnsurr r ΨΟ πι 1)) Reordering: I : 1 rY¡ , 5 d-5.4- b.,,...,,-Σ2, , y-< ·,. -r, ,}[ Equation

[27] and equation

[28] represent general exemplary forms of the arithmetic quotient basis data processing method of the DUO NITI system where transient effects are taken into account and two sensor nodes are used in parallel. Under ready-state conditions, equation

[27] reduces to: 7 ) hniemat Q.Sen.sar?jn 100 Reordering: „ _ (Ji\η.γπ 1'2.ni / 'C'2 ) 1 ','ηητηιϋ.ίπ- ;~;l·11 ^>11:1 ΪΛΎΙΤ' .¡Τ' ^Λοπ.νιυ' / ITT In this example data processing method, when the thermal contact resistances at each sensor node (Rci and RC21') are known, equation

[28] and equation

[30] can be used to determine an internal temperature distribution (Tin terna im) of the object. If an estimated value for the thermal contact resistance at a sensor node (Rd and / or Rc2) is unknown, this can be determined (for example, by the example procedures CHFT+ or CHFT- described above) or can be determined in another way (for example, by default values). When the thermal contact resistances at each sensor node (Reí and RC2) are estimated to be imperceptible, equation

[28] reduces to: ' ' 11 íI i'üll,® + Σρ, Δί?^™ι·ι,;ΧΜ* - ί· 10 - (fcortji+Σ ! X ¢(1, - ζ 0) and equation

[30] reduces to: Tsensc>r2,mxΤΛΐπνίΓ 1 ,m Í5Fnspr2,m Gnfernaf.m— :“ L-i—J ^5 mi yn r 1, m tfs ct sor 2 .τη Equation

[32] is also of the form of equation

[30] when the thermal contact resistances at each node 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 101 of the sensor are equal (Rc= Reí = Rci'). As mentioned above, the non-limiting and exemplary transient forms of, for example, the arithmetic quotient and differential basis data processing methods are typically unique to each NITI application and thermal model given the presence of the response function. (ψ). However, the Ready State forms, for example, of the non-limiting example differential and arithmetic quotient basis data processing methods are typically universal and applicable for almost any NITI application and the corresponding thermal model. An example NITI system for performing NITI with parallel pairs of heat flux-temperature sensors (i.e., the DUO NITI system) to determine one or more internal properties of an object is illustrated in Figure 17. Two NITI sensors (one is referred to as the first and the other as the second to distinguish them) are shown (although more than two NITI sensors could be used), and each NITI sensor (for example, CHFT+ or CHFT-) includes a temperature sensor and a heat flow sensor (i.e., the heat flow-temperature sensor pair). In other example embodiments, each NITI sensor could include more than one temperature sensor and / or more than one thermal flow sensor. The configuration of temperature sensor and thermal flow sensor for each NITI sensor with each other, with other NITI sensor, and the object could be 102 as illustrated in any of the non-limiting examples shown in Figures 12-16. Temperature sensor and heat flux sensor analog signal outputs corresponding to the measured temperature sensor and measured heat flux sensor analog signals of each NITI sensor are provided via appropriate communication paths (e.g., electrical conductors) and are converted into digital signals by the data acquisition circuitry (DAQ), which could include, for example, one or more analog-to-digital converters (ADC), microcontrollers, etc. The DAQ circuitry provides the digital signals from the measured temperature sensor and the measured heat flux sensor via suitable communication paths (e.g., electrical conductors, radio signals, etc.) to the control circuitry for the processing as described above and below. The control circuitry could include one or more appropriately configured computers, microprocessors, DSPs, FPGAs, or other data processors. The proper configuration of the control circuitry could be implemented in hardware, software, or a combination. The control circuitry includes or is in communication with an output such as a display, a network, a cloud computing system, a communications device such as a telephone / AQCLn / LZnZ / E / YIAI 103 cellular, portable technology, etc. The output could also be used for one or more control operations such as sensor activation and deactivation, remote monitoring, measurement start / stop, external thermal device operation, data logging, temperature control, power flow control, system failure control, preventive maintenance control, diagnostics, system performance, data entry, data visualization, analytics, etc. In this non-limiting example, where applicable (for example, using the CHFT+ nodes), each external thermal device is controlled using a respective relay (i.e., a switch), and the relay is operated by a relay signal from the DAQ which in turn provides the relay signal based on the input of the control circuitry. A flowchart showing example procedures for a differential basis data processing method performed by the control circuitry for the purpose of determining one or more internal parameters of an object (i.e., internal parameters) using two parallel NITI sensors (one is referred to as the first and the other as the second to distinguish them). The surface temperature measured at one or more specified times of the temperature sensor (i.e. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 104 i.e., the measured sensor temperature) at each of the first and second NITI sensors and the surface heat flux measured at one or more of the specified heat flux sensor times at each of the first and second NITI sensors are input to the array. of control circuits. The initial values ​​for one or more of the internal parameters (e.g., R, k, p, C, y / kpC, etc.) at one or more of the specified times and the values ​​for the thermal contact resistance at each sensor node (Rci and / or RC2) are also input to the control circuitry. The control circuitry uses a differential basis data processing method that determines, for example, based on equation

[20] , one or more of the internal parameters at one or more of the specified times. Finally, the control circuitry generates information (e.g., for output) that corresponds to one or more precise values ​​indicating internal parameters for the object such as R, k, p, C, etc. A flowchart showing example procedures for a differential basis data processing method performed by the control circuitry for the purpose of determining the ready-state thermal resistance of an object (a parameter) is shown in Figure 18B. internal) that uses two NITI sensors (one is referred to as the first and the other as the second for 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 105 distinguish them) in ready-state conditions. The temperature measured at one or more specified times of the temperature sensor (i.e., the measured sensor temperature) at each of the first and second NITI sensors and the heat flux measured at one or more of the specified times of the heat flow sensor each of the first and second NITI sensors are input to the control circuitry. Values ​​for the thermal contact resistance at each sensor node (Rd and / or RC2) are also input to the control circuitry. The control circuitry then uses a differential basis data processing method that determines, for example, based on equation

[22] , the ready-state thermal resistance of the object (an internal parameter) in one or more of the specified times. Finally, the control circuitry generates information (e.g., for output) that corresponds to the precise values ​​indicating the ready-state thermal resistance of the object. Additionally, if desired, the control circuitry could generate information (e.g., for output) that corresponds to one or more precise values ​​indicating one or more of the other internal parameters for the object such as k, p , C,jkpC.. , etc., depending on the determined ready-state thermal resistance of the object and one or more determined internal parameters (e.g., default, estimated, etc.). 7«QC Ln / Lznz / Ε / ΥΙΛΙ 106 A flow chart showing example procedures for an arithmetic quotient basis data processing method performed by the control circuitry for the purpose of determining an internal temperature distribution of the internal region is shown in Figure 1 9A. of an object (i.e. internal temperature distribution) using two parallel NITI sensors (one is referred to as the first and the other as the second to distinguish them). The temperature measured at one or more specified times of the temperature sensor (i.e., the measured sensor temperature) at each of the first and second NITI sensors and the heat flux measured at one or more of the specified times of the heat flow sensor each of the first and second NITI sensors are input to the control circuitry. The values ​​for one or more internal parameters (e.g., R, k, p, C, piii\, etc.) at one or more of the specified times and the values ​​for the thermal contact resistance at each sensor node (Rci and Rc2) and are also input to the control circuitry. The control circuitry then uses an arithmetic quotient basis data processing method that determines, for example, based on equation

[30] , the internal temperature distribution of the internal region of the object in one or more of the specified times. Finally, the set of control circuits generates the information (for example 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 107 example, for the output) that corresponds to one or more precise values ​​that indicate the internal temperature distribution of the internal region of the object. A flow chart showing example procedures for an arithmetic quotient basis data processing method performed by the control circuitry for the purpose of determining an internal temperature distribution of the internal region of an object (i.e., the internal temperature distribution) using two parallel NITI sensors (one is referred to as the first and the other as the second to distinguish them) under ready-state conditions. The temperature measured at one or more specified times of the temperature sensor (i.e., the measured sensor temperature) at each of the first and second NITI sensors and the heat flux measured at one or more of the specified times of the heat flow sensor each of the first and second NITI sensors are input to the control circuitry. Values ​​for the thermal contact resistance at each sensor node (Reí and Rc2) are also input to the control circuitry. The control circuitry then uses an arithmetic quotient basis data processing method that determines, for example, based on equation

[32] , the internal temperature distribution of the internal region of the object in one or more of the times 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 108 specified. Finally, the control circuitry generates information (e.g., for output) that corresponds to one or more precise values ​​indicating the internal temperature distribution of the internal region of the object. A flow chart outlining the example procedures performed by the control circuitry in an example non-limiting NITI system that includes an NITI sensor based on the NITI parallel sensor nodes (i.e., is shown in Figure 20 the DUO NITI system) and a differential basis data processing method for determining one or more internal parameters of an object at one or more specified times. A first measured temperature signal is received by the temperature sensor control circuitry at a first non-invasive heat flow sensor-temperature sensor pair at one or more specified times (step S7). A first measured heat flux signal is received by the heat flux sensor control circuitry at the first non-invasive heat flux sensor-temperature sensor pair at one or more of the specified times to determine a measurement of the heat transfer leaving or entering the object on the surface at one or more of the specified times (step S8). A second measured temperature signal is received by the temperature sensor control circuitry. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 109 in the second non-invasive thermal flow sensor-temperature sensor pair at one or more of the specified times (step S9). A second measured heat flux signal is received by the heat flux sensor control circuitry at the second non-invasive heat flux sensor-measured temperature sensor pair at one or more of the specified times to determine a heat flux measurement. the transfer of heat leaving or entering the object on the surface at one or more of the specified times (step S10). The control circuitry determines the initial values ​​for each of the internal parameters at one or more of the specified times (Sil stage). The control circuitry then determines one or more of the internal parameters of the object at one or more of the specified times based on the measured temperature signals from the temperature sensors in the first and second non-invasive flow sensor pairs. thermal temperature sensor at one or more of the specified times, the measured heat flux signals in the first and second non-invasive pairs of thermal flux sensor temperature sensor at one or more of the specified times, and the initial values ​​of the internal parameters at one or more of the specified times (step S12). The control circuitry generates information (e.g., for output) indicating one or more of the internal parameters of the object at one or more of the specified times. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 110 (step S13). In subsequent procedures performed by the control circuitry (i.e., at one or more future specified times), the control circuitry could determine the initial values ​​for one or more of the internal parameters in the Sil stage based on the values ​​of one or more of the internal parameters determined in the previous step S12 (i.e., at one or more of the specified times). Additionally, the control circuitry could perform steps S7-S11 in any order and is not limited to the order specified in this non-limiting example of procedures. Under ready state conditions, the control circuitry could not optionally perform step Sil and / or could not use initial values ​​of the internal parameters in step S12. Furthermore, the control circuitry could also perform steps to determine and take into account one or more effects associated with a thermal contact resistance between the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair. and the surface of the object and / or one or more effects associated with a thermal contact resistance between the temperature sensor in the second non-invasive thermal flow sensor-temperature sensor pair and the surface of the object. A flowchart outlining the example procedures performed by the 111 control circuitry in a non-limiting and exemplary NITI system that includes an NITI sensor based on the NITI parallel sensor nodes (i.e., the NITI DUO system) and an arithmetic quotient base data processing method for determining an internal temperature distribution of the internal region of the object at one or more specified times. A first measured temperature signal is received by the temperature sensor control circuitry at a first non-invasive heat flow sensor-temperature sensor pair at one or more specified times (step S14). A first measured heat flux signal is received by the heat flux sensor control circuitry at the first non-invasive heat flux sensor-temperature sensor pair at one or more of the specified times to determine a measurement of the heat transfer leaving or entering the object on the surface at one or more of the specified times (step S15). A second measured temperature signal is received by the temperature sensor control circuitry at the second non-invasive heat flow sensor-temperature sensor pair at one or more of the specified times (step S16). A second measured heat flux signal is received by the heat flux sensor control circuitry at the second non-invasive heat flux sensor-measured temperature sensor pair at one or more of the 112 specified times to determine a measurement of the heat transfer leaving or entering the object on the surface at one or more of the specified times (step S17). The control circuitry determines the values ​​for each of the internal parameters at one or more of the specified times (step S18). The control circuitry then determines the internal temperature distribution of the internal region of the object at one or more of the specified times based on the measured temperature signals from the temperature sensors in the first and second non-invasive sensor pairs. of heat flow sensor-temperature sensor at one or more of the specified times, the measured heat flow signals in the first and second non-invasive pairs of heat flow sensor-temperature sensor at one or more of the specified times, and the values ​​of the internal parameters at one or more of the specified times (step S19). The control circuitry generates information (e.g., for output) indicating the internal temperature distribution of the internal region of the object at one or more of the specified times (step S20). Additionally, the control circuitry could perform steps S14-S18 in any order and is not limited to the order specified in this non-limiting example of procedures. Under ready state conditions, the control circuitry could not optionally perform 113 step S18 and / or could not use the internal parameter values ​​in step S19. Additionally, the control circuitry could also perform steps to determine and take into account one or more effects associated with a thermal contact resistance between the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair. and the surface of the object and / or one or more effects associated with a thermal contact resistance between the temperature sensor in the second non-invasive thermal flow sensor-temperature sensor pair and the surface of the object. Additional exemplary procedures performed by the control circuitry in an exemplary, non-limiting NITI system that includes an NITI sensor based on the NITI parallel sensor nodes could include more than one data processing method. For example, a NITI system could include both a differential basis data processing method and an arithmetic quotient basis data processing method to determine (e.g., calculation) one or more internal parameters of an object and determine (e.g., calculation) an internal temperature distribution of the internal region of the object, respectively. The NITI system could perform, for example, multiple data processing methods, subsequently or simultaneously. In other example embodiments, a 114 data processing method could be based on a combination of multiple data processing methods to determine one or more internal properties. Example DUO NITI embodiments could use control circuitry to maintain prescribed heat flow and temperature conditions. For example, the control circuitry may be used to maintain ready state conditions by adjusting the power supplied to an external thermal device (e.g., a heater). In other exemplary embodiments, the control circuitry may regulate the amount of heat flux and / or temperature occurring at one sensor node to be a multiple constant of the heat flux and / or temperature occurring at another node. sensor. Furthermore, similar conditions could be achieved without the control circuitry. For example, a prescribed amount of thermal insulation in each sensor node could also be used to regulate the thermal flux or temperature occurring at each sensor node, for example, with a constant multiple of another sensor node. The creation of these environments where the thermal flux and / or temperature presented at sensor nodes are related, for example, by a multiple constant (Y) that allows the further simplification of NITI DUO systems and data processing methods. 115 For example, if control circuitry and / or thermal insulation is used to maintain the following relationship between the thermal flux occurring at each sensor node: T X fls'eníori.m—Qs'cnsorZ.m |3j] Equation

[27] can be rewritten as: (.Τ>ηι···')Τ1,ι;π - Qjtíbyí-;.i|iX^Cl) _ (^ΛΊ.τν·:ηΓ ·.,Ü T Σ; 1 ,fX—t, ,) ] (TieniorZj?!—ΐνπΜΓ.,πι * 7?^) - T;nffm <a q x 9ονη$·:ικ :.i] + xj="ixl.í" * vklí—f-ι)) lo cual se simplifica a: ,m íse nsot 1,7?;xcts'en.sorí.tn y tfsensqrl.m ^c2 ) .. ‘ intel nal.m — (y _ j)' ' suponiendo una resistencia de contacto térmico imperceptible o equivalente (re) en cada nodo sensor: ϊ sensüj i.nj " ^sensar¿.m.,,, untmiuíjh—^y iji doj en este ejemplo, la ecuación

[35] y

[36] pueden utilizarse para medición simplificada temperatura interna tiempo real (tintemai, m) un objeto dado sin ninguna consideración los efectos transitorios transferencia calor (por por medio función respuesta (ψ) con respecto al parámetros internos del objeto. aplicaciones de ejemplo a continuación, las modalidades ejemplo son descritas diferentes aplicaciones métodos 116 niti. algunos estos ejemplos tienen resultados datos experimentales incluidos que están basados pruebas realizadas el inventor. esto no significa sea lista exhaustiva métodos, sino su lugar, ilustran modos niti gue utilizarse. además, limitados a enlistan más adelante podrían base otros ejemplo. los sensor incluyen uno sensores flujo tecnología termopila diferencial termopar pared delgada. sin embargo, obtenerse similares considerar tipo utilizados rtd, fibra óptica, ntc, termistores, termopilas, etc.). aplicación medición perfusión sangre una aplicación es perfusión sangre (flujo) tejido como muestra modalidad representa figura 22. un (chft+) tejido. el (es decir, objeto) 117 incluye múltiples (w) , conductividad térmica (k) densidad {p), capacidad (c). medida incrementa profundidad (x), distribución (t) aproxima sanguínea central (tcore) . esta (tcore} supone igual equilibrio con) mayoría vivo está compuesta sangre. modelo matemático bio-calor señalado siguiente tabla 2. tabla modelo condición límite (basada bio-calor pennes) pde dt d2t condiciones de ϋ'γ -k—="," x t - co condición inicial τ="TmíM" λ t="0" la solución 118 (la (t)) cuando evalúa superficie (x="0)," es: πϊ __ tfíssue.m ~ j ,j~ i -*71 = 1 donde superficial : 1mci tíssue.ü—core qswisoro ** 7aqc ίπ ίζηζ ε υιλι definido positivo entra reescribiendo

[37] términos salidas entre superficies produce: τ'="Tscnvar.ü" "xx eff ( j w(í„, í,_ j) [ 39j sn dond- e h jcw estado preparado (r) limitante, constante cambia. casos (tcore), distinguirse relacionados cambios debido diferencias 119 originan cambios. por algunos casos, realizarse, cambio resultado, expresión lineal

[39] encontrada combinación

[38]

[39] . las permiten distinción diferenciación causas subyacentes internos). modelos matemáticos derivarse tomar cuenta varía opuesto suponer (teore) f coitio θπ limitante. modalidad mediciones periódicas que utilizan la estimación parámetro para chft+ chft-) utilizada método periódico procesamiento datos, podría esquema estimación parámetro determinar 120 interno tejido) similar caso general presentado sistema pares térmico-temperatura sección anterior aunque diferente valores predeterminados constantes (p) (c) objetiva será minimizada i i” rmse="i" (^sensor,,» —moj mm="1donde:" tí úteutíltt'd.fn ^tissue,th í.s'en.vrir.m' donde: ,v -1 ¿efigor n 7 rjs.s'uv.ri 142 jc.v (con calentador) fue probada simulador capaz crear entorno controlado agua pseudo este llamado fantasma fantasma. velocidades (las aqcln lznz yiai 121 perfusión), colocado mediciones fueron sigue: fueron registrados 10 segundos preparado. se encendió calentador aproximadamente 65 segundos, originando transitoria medido señales superficial. totalidad procesada incluyó menos segundo, (rc'j 3. periódica perfusión --—) temperatura tcore ° c) veloc. flujo (ce min) chft fantasma diferencia „ m2 0.0237 0.0185 21.94% 32.83 32.92 0.000206 15 0.0360 0.0347 3.61% 32.12 31.93 0.000205 20 0.0533 0.0524 1.69% 33.03 33.23 0.000254 25 0.0810 0.0709 12.47% 30.24 30.48 0.000218 observando 3, estimados utilizando 122 conformidad cercana cfd fantasma) (cc sometidos diferencia 12.47%, manera respectiva. ser inventor estaba realizando recolección experimentales, difícil mantener min). cuando ajustaron estas flujo, velocidad menudo saltó alto lo esperado originó altas compara contra observa unidad dezmiíí!' denotada —- proporcionada milímetros segundo) través volumen milímetro tejido). programadas fantasma, especificada lugar agua. algunas además reducirse s-1. otras combinarse valor proporcionar masa dada 100 gramos). 123 incrementan flujo. relativamente consistencia todas esperado. estimada coincide (twater) registrada cordón sumergido dentro grande alrededor 0.24 °c presentan con propósito demostrar óptimo (w) utiliza relación

[40] rmse) presentada 23. gráfica 23 ilustra tiene mínimo global s-1 corresponde estimado min), documentado 24 coincidencia curva (salida) calculada (entrada) medida. 124 curvas indica (k, p, c, w) utilizado construir [41 ] mismos actuales objeto). valores incorrectos originarían deficiente, ilustrado 25. como menciona anterioridad, (k), (p), entrados realizado inercia (jkpt) otro modo es, esquemas parte datos. estimar definir funciones objetivas períodos superficiales tomadas. posible sensibilidad 7«qc ln lznz 125 y, manera, ejemplo,(xt7oy consecuencia, estimarse, individual. 26 internos. específica, existe producto durante periodo tiempo, mientras (tv) inicialmente mínima tiempo. incluir parámetro, definirse designadas kpc incluyan iniciales definidas w periodos últimos adicional, operar mismo secuencias prescritas después otra). (cj calcularlas haya sido determinado 126 utilicen vez utilizando, cantidad puede calcularse

[43] \ jseii.w.'n— —líiskmn ,0 4λ>ιμι>λ: where blood perfusion (w) on the right is the optimal value of blood perfusion (w) determined when using predetermined (i.e., previous) values ​​of tissue thermal conductivity (k), tissue density (p ), and the thermal capacity of the fabric (C). The method based, for example, on equation

[43] can be used in a variety of methods to determine, for example, the product of the thermal conductivity of the fabric (k), the density of the fabric (p), and the thermal capacity of the tissue (Cj. For example, measurements can be taken at single indices or multiple indices (m). In the case of multiple indices, the average of the resulting values ​​could be taken, for example, as the determined value. If desired, the most recent value determined for kpC could update the value 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 127 previously determined and could be used to re-estimate or calculate the value of blood perfusion (w). The more this routine is practiced, the more accurate the determined values ​​of tissue thermal inertia (^,'Λ / jC) and blood perfusion (w) could be converted. This non-limiting NITI example method could be used for some or all of the NITI example modalities and / or applications. BLOOD PERFUSION MODALITY – REAL-TIME MEASUREMENTS USING PARAMETER ESTIMATION In the exemplary embodiment of periodic blood perfusion measurements using parameter estimation, data processing by the control circuitry begins once all measurements are taken. Thus, in the previous experimental phantom test, measurements were output about every 75 seconds in a periodic mode. NITI sensor data (e.g., CHFT+ or CHFT-) could alternatively be processed in real time to provide real-time outputs of blood perfusion (w), core blood temperature (Tcore), and / or or the thermal contact resistance (Re) between the NITI sensor and tissue surfaces. As time passes, more data points were added to the surface heat flux and surface temperature curves and processed in real time by a data processing method that includes an estimation scheme. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 128 parameter and outputs values ​​in less than 1 second. BLOOD PERFUSION MODE - MEASUREMENTS WITHOUT PARAMETER ESTIMATION Equation

[39] can be rearranged as: 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ í I Tr¿xsue ,m (Th'e'n.s'ur.n ) jkPcwς;ϊ Λ™-., * where: Ñíjviíc.m—¡Senso—^sensor.™

[44] [Four. Five] Combining equation

[44] and equation

[45] : . I Cfsensor.m tfsenw.m X ) (Tseiisor.tí ^¡Sensor,í) [461 When the thermal contact resistance (Re) between the NITI sensor (e.g., CHFT+ or CHFT-) and the fabric surfaces is known and typical values ​​for fabric thermal conductivity (k), fabric density ( p), and tissue thermal capacity (C), equation

[46] could be used for real-time blood perfusion measurement when a typical blood perfusion value (w) is entered on the right side. In some exemplary embodiments, for example when the change in blood perfusion (w) is of interest, the quantity Tsensor,o - q sensor, or X Re could be assumed at one or more specified times. In other exemplary embodiments, the quantity Tsensor, or -q'sensor, or X Rc could be determined, for example, using an additional temperature sensor; the output of which is indicative of 129 the temperature of the surface of the tissue and / or central (i.e., internal) tissue. Although the calculated value of blood perfusion (w) on the left side will not be exact, it will still suffice for exact quantitative and / or qualitative measurements. Also, for most accurate results, the typical value for blood perfusion (w) on the right hand side could be updated to reflect the most recent and / or accurate value calculated using equation

[46] . In other methods, the values ​​for blood perfusion (w) on the right and left sides could be determined at the same time, providing precise or exact quantitative measurements. This could obviate the need to enter a typical blood perfusion (w) value on the right side. If the value of the thermal contact resistance (Re) is unknown, it can be determined (for example, by 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ of the NITI procedures described above) or may otherwise be determined or taken into account. In some cases, the thermal contact resistance (Re) could be estimated to be imperceptible. Furthermore, under ready state conditions Equation

[46] reduces to: (( ^sensor (J Sensor,» ^sensor,0 -------------------------------------------------- ---------------:---------------------------------- --:-|47] Equation

[47] no longer requires a typical value 130 blood perfusion (w) on the right side. Ready state conditions could be achieved in a variety of ways including control circuitry that regulates heat flux and / or temperature presented to the tissue surface by means of external thermal devices (e.g., heaters, coolers, etc.). BLOOD PERFUSION MODE - NITI DUO SENSOR For an example DUO NITI sensor modality when using the first and second parallel NITI sensor nodes (each node has a heat flux-temperature sensor pair), two independent equations are formed: FF τρ 1.FF / । i η X *Ui = 7 / ·^« + , ,> Fr / í - Í-!))

[49] oroprocessing of / «QCLn / LZnZ / E / YIAI Using an example differential basis data method, equations

[48] -

[49] produce: / (tvMM l.íí r / ι ( híü'.U.'f' - r,i X ) 1 ( l.'i - i 1,-1 |, / X (y !*((* ~ j- 1 j) ~ Σ,-Ι i X *;f7 (y ^'(Ιλ - *)-!.))) / [501 This transient equation is the result of the DUO NITI sensor configuration and allows real-time measurement of blood perfusion (w) without considering core blood temperature (Tcore), when entered 131 Typical values ​​for tissue thermal conductivity (k), tissue density (p), specific tissue heat capacity (C), and blood perfusion (w) on the right. Although the calculated value of blood perfusion (w) on the left side will not be exact, it will still be very close and sufficient for accurate quantitative and / or qualitative measurements. Additionally, for most accurate results, the typical value for blood perfusion (w) could be updated to reflect the most recent and / or accurate value calculated using the equation

[50] . In other methods, values ​​for blood perfusion (w) on the right and left sides could be determined at the same time, providing exact or precise quantitative measurements. This could obviate the need to enter a typical blood perfusion (w) value on the right side. Estimated values ​​for thermal contact resistances (Reí and Rc2”) between each NITI sensor (e.g., CHFT+ or CHFT-) and tissue surfaces can be determined (e.g., by NITI procedures described above). or they can be determined in another way. In some cases, the thermal contact resistance (Raí and / or Res) could be estimated to be imperceptible. Under ready-state conditions, equation

[50] reduces to: w = kpc Q.Sen.swl.m ) (TÍensorZ.m 4.St'nir>r2,TTt r 1, dsensor¿ ,m 132 where a typical blood perfusion value (w) is no longer required on the right side. The ready state conditions could be achieved in a variety of ways that include the set of control circuits that regulate the thermal flow and / or temperature presented on the fabric surface by means of external thermal devices (heaters, coolers, etc.). .). A graph is shown in Figure 27 showing the results of an example DUO CHFT+ modality when used to measure the perfusion (w) of the pseudo tissue in the phantom at different flow rates of 30, 20 and 10 (cc / min). This graph shows that the example DUO CHFT+ modality is capable of determining the perfusion (w) of the pseudo tissue in the phantom when it is initially turned on at 30 (cc / min) (perfusion rate (iv) of -0.035. Subsequently, after about 10 minutes, the DUO CHFT+ example modality determines the change in perfusion (w) in real time as the phantom rate is set to 10 (cc / min) (perfusion rate ( w) of -0.020 ''"i·- and is then increased by 20 (cc / min) (perfusion rate (w) of -0.027 , where the experimental measurements end after about 10 minutes. To show the accuracy and compliance of the real-time DUO CHFT+ example method, a different NITI example method is also used for perfusion measurement / AQCLn / LZnZ / E / YIAI 133 (CHFT+ Periodic) to determine the perfusion rate at each specified flow rate. The agreement between the two measurements indicates the validity of both methods to determine the perfusion rate (w) of the tissue. TISSUE HYDRATION MEASUREMENT APP All of the example methods and modalities for measuring blood perfusion can be used to determine = t, which is the prepared state kpcw i¡ w thermal resistance (R) of the tissue as defined in these example methods. The ready-state thermal resistance (R) of the tissue could be an accurate and reliable indicator of tissue hydration. For example, correlations could be developed and used as a means to calibrate tissue hydration and dehydration levels based on, for example, the ready-state thermal resistance of the tissue. Independent values ​​indicative of blood perfusion (w), or other internal parameters, could also be used to calibrate tissue hydration and dehydration levels. CORE TISSUE TEMPERATURE MEASUREMENT APP Combining equation

[37] and equation

[38] : ____ rrt ____ Γα \ ’ 1 [ΰ í I~\ ^Tiasue.in—' ':n,> + Qsrríiar.Ü T. ~ + TdTP Et~f [ . — ty-i) If52] k V W l—i K \ W1) / =1 Rewriting equation

[52] in terms of the NITI sensor outputs and including the effects of the 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 134 Thermal contact resistance (Re) between NITI sensor and tissue surfaces: m _ _________ .. 1 the v 1 ® / ¡ Λ Tstmsorjn—?5t?rtsor,m—^Core i Qsmsor.0 T l~ + / ^Qsenxar.j t l~ ^(Im—6~1) ) / -1 Rearranging and realizing that the Tcore is independent of the values ​​that change with respect to time (the measurement index (m)): _ m _ .. 1 [a yy 1 fet / f x Tcürt'.yii ~—^Sen.vor.mx — xT | / ^fl.íen.wr, / xT j & / [ |—-1) 1 K XIV 2—í K \W / Equation

[54] is an example equation for measuring tissue core temperature (TTissue,m) and is used in the following example embodiments. For some of these example embodiments, values ​​of fabric thermal conductivity (k), fabric density (p), specific fabric thermal capacity (Cj), thermal contact resistance (Re) between the surfaces need to be determined. of the NITI and tissue sensor, and / or blood perfusion (w). This can be done, for example, by determining these values ​​(for example, by means of the CHFT+ or CHFT- methods described above) or, for example , when using default values ​​(for example, values ​​from a textbook). CORE TISSUE TEMPERATURE MODALITY - CHFT+ (ACTIVE THERMOMETRY) A CHFT+ mode uses a thermal device 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 135 external integrated such as a heater to create a thermal event (ie, heat transfer) that can be used to perform NITI. For tissue core temperature measurement (Icore,m), the heater could operate in any mode (ready, periodic, cycling, etc.) and in this example, equation

[54] would output the core temperature of tissue (Tcore,m) accurately and in real time when values ​​for blood perfusion (w), tissue thermal conductivity (k), tissue density ( / ?), tissue heat capacity (C ), and the estimated thermal contact resistance (Re) are entered on the right side. These values ​​could be determined, for example, using a data processing method (eg, including a parameter estimation scheme) or otherwise determined and taken into account. In some cases, the thermal contact resistance (Re) could be estimated to be imperceptible. Although not required, it may be beneficial to cover the CHFT+ with insulating material to prevent missignals from external stimuli such as running, touching, etc. A graph showing the results of an example CHFT+ modality (with integrated heater) is shown in Figure 28 when used to measure the core temperature (Tcore,m) of the pseudo-tissue in the phantom at the flow rate of 2 ( cc / min) . In this graph / AQCLn / LZnZ / E / YIAI is 136 shows that the exemplary modality CHFT+ is capable of determining the core temperature (Tcore,m) of the pseudo tissue in the phantom (ie, measured (internal)) without considering surface temperature conditions. Specifically, the surface temperature is initially increased as a result of the integrated heater being turned on. Subsequently, after a period of time, the surface temperature decreases as a result of an external fan (i.e., thermal disturbance) (which is blown in the CHFT+ example mode. Without considering these sudden and unexpected changes in thermal conditions For environmental conditions, the example CHFT+ modality measures the core temperature (Tcore,m) of the pseudo-tissue in close compliance with an internal probe placed within the phantom and below the pseudo-tissue. CENTRAL TISSUE TEMPERATURE MODALITY - CHFT-(PASSIVE THERMOMETRY) A CHFT-modality uses external thermal events such as the dissipation of heat from the body of a mammal to perform NITI. When subjected to an external thermal event, equation

[54] , for example, would output the tissue core temperature (Tcore.m) accurately and in real time when the values ​​for blood perfusion (w), the thermal conductivity of the fabric (k), the density of the fabric (p), the thermal capacity of the fabric (Cj, and the 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 137 estimated thermal contact resistance (Re) are entered on the right side. These values ​​could be determined, for example, using a data processing method (eg, including a parameter estimation scheme) or otherwise determined and taken into account. In some cases, the thermal contact resistance (Rcj) might be estimated to be negligible. Although not required, it might be beneficial to cover the CHFT- with insulating material to prevent missignals from external stimuli such as running, contact, etc. A graph showing the results of an example CHFT- modality when used to measure the core temperature (Tcore,m) of the pseudo tissue in the phantom at the flow rate of 2 (cc / min) is shown in Figure 29. . This graph shows that the exemplary modality CHFT is capable of determining the core temperature (Tcore,m) of the pseudo tissue in the phantom (ie, measured (internal)) without considering surface temperature conditions. Specifically, although the surface temperature is initially stable, an external fan (i.e., the thermal disturbance) is cycled (i.e., it is turned on and off) to blow air in the CHFT-example mode and the pseudo tissue . Without considering these sudden and unexpected changes in ambient thermal conditions, the CHFT- example modality measures the temperature 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 138 central (Tcore, m) of the pseudotissue with close compliance to an internal probe placed within the phantom and beneath the pseudotissue. CENTRAL TISSUE TEMPERATURE MODE - CHFT+ (PERIODIC MEASUREMENT) In addition to the example real-time methods and modalities for tissue core temperature measurement above, a NITI sensor (e.g., CHFT+ or CHFT-) can be used to take periodic tissue core temperature (Tcore) measurements when Operate in different ready state conditions. For example, ready-state measurements before a thermal event (Tsensor, or q'sensor, o) can be compared to ready-state measurements during, after, or at the end of a thermal event (Tsensor,end, q sensor ,end) for the purpose of determining the tissue core temperature (Tcore) using: T_ Tsensor.oxQsensor.FNCi—^Sensor,EWOxQsensor.Or„, Vserasoi’.fcWí? ^Sensor.O Both of the exemplary embodiments CHFT+ and / or CHFT may be subjected to different ready state conditions with respect to time. However, CHFT+ modalities are preferred due to the increased operational control of one or more of the external thermal devices that could be used to create different ready state conditions. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 139 CENTER TEMPERATURE MODE - CHFT+ (ZERO THERMAL FLOW THERMOMETRY) Using the control circuitry, an example CHFT+ modality could be used to create a zero heat flow environment where no heat transfer occurs between the tissue surfaces and the sensor, that is, where no heat enters or leaves the sensor. tissue that is measured by the thermal flow sensor (the minimum voltage output, i.e. zero). Under ready-state conditions, a zero heat flux environment simplifies equation

[54] into: —^Sensor,m 1^6] where the measured sensor temperature (Tsensor,™) is equivalent to the core temperature of the tissue (Tcore,m) . An advantage of this method is the independence of tissue core temperature measurement (Tcore,m) from internal parameter values ​​(e.g. blood perfusion (w), tissue thermal inertia, (JUpC) etc. .) and the thermal contact resistance (Re) once a ready-state zero thermal flow environment is obtained. The amount of time required to achieve these ready-state conditions, which is determined by the measured sensor temperature output (Ts ensor, m), varies depending on the example modality used and is a common limitation of existing monitoring technologies. zero thermal flux that does not / AQCLn / LZnZ / E / YIAI 140 use NITI technology. Until a ready-state zero heat flux environment is obtained, the NITI zero heat flux thermometry example embodiments could use other example embodiments, such as an active thermometry example embodiment for measuring core temperature. tissue to take exact or precise measurements of tissue core temperature (Tcore,m). A graph showing the results of an example zero heat flux (ZFIF) CHFT+ modality when used to measure the core temperature (T Tcore,!^) of the pseudo tissue in the phantom is shown in Figure 30. flow rate of 2 (cc / min). This graph shows that the CHFT+ ZFIF example modality is capable of determining the core temperature (Tcore,m) of the pseudo tissue in the phantom without considering the surface temperature conditions and without delay. Specifically, although the surface temperature takes approximately 8 minutes to achieve an output indicative of the core temperature (Tcare,™) of the pseudo tissue, the example modality CHFT+ ZFIF measures the core temperature (Tcore,m) of the pseudo tissue from the beginning with close compliance when compared to an internal probe placed inside the phantom and under the tissue. CENTRAL TEMPERATURE MODE - DUO NITI (DUAL THERMOMETRY) For an example DUO NITI mode when using the first and second NITI parallel sensor nodes 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 141 (each node has a pair of thermal-temperature flow sensors), two independent equations are formed: x «cj) - + y X t'rf ( I

[57] A. NIV ί \\ / j \ r i / __ / vi\ (T.M.m.rzm " 4%..,«,r / .^ * «<L:) " = 7 M íónArn-zj! + Y .X Frf ( " j-d)

[58] Using an arithmetic quotient basis data processing method, equation

[57] / equation

[58] produce: (' / scnsorl.m ^ci) Corejn _ (^ΐΐη.ΐοπ,α + Σρι tp j)) C^i'ííMsorZ.m—^Γοΐΐ,ίη (úi'ensoipü 5 Σρι ^Sensurlj & I (y' ^( / m—tp j)) Reordering: _ , x Κ) * (í„„;. + 17 ¿i 1, X frfÚ'Ó,,, - ~1) - , * p) -t,jj This transitory equation is the result of the 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ DUO NITI configuration and allows real-time measurement of tissue core temperature (Tcore,m) when entering typical values ​​for tissue thermal conductivity (k), tissue density (p) , tissue-specific thermal capacity (C), and blood perfusion (w) on the right side. Estimated values ​​for thermal contact resistances {Rcy Re} between each NITI sensor node (e.g., CHFT+ or CHFT-) and tissue surfaces can be determined (e.g., by NITI procedures described above). or determined and taken into account 142 account otherwise. In some cases, the thermal contact resistances (Reí and / or RC2'j could be estimated to be imperceptible. Under ready-state conditions, and where Rc= Reí = Rc2no Reí' and Reo are estimates that are imperceptible, equation

[60] reduces to: _ _ ' / senjorí.m 75t'nsorl,rn—^5'rnsori.m ·7.$·£7ιλκ·2,μ .. 1Cose.ni — = ’ 0’1 I Qi'ensorl.m—^Sensor¿.m where typical values ​​for tissue thermal conductivity (k), tissue density (p), specific tissue thermal capacity (C), and blood perfusion (w ) are no longer required on the right side. Ready state conditions could be achieved in a variety of ways including control circuitry that regulates heat flux and / or temperature presented to the tissue surface by means of external thermal devices (e.g., heaters, coolers, etc.). PIPE PARAMETER DETERMINATION APP Another application of NITI technology to determine one or more internal parameters related to the fluid flowing in a pipe or other conduit is shown in Figure 31. In this example, a heater is used (the CHFT+ example mode), although in other examples, the heater (i.e., the external thermal device) is 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 143 optional. An example thermal mathematical solution for a pipe or other conduit (for example, a copper pipe), with internal flow when subjected to surface thermal flow is: I Plpe^n—Τψί,υ ~F y ,( )(1c) |62] where the initial surface temperature of the pipe is: + 1631 where the heat flux is defined to be positive when it enters the pipe / duct and where τ = is the thermal time constant (i.e., the time constant) of the pipe / duct, p is the density of the pipe / duct, C is the specific heat capacity of the pipe / duct, δ is the wall thickness of the pipe / duct, h is the internal convective heat transfer coefficient (i.e., convection coefficient) of the pipe / duct and related to the internal flow velocity (i.e., flow rate) of the pipe / duct, Tpipe is the pipe / duct surface temperature, and Tpiuíd is the fluid core (i.e., internal) temperature. . Rewriting equation

[62] in terms of the NITI sensor outputs and including the effects of the 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 144 thermal contact resistance (Rc) between the NITI sensor and the pipe / duct surfaces produces: 'Γ τ „ nr.· I V Λ'σηίΟΓ J-ÍWor.j-l·. -I T k rz.n Tpépe.m—kíé.níür{j fcen»,r.Ox^í? + y ( . )0e' ) [64J í—i n / -i where is the ready-state thermal resistance (R) of the convective internal flow velocity. Equation

[62] and equation

[64] are valid for pipes or conduits made of materials with high thermal conductivity. For other materials, such as PVC, a different thermal model and corresponding solution may need to be developed. Other models and thermal solutions could also be developed for materials with high thermal conductivity. In this example, the greater the flow velocity (ú), the greater the convective heat transfer coefficient (h). Typically, the relationship between ύ and h is not linear at least at low flow rates (e.g., laminar), and therefore a correlation function between the two variables is desirable. This correlation function can be found, for example, through experimental testing. An example of a correlation experimentally found when a CHFT+ was operated on a 0.01905 m (^) L-type copper pipe with a 0.00127 m (0.05) wall thickness is: 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 145 hours = 1035.2 IV m2- °C pO.2137 [MJ / AQCLn / LZnZ / E / YIAI Reordering: = 1 1(Γ14 i / 2 gal (m — C \ h4* 47 5 |66| min IV / Thus, a general example of a correlation between the convection coefficient (h) and the flow velocity (ύ) could be: h=Z IV / nün\ nr - °C \gal /

[67] where Z and P are the correlation values. Other forms of correlations could be developed depending on the mathematical techniques used (e.g., logarithmic functions, exponentials, etc.). A graph showing how the example correlation with experimental measurements could develop is shown in Figure 32. In this example, the correlation is found by plotting the experimental results for measurements taken at different flow rates. Once a sufficient number of measurements are taken at different flow rates, the best fitting curve (e.g., trend line) can be used to find a correlation (i.e., equation) relating the measured convection coefficient (h) with the flow velocity (ó) or vice versa. In other example embodiments, the functions of 146 correlation and / or other methods of relating the convective heat transfer coefficient (h) to the flow velocity (ó), or vice versa, could be determined using machine learning methods (e.g. neural networks, etc.) . PIPE APPLICATION MODE - PERIODIC MEASUREMENTS USING PARAMETER ESTIMATION For an example NITI sensor modality (e.g., CHFT+ or CHFT-) with a periodic data processing method, equation

[64] could be used in a parameter estimation scheme to determine the internal parameter of the convection coefficient (h), the fluid core temperature (Trieid) (i.e., internal), and / or the thermal contact resistance (Rc) between the NITI sensor and pipe / duct surfaces. This is similar to the general case presented as an example, for the NITI example system embodiments with one or more heat flux-temperature sensor pairs from the previous section with a different thermal model for a different NITI application. In this example, constant default values ​​were used for the internal parameters of pipe density (p), pipe thermal capacity (C), and pipe wall thickness (δ). In this example, the default values ​​were obtained from the pipe manufacturer's specification. An example objective function that will be minimized in this example application is: 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 147 RMSE — । _1(Titrrtsor.nt Pi:ulcuiated.in) I jW 1 M where: ^caicuiaied.m PPipe.tu L ^.teTiwr / in X1^9] and where: and v_i 7.Sensor,n ~ / pipe.n1-1I -~. An example CHFT+ modality (with heater) was tested on a 0.01905 m (^) inner diameter L-type copper pipe with a wall thickness of 0.00127 m (0.05) with water flowing through it at different velocities. and flow temperatures. The CHFT+ was coupled to the pipe surface and measurements were taken as follows: - 10 seconds of ready state data were recorded. - The heater was turned on for approximately 65 seconds, causing a transient thermal response of the pipe wall that is measured by the CHFT+ through the surface heat flow and surface temperature signals. - All data were processed through a periodic data processing method that included a parameter estimation scheme in less than 1 second, generating outputs of the convection coefficient (h), the 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 148 core water temperature (Tfimd), and the thermal contact resistance (Re) between the surfaces of the CHFT+ and the pipe. Once the convection coefficient (h) is determined, it is used in a correlation equation (e.g., equation

[66] ) to determine the flow rate which is related to the mass flow rate of the fluid. and speed (e.g. kg / s and m / s). The results are tabulated in the following table 4. Table 4. The results of the pipeline parameter determination (the CHFT+ example mode with periodic parameter estimation) 7«QC Ln / Lznz / E / YIAI Velocity uai (——) flow min h(^) m~ i. T(S) K'< RMSE ( C) γιιγτ Estimated + flow velocity qat (—) min 838 5.22 0.000331 0.126 0.9 829 5.27 0.000327 0.134 0.9 1 825 5.30 0.000334 0.134 0.9 826 5.29 0.000331 0.143 0.9 826 5.29 0.000334 0.137 0.9 826 5.29 0.000329 0.041 0.9 1378 3.17 0.000329 0.041 3.9 1385 3.16 0.000329 0.038 4.0 4 1377 3.17 0.000329 0.043 3.9 1366 3.20 0.0 00328 0.041 3.7 1388 3.15 0.000328 0.037 4.0 1401 3.12 0.000331 0.036 4.2 7 1588 2.75 0.000331 0.023 7.5 1585 2.76 0.000328 0.023 7.4 149 Table 4. (Continued) 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ Flow gal velocity h(^-) nv a. T(S) R< CC^) RMSECC) Estimated CHrl + fiow rate min 1583 2.76 0.000329 0.024 7.4 1594 2.74 0.000328 0.021 7.6 1589 2.75 0.000331 0.022 7.5 1599 2.73 0.00033 0.023 7.8 1687 2.59 0.0003.32 0.020 10.0 1695 2.58 0.000333 0.021 10.2 10 1690 2.59 0.000331 0.021 10.0 1688 2.59 0.000333 0.023 10.0 1683 2.60 0.000331 0.022 9.8 1682 2.60 0.000331 0.025 9.8 1786 2.45 0.000332 0.019 13.0 1796 2.43 0.000331 0.019 13.3 13 1808 2.42 0.000331 0.020 13.7 1794 2.44 0.000329 0.019 13.2 1794 2.44 0.000329 0.020 13.2 1800 2.43 0.00033 0.020 13.5 1869 2.34 0.000329 0.019 16.0 1864 2.35 0.00033 0.020 15.8 16 1863 2.35 0.000331 0.021 15.8 1857 2.35 0.00033 0.020 15.6 1863 2.35 0.000331 0.025 15.8 1857 2.35 0.00033 0.021 15.6 In order to demonstrate the ability of the parameter estimation scheme used in this data processing method to determine the prime value of the convection coefficient (h) when used with experimental data, the relationship between the example objective function in the equation

[68] (i.e., RMSE) and the convection coefficient (h) for the case of 0.6309 It / s (10 gal / m) is displayed in Figure 33. The graph in Figure 33 illustrates that the relationship has a global minimum in the value 150 H·' of the convection coefficient (h) of 1690 ^7 . This corresponds to the estimated case value of 0.6309 It / s (10 gal / m) which is documented in table 4. For the 0.6309 It / s (10 gal / m) case, a graph illustrating an example of a match between a calculated sensor (output) temperature curve and a sensor (input) temperature curve is shown in Figure 34. extent. The coincidence or comparison between the two temperature curves indicates that the internal parameter values ​​(h, p, C, δ) and the thermal contact resistance value (Re) used to construct the sensor (output) temperature curve calculated by means of equation

[69] are the same as the current values ​​presented in the pipe (i.e., the object). As mentioned above, in this example, the default values ​​for pipe density (p), pipe heat capacity (C), and pipe wall thickness (δ) were determined using the manufacturer's specification for the pipe. copper tubing and were entered as constant values ​​in the example data processing method performed for tubing parameter determination. Although determined as part of the data processing method in this example, the value for the estimated thermal contact resistance (Re) can also be entered as a predetermined value in advance and 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 151 similar results can still be achieved. In this exemplary embodiment, whether or not the predetermined value for the thermal contact resistance (Re) is accurate, the flow rate (ύ) output results could be accurate because the effect of any inaccuracies in the predetermined value of the thermal contact resistance (Re) is compensated by the subsequently developed correlation. Another way to define and determine the thermal contact resistance (Re') is by using the full definition of the heat transfer coefficient, U, where: +V e U (ie, the total ready-state thermal resistance of the object) can be determined by a number of methods. An example method is the use of measurements taken under ready-state conditions (for example, before, after, or at the end of a thermal event) where, for example: _ Qsensor.ENü IV711 / íCTSonfA'D- 1Fluid.EW In this way, the thermal contact resistance (Re') can be defined as: «c=--------|73| / AQCLn / LZnZ / E / YIAI and is substituted in place of equation

[70] . With the For the purpose of using equation

[73] , typically, the value of Τρίυΐά,Εκο needs to be determined. Some example methods of determining TFiuid,END (ie, TFiuid,m) are described below. In other example embodiments, TFiuid,m could be assumed or otherwise determined using, for example, surface-mounted temperature sensors that could be isolated. Another example method for determining U is the use of measurements taken under different ready-state conditions (for example, before, at the end, or after the thermal event): 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ , , feiLTOT·.END Qsensor.O . —, . . ti = ~:-----p-q------- l where ^sensor,end and Tsensor,END oe represent the heat flux and surface temperature measurements taken under ready-state conditions at the end of a thermal event. It should be noted that equation

[74] requires different ready state conditions which can be obtained, for example, by taking measurements before and after a thermal event has been generated, for example by means of an external thermal device. Using equation

[74] and equation

[71] : T — TIISi'?isor.EA'D1Sensor_ ¡k —-----—--h ÍSensorJTA'D mSé rt.+rtr. 0 153 A data processing method that includes a parameter estimation scheme and flow velocity correlation (ó) could also be performed without differentiation between convective heat transfer coefficient (h) and thermal contact resistance (Re ). Of course, the data processing method could be based on a thermal solution that is expressed using the total heat transfer coefficient (U) as illustrated, for example, in equation

[76] : m - - ,f_r. — _ — {PSen.wrJ " tfsenxnr.j-1) ,. -( ' '1 / cak'uíafi'd u.m ~ 'sensor,U + / , jy — (?JJ | o] where Tcaieuiated,u, m is the calculated temperature curve (output) found when using the total heat transfer coefficient (U) Also, the example objective function in this example mode could be: M-1 1 m— 1 Above all, this method is useful when the estimated thermal contact resistance (Re) is minimal or is otherwise estimated to be imperceptible or negligible. PIPE APPLICATION MODE - REAL-TIME MEASUREMENTS USING PARAMETER ESTIMATION In the example mode of the periodic measurements-pipe application that uses the estimation of 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ .Wn.íor.m Tcalcutaíed Ujn )

[77] RMSE = I— 154 parameter, data processing by the control circuitry begins once all measurements are taken. Thus, in the previous experimental pipeline test, measurements were output every 75 seconds in a periodic mode. NITI sensor data (e.g., CHFT+ or CHFT-) were alternatively processed in real time to provide real-time outputs of convection coefficient (h), core fluid temperature (Tpiuid), and / or resistance of thermal contact (Re) between the NITI sensor and pipe / duct surfaces. As time passes, more data points are added to the surface heat flux and surface temperature curves and are processed in real time by a data processing method that includes a parameter estimation scheme and outputs the data. values ​​in less than 1 second. PIPE APPLICATION MODE - REAL-TIME MEASUREMENTS WITHOUT PARAMETER ESTIMATION Equation

[64] can be rearranged as: / Pipe.tu—G Sensor,ti—Asenso r,UrÓ where: 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ Combining equation

[78] and equation

[79] : 155 _ Σ;”1 When the thermal contact resistance (Re) between the NITI sensor (e.g. CHFT+ or CHFT-) and the pipe / duct surfaces is known, equation

[80] could be used for real-time measurement of the convection coefficient ( h) when a typical value for the thermal time constant (τ) is entered on the right side. As mentioned previously, the thermal time constant (τ) is a function of the convection coefficient (h). Thus, a typical value for the coefficient of convection (h) needs to be determined. In some exemplary embodiments, for example when the change in the convection coefficient (h) is of interest, the quantity Tsensor, or -q sensor, or X Re could be assumed at one or more specified times. In other exemplary embodiments, the quantity Tsensor, or -qsensor, or X Re could be determined, for example, by using an additional temperature sensor; the output of which is indicative of the pipe surface and / or core (ie internal) fluid temperature. Although the calculated value of the convection coefficient (h) on the left side will not be exact, it will still be sufficient for accurate quantitative and / or qualitative measurements. Also, for most accurate results, the typical value for the coefficient of 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ convection (h), which refers to the thermal time constant 156 (τ), on the right side could be updated with respect to time to reflect the most recent and / or precise value calculated by equation

[80] . In other methods, the values ​​for the convection coefficient (h) on the right and left sides could be determined at the same time, providing accurate quantitative measurements. This could omit the need for input of a typical convection coefficient (h) value on the right hand side. If the value of the thermal contact resistance (Re) is unknown, it can be determined (for example, by the NITI procedures described above) or otherwise determined and taken into account. In some cases, the thermal contact resistance (Re) could be estimated to be imperceptible. Input of the determined value of convection coefficient (h) from equation

[80] into a correlation equation (e.g., equation [66) results in corresponding values ​​of flow velocity (ύ) in real time. Furthermore, under ready-state conditions, equation

[80] reduces to: 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ Asensor.m Asenso? ,(J — Q sensor,mx —(^Senior.O—Asensor,Dx Equation

[80] no longer requires the typical value of the thermal time constant (τ) on the right hand side. The 157 ready state conditions could be achieved in a variety of ways including the set of control circuits that regulate the thermal flow and / or temperature presented at the surface by means of external thermal devices (for example, heaters, coolers, etc. ) . A similar rearrangement can be done for equation

[76] where the total heat transfer coefficient (U) is used and produces: Σ;1x (1 - eτj [ 8 Ή and in ready state conditions: / AQCLn / LZnZ / E / YIAI Qseíisüfjjt QSensor,o—Sensor,L> |S3| PIPE APPLICATION MODE - NITI DUO SENSOR For an example NITI DUO sensor mode when using the first and second parallel NITI sensor nodes (each node has a pair of heat flux-temperature sensors), two independent equations are formed: t Ir'¿ ' [i *. ... 'Mf, 1 V1I.,., -1 'n‘ L rofi ^.Sfnsrjr2.in—ΦϊιίιvnrJjn— —)(l-e1-1) R 158 Using an example differential basis data processing method, equation

[84] -equation

[85] produce: X (1- e"' Ϊ -b -(x (1 — e-<· * / )) . h =;---__----------- /

[86] (TwnjOrl.n! Q.Srnv,,'! mXr 1) .ν,ιι-Λ.,η k:z) This transient equation is the result of the DUO NITI sensor configuration and allows the real-time measurement of the convection coefficient (h) without considering the central fluid temperature (TFiuíd), when a typical value for the thermal time constant ( zj, a function of the convection coefficient (h), on the right side. Although the calculated value of the convection coefficient (h) on the left side will not be exact, it will still be sufficient for accurate quantitative and / or qualitative measurements. Additionally, for most accurate results, the typical value for the convection coefficient (h), which refers to the thermal time constant (zj, on the right side) could be updated with respect to time to reflect the most recent value and / o calculated by means of equation

[86] . In other methods, the values ​​for the convection coefficient (h) on the right and left sides could be determined at the same time, providing precise quantitative measurements. This could omit the need for the entry of a typical value of convection coefficient (h) on the right side. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 159 Estimated values ​​for thermal contact resistances (Reí and Rec) between each NITI sensor node (e.g., CHFT+ or CHFT-) and the pipe / duct surfaces can be determined (e.g., by NITI procedures described in advance) or otherwise determined and taken into account. In some cases, the thermal contact resistances (Reí and / or Rec') could be estimated to be imperceptible. Under ready-state conditions, equation

[86] reduces to: . _ G / .Vtm.vurl ιύ-τι rl — v-π ~a "and? ' "and L ' J VSerisorl,m—?5in.Torl,mx —U Sensor?,—^SensorZ.n?.xwhere a typical value of the thermal time constant (zj is no longer required on the right side. Ready state conditions could be maintained in a variety of ways including control circuitry that regulates the heat flux and / or temperature presented at the surface of each sensor node by means of external thermal devices (e.g., heaters, coolers, etc.). ). An example DUO CHFT+ / - modality with one sensor node having a heater (CHFT+) and another sensor node without a heater (CHFT-) was tested on a 0.01905 m inner diameter L-type copper pipe (34 ) with a wall thickness of 0.00127 m (0.05) with water flowing through / «QCLn / LZnZ / E / YIAI 160 this at different flow rates and temperatures. The DUO CHFT+ / - arrangement was coupled to the pipe surface and measurements were compared against an example CHFT+ modality as well as an in-line flow meter. Table 5. Results of an example DUO modality CHFT+ / / AQCLn / LZnZ / E / YIAI Flow meter CHFT+ DUO CHFT+ / - Flow rate ) j Speed ​​। ¿|UÍ ) of flow ,ηιη Flow velocity ’r>!n 4.0 3.8 3.9 7.0 7.3 7.5 10.0 9.8 10.4 13.0 13.1 12.9 16.0 15.9 15.6 A similar rearrangement can be done for equation

[76] , where the total heat transfer coefficient (U) is used, and produces: Hsemon p - ¿wü I Σ71 X (1 - e ' j * í1-e [ T T -T and in ready state: ,, _ Vi’fnsori.m—^sensor'Z.ni rvoi — ... _ I’ .1Jyenso r 1, zn ' 5 ensor ¿, m In addition to the flow rate (ύ), and the core fluid temperature (Triuid), this NITI application (i.e., determining pipeline parameters) might be able to determine the thermal energy that is being transferred by the flow within of the pipe, a function of ύ and Tpiuid. CORROSION / FOULING DETECTION APPLICATION All example methods and modalities IMJ 161 example for determining external pipe parameters determined h or U which is then input into a correlation function to determine the flow velocity (ύ). Monitoring the h or U value independently can also be used to determine the occurrence of corrosion or scaling of a pipe / duct over time. This is because the value of h or U must be consistent for a given amount of flow velocity occurring in the pipe. As corrosion or scaling occurs, the values ​​begin to change and in this way, corrosion or scaling can be detected. Monitoring the thermal time constant (t) of a pipe / duct made, for example, of high thermal conductivity materials also produces a similar capacity. For example, in this example application, the thermal time constant (τ) is a function of pipe / duct properties including density (p), specific heat capacity (C), and wall thickness ( δ). The values ​​of these properties are impacted by corrosion or scaling which consequently affects the thermal time constant (r) of the pipe / duct. APPLICATION OF INTERNAL TEMPERATURE MEASUREMENT OF PIPE OR DUCT Combining equation

[62] and equation

[63] : i Pipo.m = Iptuia + ----£---- h -------~h---------X·1"e 19 )J= 1 162 Rewriting equation

[90] in terms of the NITI sensor outputs and including the effects of thermal contact resistance (Re) between the NITI sensor and the pipe / duct surfaces: „,fl.í,r. t -,·. r-n,.. Q .ShuAri' ,n \1 / 4tensar,!—.? । -1 1 | e i ™ x R, = freM + ---7---+ ) (---------7---------NI - fτ) [91 J π n 1=L Rearranging and realizing that the Tpiuid is dependent on values ​​that change with respect to time (the measurement index (m)): ,Yo . ·P_r ... ,, Q .íi.nynr.n \ ' Atensui,! i~is! | -—-) l J>1 OíIMU.’H ΠΑηί-·.;η X 4,· - / ( - )(1 O ) [ )—| nn = 1 Equation

[92] is an example equation for measuring core fluid temperature (TFiuíd,m) in pipes or conduits with a high thermal conductivity (e.g., copper) and is used in the following example embodiments. For some of these example embodiments, the values ​​of the convection coefficient (h), the estimated thermal contact resistance (Rc) between the NITI sensor and the pipe / duct surfaces, and / or the thermal time constant need to be determined. (τ) . This can be done, for example, by determining these values ​​(for example, by means of the CHFT+ or CHFT- methods described above) or by entering default values ​​(for example, values ​​from a / « book QCLn / LZnZ / E / YIAI text). 163 Similar to the example embodiments for those that can be used with equation

[76] , where the total heat transfer coefficient (U) is used instead of a combination of the convection coefficient (h) and the thermal contact resistance (Re) between the NITI sensor and pipe / duct surfaces. INTERNAL PIPE TEMPERATURE MODE - CHFT+ (ACTIVE THERMOMETRY) A CHFT+ modality uses a built-in external thermal device such as a heater to create a thermal event (ie, heat transfer) that can be used to perform NITI. For the measurement of the core fluid temperature (TFiuid,m) , the heater could operate in any mode (ready, periodic, cycling, etc.) and, in this example, equation

[92] would output the fluid temperature center (TFiuid,m) accurately and in real time when the values ​​for the convection coefficient (h), the thermal time constant (τ), and the estimated thermal contact resistance (Re) are entered on the right hand side. These values ​​could be determined, for example, using a data processing method (eg, including a parameter estimation scheme) or otherwise determined and taken into account. In some cases, the thermal contact resistance (Re) could be estimated to be imperceptible. Although not required, it could be / AQCLn / LZnZ / E / YIAI 164 beneficial the cover of the CHFT+ with materials to avoid the erroneous signals of the external stimuli such as the environmental changes, the contact, etc. Table 6 provides experimental results of an example CHFT+ (with built-in heater) modality when used to measure the core fluid temperature (Triuid,m) of a 0.01905 m (ti) ID Type L copper pipe with a wall thickness of 0.00127 m (0.05) at different flow velocities where the measurements of the central fluid temperature gauge (TFiuíd,^) have been averaged with respect to time: Table 6. CHFT+ example mode results for internal pipe temperature 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ Rate, gal t of mean flow CHFT+ Output(O TFiuid measured ( ;C) 1 VI1 > O 1 24 76 24.86 0.10 24.98 25.09 0.11 25 18 2530 0.12 25 42 25.52 0.10 25.62 25.73 0.11 165 Table 6. (Continued) / AQCLn / LZnZ / E / YIAI Flow gat speed3° (ΉΓΤτ Output) (') Tpiuid measure i c» ΙΛΤΚ O 25.85 25.95 0.10 22 28 22 41 0.13 22 45 22.58 0.13 4 22 75 22.86 0.11 22.95 23 10 0.15 23 25 23.31 0.06 23 70 23.84 0.14 22 65 22 68 0.03 22 86 22.91 0.05 7 23 14 23 19 0.05 23.40 23 46 0.06 23 77 23 85 0.08 24.12 24.17 0.05 2546 25 58 0.12 25 66 25.7 6 0.10 10 29.24 29.27 0.03 2963 29.69 0.06 29 89 29.86 0.03 30.34 30.32 0.02 25 47 25 61 0.14 25 65 25.77 0.12 13 25 86 25 99 0.13 26.04 26 13 0.09 26 25 26.40 0.1S 26 51 26.66 0.15 2624 26.42 0.18 26 38 26.49 0.11 16 26.51 26.60 0.09 2668 26.79 0.11 26 83 27.01 0.18 27 02 27.19 0.17 A graph showing the results of an example CHFT+ mode (with integrated and controlled heater) is shown in Figure 35 when used to measure the core fluid temperature (TFiuid,m) of a type L diameter copper pipe. interior of 0.01905 m (3A) with a wall thickness of 0.00127 m (0.05) that experiences fluid flow at 56.7812 It / m (15 gal / m). This graph shows 166 that the CHFT+ example modality is able to determine the central fluid temperature (Tn / uid,™) of a pipe without considering the surface temperature conditions. Specifically, in this example, the surface temperature increases with time as a result of the built-in heater being turned on. Disregarding this consistent increase in surface temperature with respect to time, the CHFT+ example modality measures the core fluid temperature (TFiuid,™) within the copper tubing in close compliance with an internal probe placed within the tubing and within of the pipe flow. INTERNAL PIPE TEMPERATURE MODE - CHFT-(PASSIVE THERMOMETRY) A CHFT-mode uses external thermal events such as pipe heat dissipation to the surroundings to perform the NITI. When subjected to an external thermal event, equation

[92] , for example, would output the core fluid temperature (Triuid,™) accurately and in real time when the values ​​for the convection coefficient (h), the constant thermal time (r), and the estimated thermal contact resistance (Re) are entered on the right side. These values ​​could be determined, for example, using a data processing method (for example, including a parameter estimation scheme) or otherwise determined and taken into account. In some / «QCLn / LZnZ / E / YIAI 167 cases, the thermal contact resistance (Re) could be estimated to be imperceptible. Although not required, it may be beneficial to cover the CHFT- with insulating material to prevent erroneous signals from external stimuli such as environmental changes, touch, etc. INTERNAL PIPE TEMPERATURE MODE - CHFT+ (PERIODIC MEASUREMENT) In addition to the example real-time methods and the example modalities for internal temperature of the pipe or conduit measurement above, a NITI sensor can be used to take periodic measurements of core fluid temperature (Tfiuíci) when operating in conditions different from ready state. For example, ready-state measurements before a thermal event (Tsensor, o, q sensor, o) can be compared to ready-state measurements during, after, or at the end of a thermal event (Tsensor,ενώ - q sensor, end) for the purpose of determining the core fluid temperature (Tpiuid) using: X 'Psen.'itir.F.ND --7----------------------1931 ÍJ'míw.C'iVP ^Sensor,ϋ Both of the example modes CHFT+ and / or CHFT may be subject to different ready state conditions with respect to time. However, exemplary CHFT+ embodiments are preferred due to the increase in operational control of one or more of the thermal event devices. 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 168 that could be used to create different ready state conditions. INTERNAL PIPE TEMPERATURE MODE - CHFT+ (ZERO THERMAL FLOW THERMOMETRY) Using the control circuitry, an example CHFT+ modality could be used to create a zero heat flow environment where no heat transfer occurs between the pipe and sensor surfaces, that is, where no heat enters or leaves the pipe. which is measured by the thermal flow sensor (the minimum voltage output, i.e. zero). Under ready-state conditions, a zero heat flux environment simplifies equation

[92] into: I Huid m—I Sensor,m 194] where the measured sensor temperature (Tsensor,ni) OS equivalent to the core fluid temperature (TFiuid,in) . The advantage of this method is the independence of the measurement of the core fluid temperature (TFiuid,m) from the internal parameter values ​​(e.g., the convection coefficient (h), the thermal time constant (r), etc. .) and the thermal contact resistance (Re”) once a ready-state zero thermal flow environment is obtained. Until a ready-state zero heat flow environment is obtained, other modes, such as the active thermometry mode for internal temperature measurement 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 169 pipe or conduit, can be used to take accurate measurements of the core fluid temperature (Tpiuid,^ . The amount of time required to achieve these ready-state conditions, which is determined by the measured temperature output of the sensor (Ts ensor,^rVdlíd depending on the example modality used and is a common limitation of existing zero heat flow technologies that do not use NITI technology. Until a ready state zero heat flow environment is obtained, the zero heat flow thermometry example modes could use other example modes, such as an active thermometry example mode for internal pipe temperature measurement, to take accurate core fluid temperature measurements ( TFluid, m). INTERNAL PIPE TEMPERATURE MODE - DUO NITI (DOUBLE THERMOMETRY) For an exemplary DUO NITI sensor modality when using the first and second parallel NITI sensor nodes (each node has a pair of heat flow-temperature sensors), two independent equations are formed when placed in an elaborate pipe / duct. of a material with a high thermal conductivity: 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 170 „,. lf .. v -[mi (E'í?Hsor2,m ·<ύ (2 (ri de:) DíuÍdm ^1 n 1" y।xU ') 1|96| \ Vi / Using an arithmetic quotient base data processing method, equation

[95] / equation

[96] produces: / . . \rr-v Tí ^.(^( ^ +Γϋ U Sé'jnorl.m uYes'nstirl.m * "C1J Λ^ίιηϊΐ.ιπ _ \ /

[97] X - / , ™ . , ' v fl - a1r '' 'K I [ ‘ / sensorZ.U ' 1ntf;>sensor2, / Λl1 LJf Reordering / AQCLn / LZnZ / E / YIAI This transient equation is the result of the DUO NITI setup and allows real-time measurement of the core fluid temperature (TFiuid.m) when typical values ​​for the convection coefficient (h) and thermal time constant ( zj on the right side. Estimated values ​​for the thermal contact resistances (Rei and Red) between each NITI sensor node (for example, CHFT+ or CHFT-) and the pipe / duct surfaces can be determined (for example, by means of NITI procedures described below). previously) or otherwise determined and taken into account. In some cases, the thermal contact resistances (Rei and / or Red) could be estimated to be imperceptible. Under ready state conditions, and where Rc= Raí = Red or Reí and Red are estimated to be imperceptible, equation

[98] reduces to: 171 „ _ ¡Sensor2rm Qüensorl.m—X'ensorl.mx^Sensat 2,m .. IFluid.m —: ;ll íhc’ni'ür l,m—2,m where the typical values ​​for the convection coefficient (h) and the thermal time constant (τ) are no longer required on the right-hand side. This implies that, when in ready-state conditions, equation

[99] can be used for pipes or conduits without considering the pipe / duct material, wall thickness, etc. Ready state conditions could be achieved in a variety of ways including control circuitry that regulates heat flow and / or temperature occurring at the fabric surface by means of external thermal devices (e.g., heaters, coolers, etc.). A graph showing the results of an example DUO CHFT+ / - modality (one sensor node with a heater and one sensor node without a heater) when used to measure the internal temperature of a copper pipe is shown in Figure 36. L type of 0.01905 m (34) inner diameter with a wall thickness of 0.00127 m (0.05) experiencing fluid flow at 56.7812 It / m (15 gal / m). In this example, both of the sensor nodes were covered with insulation in order to prevent sporadic heat and temperature transfer signals from impacting the measurement quality. This example was made in 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 172 ready and transient state conditions. As shown in the graph, there is close compliance between the example DUO CHFT+ / - mode and an internal probe (placed inside the pipe and inside the pipe flow). A graph showing the results of an example DUO CHFT+ / - modality (one sensor node with a heater and one sensor node without a heater) when used to measure the internal temperature of a CPVC pipe is shown in Figure 37. 80 gauge bore of 0.0492506 m (1.939) with a wall thickness of 0.0055372 m (0.218) experiencing fluid flow at 189.271 It / m (50 gal / m). In this example, both of the sensor nodes were not covered with insulation. This example was performed under ready-state conditions where internal pipe parameters are not required to make precise or accurate measurements. As shown in the graph, there is close compliance between the example DUO CHFT+ / mode and an internal probe (placed inside the pipe and inside the pipe flow). However, there are more sporadic measurements as a result of the lack of coverage of isolated sensor nodes. Although various exemplary embodiments have been shown and described in detail, the claims are not limited to any particular embodiment or example. Also, the above example embodiments use thermal signals / AQCLn / LZnZ / E / YIAI 173 (e.g., heat transfer and temperature signals) combined with analytical solutions that are based on thermal mathematical models to determine one or more internal properties of an object. Other exemplary modalities could use other methods including, but not limited to empirical methods, machine learning methods (e.g., neural networks), regression basis methods, artificial intelligence basis methods, motion basis methods. average, etc. For the purpose of determining one or more internal properties of an object based on the thermal signals measured on the surface of the object. In other example embodiments, the output of other base devices without NITI could be used in conjunction with NITI techniques to determine one or more internal properties of the internal region of an object. For example, the output of an internal temperature probe inside a pipe could be used with a surface-mounted NITI sensor to determine the flow rate inside the pipe. In the present application, the words configured to... are used to mean that an element of an apparatus has a configuration capable of performing the defined operation. The term configuration could also refer to a hardware interconnection arrangement or mode 7AQC ίΠ / ίΖηΖ / Ε / ΥΙΛΙ 174 or software. For example, the appliance could have dedicated hardware that provides the defined operation, or a processor or other processing device could be programmed to perform the function. The term configured to does not imply that the appliance or element needs to be changed in any way for the purpose of providing the defined operation. Nothing in the above description should be read to imply that any particular member, stage, rank or function is essential. All structural and functional equivalents for members of the above-described embodiments that are known to those of ordinary skill in the art are incorporated herein by reference and are intended to be included. Furthermore, no modality, feature, component or stage in this specification is intended to be dedicated to the public. Although the illustrative embodiments have been described in detail herein with reference to the accompanying drawings, it is understood that the invention is not limited to those precise embodiments, and that various changes and modifications can be made herein by a person skilled in the art. without departing from the scope of the attached claims.

Claims

1. A system for the non-invasive detection of an object having a volume with a surface and an internal region, characterized in that it comprises: a non-invasive sensor including: a heat flow sensor having one or more heat flow sensor output terminals; a temperature sensor having one or more temperature sensor output terminals, wherein the non-invasive sensor is adapted to be placed on or near the surface of the object, wherein the internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution; a circuit assembly, coupled with one or more of the heat flow sensor output terminals and one or more of the temperature sensor output terminals, for: receiving a measured temperature signal from the temperature sensor at one or more specified times;receive a measured heat flow signal from the heat flow sensor at one or more specified times; determine an indicative quantity for one or more of the internal parameters at one or more specified times; determine an internal temperature distribution of the internal region of the object at one or more specified times based on at least the measured temperature signal, the measured heat flow signal, and the indicative quantities determined for the internal parameters; and generate information indicating the internal temperature distribution of the internal region of the object at one or more specified times.

2. The system according to claim 1, characterized in that the circuit assembly is configured to determine a measurement of heat transfer leaving or entering the object at the surface as a function of the measured thermal flow signal.

3. The system according to claim 1, characterized in that the circuit assembly is configured to generate information indicating one or more of the indicative quantities determined for the internal parameters at one or more specified times.

4. The system according to claim 1, characterized in that the circuit assembly is configured to include one or more effects associated with an estimated thermal contact resistance between the temperature sensor and the object surface.

5. The system according to claim 1, characterized in that the circuit assembly is configured to generate the information indicating the internal temperature distribution of the internal region of the object at a specified time in less than one second of this specified time.

6. The system according to claim 3, characterized in that the circuit assembly is configured 7AQC ίΠ / ίΖηΖ / E / YΙΛΙ 177 to generate the generated information indicating one or more of the indicative quantities determined for the internal parameters at a time specified in less than one second of this specified time.

7. The system according to claim 1, characterized in that the circuit assembly is configured to use a predetermined indicative amount for one or more of the internal parameters at specified times.

8. The system according to claim 1, characterized in that the circuit assembly is configured to use an estimated indicative quantity for one or more of the internal parameters at specified times.

9. The system according to claim 1, characterized in that the circuit assembly is configured to: determine an estimated indicative quantity for one or more of the internal parameters at one or more specified times based on at least the measured temperature signal, the measured thermal flow signal, and one or more effects associated with an estimated thermal contact resistance between the temperature sensor and the object surface.

10. The system according to claim 9, characterized in that the circuit assembly is configured to: determine a calculated sensor temperature at one or more specified times as a function of at least the measured temperature signal, the measured heat flow signal, one or more of the estimated indicative quantities of internal parameter, one or more remaining indicative quantities of internal parameter when there are one or more remaining indicative quantities of internal parameter, and one or more effects associated with the estimated thermal contact resistance; and compare the calculated sensor temperature with a measured temperature that is a function of the measured temperature signal to determine a difference.

11. The system according to claim 10, characterized in that the circuit assembly is configured to: adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance based on the difference to produce the updated estimated indicative quantities for the internal parameters and the estimated thermal contact resistance; and determine the internal temperature distribution of the internal region of the object based on at least the measured temperature signal, the measured thermal flux signal, and the updated estimated indicative quantities for the internal parameters and the estimated thermal contact resistance.

12. The system according to claim 10, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance to reduce the difference, and wherein when the difference is less than a threshold quantity or is otherwise determined to be minimal, the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance are optimally updated, and the circuit assembly is configured to generate information indicating the optimally updated estimated indicative quantities for the internal parameters and the estimated thermal contact resistance.

13. The system according to claim 10, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance using one or more optimization techniques.

14. The system according to claim 10, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance using one or more machine learning techniques.

15. The system according to claim 9, characterized in that the circuit assembly is configured to determine the estimated thermal contact resistance 7AQC ίΠ / ίΖηΖ / E / YΙΛΙ 180 independent of the internal parameters.

16. The system according to claim 9, characterized in that the circuit assembly is configured to determine the estimated thermal contact resistance based on internal parameters.

17. The system according to claim 9, characterized in that the circuit assembly is configured to determine the estimated thermal contact resistance based on a total ready-state thermal resistance of the object.

18. The system according to claim 10, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance in real time.

19. The system according to claim 1, characterized in that the circuit assembly is configured to determine the internal temperature distribution of the internal region of the object using one or more machine learning techniques.

20. The system according to claim 1, characterized in that the circuit assembly is configured to determine the internal temperature distribution of the internal region of the object using one or more thermal mathematical models for the object. 7AQC iP / iZηZ / E / YILI 181 21. The system according to claim 20, characterized in that one or more of the thermal mathematical models has a transient temperature solution defined as a function of the initial temperature distribution, heat flow, time, space, and internal parameters.

22. The system according to claim 20, characterized in that one or more of the thermal mathematical models includes one or more prepared state conditions.

23. The system according to claim 21, characterized in that the initial temperature distribution is based on a prepared state temperature profile.

24. The system according to claim 1, characterized in that the internal parameters include one or more from a list comprising: R: the prepared-state thermal resistance, x: the surface depth, R Total: the total prepared-state thermal resistance, U: the total heat transfer coefficient, k: the thermal conductivity, p: the density, C: the heat capacity, pC: the volumetric heat capacity, ylkpC: thermal inertia, 182 a=k / pC: the thermal diffusivity, h: the convective heat transfer coefficient, ó: the flow rate, δ: the wall thickness, τ: the time constant, yw: the blood perfusion.

25. The system according to claim 1, characterized in that the non-invasive sensor includes thermal insulation to reduce noise in the measured signal.

26. The system according to claim 1, characterized in that the non-invasive sensor includes thermal insulation to control a quantity of heat transfer that occurs through the non-invasive sensor.

27. The system according to claim 1, characterized in that the temperature sensor is a thin-film thermocouple, a thin temperature sensor, a resistance temperature sensor, or a fiber optic temperature sensor.

28. The system according to claim 1, characterized in that the thermal flow sensor is based on differential thermopile technology.

29. The system according to claim 1, characterized in that the thermal flow sensor is based on thin-film technology. / «QCLn / LZnZ / E / YIAI 183 30. The system according to claim 1, characterized in that the thermal flow sensor is a thin thermal flow sensor.

31. The system according to claim 1, characterized in that the thermal flow sensor is a flexible thermal flow sensor.

32. The system according to claim 1, characterized in that the thermal flow sensor is based on one or more thermoelectric devices.

33. The system according to claim 1, further characterized in that it comprises one or more external thermal devices for heating and / or cooling the non-invasive sensor.

34. The system according to claim 1, characterized in that the circuit assembly controls one or more external thermal devices to heat and / or cool the non-invasive sensor.

35. The system according to claim 1, characterized in that the circuit assembly controls one or more external thermal devices to heat and / or cool the non-invasive sensor towards a measured thermal flow signal and / or a measured temperature signal.

36. The system according to claim 1, characterized in that the temperature sensor is located in or near a thermal flow sensor detection area. 7AQC iP / iZηZ / E / YILI 184 37. The system according to claim 1, characterized in that the temperature sensor is located between the object and the thermal flow sensor.

38. The system according to claim 1, characterized in that the thermal flow sensor is located between the object and the temperature sensor.

39. A system for the non-invasive detection of an object having a volume with a surface and an internal region, characterized in that it comprises: a non-invasive sensor including: a heat flow sensor having one or more heat flow sensor output terminals; a temperature sensor having one or more temperature sensor output terminals, wherein the non-invasive sensor is adapted to be placed on or near the surface of the object, wherein the internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution; a circuit assembly, coupled with one or more of the heat flow sensor output terminals and one or more of the temperature sensor output terminals, for: receiving a measured temperature signal from the temperature sensor at one or more specified times;receive a measured heat flow signal from the heat flow sensor at one or more specified times; determine an estimated indicative quantity for one or more of the internal parameters at one or more specified times based on the 7AQC ίΠ / ίΖηΖ / E / YΥΙΛΙ 185 minus the measured temperature signal and the measured heat flow signal; and generate information indicating one or more of the estimated indicative quantities determined for the internal parameters at one or more specified times.

40. The system according to claim 39, characterized in that the circuit assembly is configured to determine a measurement of heat transfer leaving or entering the object at the surface as a function of the measured thermal flow signal.

41. The system according to claim 39, characterized in that the circuit assembly is configured to include one or more effects associated with an estimated thermal contact resistance between the temperature sensor and the object surface.

42. The system according to claim 39, characterized in that the circuit assembly is configured to: determine one or more of the estimated indicative quantities for the internal parameters at one or more specified times based on at least the measured temperature signal, the measured thermal flow signal, the determined indicative quantities for one or more of the internal properties, and one or more effects associated with an estimated thermal contact resistance between the temperature sensor and the object surface.

43. The system according to claim / AQCLn / LZnZ / E / YIAI 186 39, characterized in that the circuit assembly is configured to generate the generated information which indicates one or more of the estimated indicative quantities determined for the internal parameters at a specified time in less than one second of this specified time.

44. The system according to claim 42, characterized in that the circuit assembly is configured to generate the generated information indicating one or more of the estimated indicative quantities determined for the internal parameters at a specified time in less than one second of this specified time.

45. The system according to claim 42, characterized in that the circuit assembly is configured to use a predetermined indicative quantity for one or more of the internal properties at specified times.

46. ​​The system according to claim 42, characterized in that the circuit assembly is configured to use an estimated indicative quantity for one or more of the internal properties at specified times.

47. The system according to claim 42, characterized in that the circuit assembly is configured to: determine a calculated sensor temperature at one or more specified times as a function of at least the measured temperature signal, the measured thermal flow signal, one or more estimated indicative quantities of internal parameter, one or more indicative quantities of internal property, and one or more effects associated with the estimated thermal contact resistance; and compare the calculated sensor temperature with a measured temperature that is a function of the measured temperature signal to determine a difference.

48. The system according to claim 47, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance based on the difference to produce the updated estimated indicative quantities for the internal parameters and the estimated thermal contact resistance.

49. The system according to claim 47, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance to reduce the difference, and wherein when the difference is less than a threshold quantity or is otherwise determined to be minimal, the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance are optimally updated, and the circuit assembly is configured to generate information indicating the optimally updated estimated indicative quantities for the internal parameters and the estimated thermal contact resistance.

50. The system according to claim 47, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance using one or more optimization techniques.

51. The system according to claim 47, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance using one or more machine learning techniques.

52. The system according to claim 41, characterized in that the circuit assembly is configured to determine the estimated thermal contact resistance independent of the internal parameters.

53. The system according to claim 41, characterized in that the circuit assembly is configured to determine the estimated thermal contact resistance based on internal parameters.

54. The system according to claim 7AQC ίΠ / ίΖηΖ / E / YΙΛΙ 189 41, characterized in that the circuit assembly is configured to determine the estimated thermal contact resistance based on a total prepared-state thermal resistance of the object.

55. The system according to claim 47, characterized in that the circuit assembly is configured to adjust one or more of the estimated indicative quantities for the internal parameters and the estimated thermal contact resistance in real time.

56. The system according to claim 39, characterized in that the circuit assembly is configured to determine one or more of the estimated indicative quantities for the internal parameters using one or more machine learning techniques.

57. The system according to claim 39, characterized in that the circuit assembly is configured to determine one or more of the estimated indicative quantities for the internal parameters using one or more thermal mathematical models for the object.

58. The system according to claim 57, characterized in that one or more of the thermal mathematical models has a transient temperature solution defined as a function of the initial temperature distribution, heat flux, time, space, and the internal parameters / AQCLn / LZnZ / E / YIAI. 190 59. The system according to claim 57, characterized in that one or more of the thermal mathematical models includes one or more prepared state conditions.

60. The system according to claim 58, characterized in that the initial temperature distribution is based on a prepared state temperature profile.

61. The system according to claim 39, characterized in that the internal parameters include one or more from a list comprising: R: the prepared-state thermal resistance, x: the surface depth, RTotai: the total prepared-state thermal resistance, U: the total heat transfer coefficient, k: the thermal conductivity, ρ: the density, C: the heat capacity, pC: the volumetric heat capacity, ylkpC: the thermal inertia, a=k / pC: the thermal diffusivity, h: the convective heat transfer coefficient, ρ: the flow rate, δ: the wall thickness, τ: the time constant, yw: the blood perfusion. 7AQC ίΠ / ίZΖηZ / E / YΙΛΙ 191 62. The system according to claim 39, characterized in that the non-invasive sensor includes thermal insulation to reduce noise in the measured signal.

63. The system according to claim 39, characterized in that the non-invasive sensor includes thermal insulation to control a quantity of heat transfer that occurs through the non-invasive sensor.

64. The system according to claim 39, characterized in that the temperature sensor is a thin-film thermocouple, a thin temperature sensor, a resistance temperature sensor, or a fiber optic temperature sensor.

65. The system according to claim 39, characterized in that the thermal flow sensor is based on differential thermopile technology.

66. The system according to claim 39, characterized in that the thermal flow sensor is based on thin-film technology.

67. The system according to claim 39, characterized in that the thermal flow sensor is a thin thermal flow sensor.

68. The system according to claim 39, characterized in that the thermal flow sensor is a flexible thermal flow sensor. 7AQC iP / iZηZ / E / YILI 192 69. The system according to claim 39, characterized in that the thermal flow sensor is based on one or more thermoelectric devices.

70. The system according to claim 39, further characterized in that it comprises one or more external thermal devices for heating and / or cooling the non-invasive sensor.

71. The system according to claim 39, characterized in that the circuit assembly controls one or more external thermal devices to heat and / or cool the non-invasive sensor.

72. The system according to claim 39, characterized in that the circuit assembly controls one or more external thermal devices to heat and / or cool the non-invasive sensor towards a measured thermal flow signal and / or a measured temperature signal.

73. The system according to claim 39, characterized in that the temperature sensor is located in or near a thermal flow sensor detection area.

74. The system according to claim 39, characterized in that the temperature sensor is located between the object and the thermal flow sensor.

75. The system according to claim 39, characterized in that the heat flow sensor is located between the object and the temperature sensor. 7AQC iP / iZηZ / E / YILI 193 76. A system for the non-invasive detection of an object having a volume with a surface and an internal region, characterized in that it comprises: a first non-invasive thermal flow sensor-temperature sensor pair; a second non-invasive thermal flow sensor-temperature sensor pair; each of the first and second non-invasive thermal flow sensor-temperature sensor pairs including: a thermal flow sensor having one or more thermal flow sensor output terminals;a temperature sensor having one or more temperature sensor output terminals, wherein the first and second non-invasive thermal flow sensor-temperature sensor pairs are adapted to be placed in different locations on or near the surface of the object and are subjected to a differential thermal flow environment, and wherein the internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution, a circuit assembly, coupled with one or more of the thermal flow sensor output terminals and one or more of the temperature sensor output terminals of each of the first and second non-invasive thermal flow sensor-temperature sensor pairs, and configured to: receive a first measured temperature signal from the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair at one or more specified times;receive a first measured thermal flow signal from the thermal flow sensor in the first non-invasive thermal flow sensor-temperature sensor pair at one or more specified times; receive a second measured temperature signal from the temperature sensor in the second non-invasive thermal flow sensor-temperature sensor pair at one or more specified times; receive a second measured thermal flow signal from the thermal flow sensor in the second non-invasive thermal flow sensor-temperature sensor pair at one or more specified times;Determine an internal temperature distribution at one or more specified times based on at least the measured temperature signals from the temperature sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times and the measured thermal flow signals from the thermal flow sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times; and generate information indicating the internal temperature distribution at one or more specified times.

77. The system according to claim 76, characterized in that each respective temperature sensor is located between the object and its corresponding thermal flow sensor and / or in that each respective thermal flow sensor is located between the object and its corresponding 7AQC ίΠ / ίΖηΖ / E / YΙΛΙ 195 temperature sensor.

78. The system according to claim 76, characterized in that the circuit assembly is configured to determine a heat transfer measurement that is presented through the first non-invasive thermal flow sensor-temperature sensor pair and that exits or enters the object at the surface based on the first measured thermal flow signal at one or more specified times and / or determines a heat transfer measurement that is presented through the second non-invasive thermal flow sensor-temperature sensor pair and that exits or enters the object at the surface based on the second measured thermal flow signal at one or more specified times.

79. The system according to claim 76, characterized in that the circuit assembly is configured to: determine an indicative quantity for one or more of the internal parameters at one or more specified times; and determine the internal temperature distribution at one or more specified times based on at least the measured temperature signals from the temperature sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times, the measured thermal flow signals from the thermal flow sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times, and one or more of the determined indicative quantities for the internal parameters at one or more specified times.

80. The system according to claim 79, characterized in that the circuit assembly is configured to use an estimated and / or predetermined indicative quantity for one or more of the internal parameters at specified times.

81. The system according to claim 76, characterized in that the circuit assembly is configured to take into account one or more effects associated with an estimated thermal contact resistance between the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair and the object surface.

82. The system according to claim 76, characterized in that the circuit assembly is configured to take into account one or more effects associated with an estimated thermal contact resistance between the temperature sensor in the second non-invasive thermal flow sensor-temperature sensor pair and the object surface.

83. A system for the non-invasive detection of an object having a volume with a surface and an internal region, comprising: a first non-invasive thermal flow sensor-temperature sensor pair; a second non-invasive thermal flow sensor-temperature sensor pair; each of the first and second non-invasive thermal flow sensor-temperature sensor pairs including: a thermal flow sensor having one or more thermal flow sensor output terminals;a temperature sensor having one or more temperature sensor output terminals, wherein the first and second non-invasive thermal flow sensor-temperature sensor pairs are adapted to be placed in different locations on or near the surface of the object and are subjected to a differential thermal flow environment, and wherein the internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution, a circuit assembly, coupled with one or more of the thermal flow sensor output terminals and one or more of the temperature sensor output terminals of each of the first and second non-invasive thermal flow sensor-temperature sensor pairs, and configured to: receive a first measured temperature signal from the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair at one or more specified times;receive a first measured thermal flow signal from the thermal flow sensor in the first non-invasive thermal flow sensor-temperature sensor pair at one or more specified times; receive a second measured temperature signal from the temperature sensor in the second non-invasive thermal flow sensor-temperature sensor pair at one or more specified times; receive a second measured thermal flow signal from the thermal flow sensor in the second non-invasive thermal flow sensor-temperature sensor pair at one or more specified times;Determine an indicative quantity for one or more of the object's internal parameters at one or more specified times based on at least the measured temperature signals from the temperature sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times and the measured thermal flow signals from the thermal flow sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times; and generate information indicating one or more of the determined indicative quantities for the object's internal parameters at one or more specified times.

84. The system according to claim 83, characterized in that the circuit assembly is configured to determine a heat transfer measurement that is presented through the first non-invasive thermal flow sensor-temperature sensor pair and that exits or enters the object at the surface depending on the first / «QCLn / LZnZ / E / YIAI 199 measured thermal flow signal at one or more specified times and / or determines a heat transfer measurement that is presented through the second non-invasive thermal flow sensor-temperature sensor pair and that exits or enters the object at the surface depending on the second measured thermal flow signal at one or more specified times.

85. The system according to claim 83, characterized in that each respective temperature sensor is located between the object and its corresponding thermal flow sensor and / or in that each respective thermal flow sensor is located between the object and its corresponding temperature sensor.

86. The system according to claim 83, characterized in that the circuit assembly is configured to: determine an initial indicative quantity for one or more of the internal parameters at one or more specified times; and determine one or more of the indicative quantities for the internal parameters of the object at one or more specified times based on at least the measured temperature signals from the temperature sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times, the measured thermal flow signals from the thermal flow sensors in the first and second non-invasive thermal flow sensor-temperature sensor pairs at one or more specified times, and one or more of the determined initial indicative quantities for the internal parameters at one or more specified times.

87. The system according to claim 86, characterized in that the circuit assembly is configured to use an initial estimated and / or predetermined indicative quantity for one or more of the internal parameters at specified times.

88. The system according to claim 83, characterized in that the circuit assembly is configured to take into account one or more effects associated with an estimated thermal contact resistance between the temperature sensor in the first non-invasive thermal flow sensor-temperature sensor pair and the object surface and / or one or more effects associated with an estimated thermal contact resistance between the temperature sensor in the second non-invasive thermal flow sensor-temperature sensor pair and the object surface.

89. A non-invasive sensor adapted to be placed on or near a surface of an object having a volume with a surface and an internal region, wherein the internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution, characterized in that it comprises: a non-invasive thermal flow sensor-temperature sensor pair;The non-invasive thermal flow sensor-temperature sensor pair includes: a thermal flow sensor having one or more thermal flow sensor output terminals to provide a measured thermal flow signal for a location on or near the object surface, and a temperature sensor having one or more temperature sensor output terminals to provide a measured temperature signal for a location on or near the object surface, wherein the non-invasive sensor is configured to ensure that there is no mismatch between the measured thermal flow signal and the measured temperature signal.

90. The non-invasive sensor according to claim 89, further characterized in that it comprises one or more external thermal devices for heating and / or cooling the non-invasive thermal flow sensor-temperature sensor pair.

91. The non-invasive sensor according to claim 90, characterized in that one or more of the external thermal devices include a heater and / or a cooler.

92. The non-invasive sensor according to claim 89, characterized in that the thermal flow sensor is positioned to produce a differential voltage 7AQC ίΠ / ίΖηΖ / E / YΙΛΙ 202 indicative of the heat transfer occurring through the thermal flow sensor on the surface of the object.

93. The thermal flow sensor according to claim 92, characterized in that the differential voltage is related to the heat transfer occurring through the thermal flow sensor and on the surface of the object by a calibration constant or a sensitivity constant associated with the thermal flow sensor.

94. The thermal flow sensor according to claim 92, characterized in that the differential voltage is related to the heat transfer occurring through the thermal flow sensor and on the surface of the object by a calibration curve or a sensitivity curve associated with the thermal flow sensor.

95. The non-invasive sensor according to claim 89, characterized in that the thermal flow sensor is based on thin-film differential thermopile technology.

96. The non-invasive sensor according to claim 89, characterized in that the thermal flow sensor includes two or more thermocouple junctions connected in series to provide a voltage output that is indicative of a temperature difference across a given thermal resistance. 7AQC iP / iZηZ / E / YILI 97. The non-invasive sensor according to claim 89, characterized in that the temperature sensor is based on thermocouple, fiber optic or thermistor technology.

98. The non-invasive sensor according to claim 89, characterized in that a thickness of the temperature sensor is less than or equal to a thickness of the thermal flow sensor.

99. A non-invasive sensor adapted to be placed on or near a surface of an object having a volume with a surface and an internal region, wherein the internal region of the object has internal properties indicated by corresponding internal parameters and an internal temperature distribution, insofar as the non-invasive sensor comprises: a first non-invasive thermal flow sensor-temperature sensor pair; a second non-invasive thermal flow sensor-temperature sensor pair; each of the first and second non-invasive thermal flow sensor-temperature sensor pairs including: a thermal flow sensor having one or more thermal flow sensor output terminals;A temperature sensor having one or more temperature sensor output terminals, wherein the first and second non-invasive thermal flux sensor-temperature sensor pairs are adapted to be placed at different locations on or near the surface of the object and are subjected to a differential thermal flux environment. / AQCLn / LZnZ / E / YIAI 204; 100. The non-invasive sensor according to claim 99, further characterized in that it comprises one or more external thermal devices for heating and / or cooling the first non-invasive thermal flow sensor-temperature sensor pair and / or one or more external thermal devices for heating and / or cooling the second non-invasive thermal flow sensor-temperature sensor pair.

101. The non-invasive sensor according to claim 99, characterized in that the thermal flow sensor in each of the first and second non-invasive thermal flow sensor-temperature sensor pairs is positioned to produce a differential voltage indicative of the heat transfer occurring through the first and second non-invasive thermal flow sensor-temperature sensor pairs, respectively.

102. The thermal flow sensors according to claim 101, characterized in that the differential voltage produced by the thermal flow sensor in the first and second non-invasive thermal flow sensor-temperature sensor pairs is related to the heat transfer occurring through the corresponding thermal flow sensor-temperature sensor pair by a calibration constant, a sensitivity constant, a calibration curve, or a sensitivity curve associated with the thermal flow sensor. / AQCLn / LZnZ / E / YIAI 205 103. The non-invasive sensor according to claim 99, characterized in that the thermal flow sensors are based on thin-film differential thermopile technology.

104. The non-invasive sensor according to claim 99, characterized in that the thermal flow sensors include two or more thermocouple junctions connected in series to provide a voltage output that is indicative of a temperature difference across a given thermal resistance.

105. The non-invasive sensor according to claim 99, characterized in that the temperature sensors are based on thermocouple, fiber optic or thermistor technology.

106. The non-invasive sensor according to claim 99, characterized in that a temperature sensor thickness is less than or equal to a thermal flow sensor thickness.

107. The system according to claim 8, characterized in that the circuit assembly is configured to determine one or more indicative quantities estimated based on at least the measured temperature signal and / or the measured thermal flow signal.

108. The system according to claim 1, characterized in that the non-invasive sensor includes multiple / «QCLn / LZnZ / E / YIAI 206 thermal flow sensors and / or multiple temperature sensors.

109. The system according to claim 1, further characterized in that it comprises one or more non-NITI base devices.

110. The system according to claim 109, characterized in that the circuit assembly is configured to use one or more output signals from one or more of the non-NIT base devices to determine one or more of the indicative quantities for the internal parameters.

111. The system according to claim 109, characterized in that the circuit assembly is configured to use one or more output signals from one or more of the non-NiTi base devices to determine the internal temperature distribution.

112. The system according to claim 39, characterized in that the non-invasive sensor includes multiple thermal flow sensors and / or multiple temperature sensors.

113. The system according to claim 39, further characterized in that it comprises one or more non-NiTi base devices.

114. The system according to claim 113, characterized in that the circuit assembly is configured to use one or more output signals from one or more 7AQC ίΠ / ίΖηΖ / E / YΙΛΙ 207 of the non-NITI base devices to determine one or more of the estimated indicative quantities for the internal parameters.

115. The system according to claim 76, further characterized in that it comprises one or more external thermal devices for heating and / or cooling the first non-invasive thermal flow sensor-temperature sensor pair and / or one or more external thermal devices for heating and / or cooling the second non-invasive thermal flow sensor-temperature sensor pair.

116. The system according to claim 76, characterized in that the circuit assembly controls one or more external thermal devices for heating and / or cooling the first non-invasive thermal flow sensor-temperature sensor pair and / or one or more external thermal devices for heating and / or cooling the second non-invasive thermal flow sensor-temperature sensor pair.

117. The system according to claim 76, characterized in that the circuit assembly controls one or more external thermal devices for heating and / or cooling the first non-invasive thermal flow sensor-temperature sensor pair towards a measured thermal flow signal and / or a measured temperature signal and / or one or more external thermal devices for heating and / or cooling the second non-invasive thermal flow sensor-temperature sensor pair towards a 7AQC ίΠ / ίΖηΖ / E / YΥΙΛΙ 208 measured thermal flow signal and / or a measured temperature signal.

118. The system according to claim 76, characterized in that each respective thermal flow sensor is located between the object and its corresponding temperature sensor.

119. The system according to claim 76, further characterized in that it comprises one or more non-NITI base devices.

120. The system according to claim 119, characterized in that the circuit assembly is configured to use one or more output signals from one or more of the non-NiTi base devices to determine the internal temperature distribution.

121. The system according to claim 83, further characterized in that it comprises one or more external thermal devices for heating and / or cooling the first non-invasive thermal flow sensor-temperature sensor pair and / or one or more external thermal devices for heating and / or cooling the second non-invasive thermal flow sensor-temperature sensor pair.

122. The system according to claim 83, characterized in that the circuit assembly controls one or more external thermal devices for heating and / or cooling the first non-invasive thermal flow sensor-temperature sensor pair and / or one or more external thermal devices for heating and / or cooling the second non-invasive thermal flow sensor-temperature sensor pair.

123. The system according to claim 83, characterized in that the circuit assembly controls one or more external thermal devices for heating and / or cooling the first non-invasive thermal flow sensor-temperature sensor pair towards a measured thermal flow signal and / or a measured temperature signal and / or one or more external thermal devices for heating and / or cooling the second non-invasive thermal flow sensor-temperature sensor pair towards a measured thermal flow signal and / or a measured temperature signal.

124. The system according to claim 83, characterized in that each respective thermal flow sensor is located between the object and its corresponding temperature sensor.

125. The system according to claim 83, further characterized in that it comprises one or more non-NiTi base devices.

126. The system according to claim 125, characterized in that the circuit assembly is configured to use one or more output signals from one or more of the non-NITI base devices to determine one or more of the estimated indicative quantities for the internal parameters 7AQC ίΠ / ίΖηΖ / E / YΥΙΛΙ 210.

127. The non-invasive sensor according to claim 89, characterized in that the measured thermal flow signal indicates a measurement of heat transfer leaving or entering the object at the surface.

128. The non-invasive sensor according to claim 89, characterized in that it can be used in a system configured to determine one or more of the internal parameters of the internal region of the object.

129. The non-invasive sensor according to claim 89, characterized in that it can be used in a system configured to determine the internal temperature distribution of the internal region of the object.

130. The non-invasive sensor according to claim 89, characterized in that it includes multiple heat flow sensors and / or multiple temperature sensors.

131. The non-invasive sensor according to claim 89, characterized in that it can be used in a system comprising one or more non-NiTi base devices.

132. The non-invasive sensor according to claim 97, characterized in that one or more of the external thermal devices are used to heat and / or cool the non-invasive thermal flow sensor / temperature sensor pair towards a measured thermal flow signal 7AQC ίΠ / ίΖηΖ / E / YΙΛΙ 211 and / or a measured temperature signal.

133. The non-invasive sensor according to claim 99, characterized in that each of the thermal flow sensors is configured to determine a measurement of heat transfer leaving or entering the object at the surface.

134. The non-invasive sensor according to claim 99, characterized in that it can be used in a system configured to determine one or more of the internal parameters of the internal region of the object.

135. The non-invasive sensor according to claim 99, characterized in that it can be used in a system configured to determine the internal temperature distribution of the internal region of the object.

136. The non-invasive sensor according to claim 108, characterized in that it can be used in a system comprising one or more NIT-based devices.

137. The system according to claim 1, characterized in that the object is non-biological.

138. The system according to claim 39, characterized in that the object is non-biological.

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