Wireless temperature measurement system based on Internet of Things

Abstract

The invention discloses a wireless temperature measurement system based on the Internet of Things, and the system comprises the steps: S1, at least one temperature measurement node which comprises a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and a self-adaptive frequency hopping control module; s2, a wireless data transmission module which is electrically connected with the temperature measurement nodes and is used for transmitting temperature data and interference detection data; s3, the central processing unit receives the temperature data and the interference detection data through the wireless data transmission module, and stores and processes the temperature data and the interference detection data; and S4, the power supply module provides working electric energy for the temperature measuring nodes, the wireless data transmission module and the central processing unit. The system has the advantages of being stable in data transmission, high in anti-interference capability, wide in coverage range and high in temperature monitoring precision.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and in particular to a wireless temperature measurement system based on the Internet of Things. Background Art

[0002] With the rapid development of the Internet of Things and wireless communication technologies, the application requirements of wireless temperature measurement systems in the fields of industrial automation, environmental monitoring, and building safety are increasing continuously. However, in the existing technologies, wireless temperature measurement systems adopting fixed frequencies or simple frequency hopping strategies generally have problems such as limited coverage, vulnerability of data transmission to electromagnetic interference, and insufficient temperature measurement accuracy. In the existing technologies, the acquisition and transmission of temperature data mainly rely on a single radio frequency module for data transmission, and local electromagnetic interference cannot be effectively identified and suppressed in complex environments, resulting in easy interruption of data transmission in large-scale or multi-region environments and inability to achieve high-precision, stable, and convenient temperature monitoring.

[0003] At the same time, when the existing systems suppress electromagnetic interference, they mostly adopt fixed filtering or static frequency switching strategies, with low anti-interference capabilities and insufficient adaptability to the real-time changing electromagnetic environment; in addition, the centralized data processing scheme has defects such as data transmission delay and low processing efficiency, and it is difficult to meet the requirements of large-scale temperature monitoring systems for real-time performance and data consistency.

[0004] In summary, there is an urgent need for a wireless temperature measurement system based on the Internet of Things. By introducing radio frequency identification technology and adaptive frequency hopping anti-interference technology, this system can monitor local electromagnetic interference in real time in each wireless temperature measurement node and automatically switch to a low-interference standby frequency band according to the signal interference situation, thereby solving the deficiencies of traditional wireless temperature measurement systems in terms of coverage, data transmission stability, and temperature monitoring accuracy. Summary of the Invention

[0005] An object of the present invention is to provide a wireless temperature measurement system based on the Internet of Things. The present invention makes full use of radio frequency identification technology and adaptive frequency hopping anti-interference technology. By integrating a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and an adaptive frequency hopping control module in a temperature measurement node, accurate acquisition and wireless transmission of temperature data are realized. At the same time, local electromagnetic interference can be monitored in real time and automatically switched to a low-interference standby frequency band, with the advantages of stable data transmission, strong anti-interference ability, wide coverage, and high temperature monitoring accuracy.

[0006] A wireless temperature measurement system based on the Internet of Things according to an embodiment of the present invention includes the following components:

[0007] S1. At least one temperature measurement node, where the temperature measurement node includes a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and an adaptive frequency hopping control module. The temperature sensor is used to measure temperature data, the radio frequency identification module is used to implement node identity identification, the local electromagnetic interference detection module is used to detect the electromagnetic interference level in the node's area in real time and generate interference detection data, and the adaptive frequency hopping control module is used to automatically switch to a low-interference standby frequency band according to the interference detection data;

[0008] S2. A wireless data transmission module, electrically connected to the temperature measurement node, for transmitting temperature data and interference detection data;

[0009] S3. A central processing unit, which receives temperature data and interference detection data through the wireless data transmission module, and stores and processes the temperature data and interference detection data;

[0010] S4. A power supply module, which provides working electrical energy for the temperature measurement node, the wireless data transmission module, and the central processing unit respectively.

[0011] Optionally, S1 specifically includes:

[0012] S11. A temperature sensor, which includes a temperature sensing element and an analog-to-digital conversion unit. The temperature sensing element is used to collect ambient temperature analog signals, and the analog-to-digital conversion unit is used to convert the ambient temperature analog signals into temperature data;

[0013]

[0014] Where T is the temperature data, ADC value is the analog-to-digital conversion output value, n is the resolution of the analog-to-digital conversion unit, representing the number of bits of the analog-to-digital converter (used to quantize and represent the input ambient temperature analog signal within the digital range of 0 to 2 n ―1), V ref is the reference voltage, V offset is the voltage bias of the temperature sensor, and K is the sensor sensitivity coefficient;

[0015] S12. A radio frequency identification module, which includes a radio frequency antenna, a signal transceiver unit, and a data processing unit. The radio frequency antenna is used to transmit and receive radio frequency signals, the signal transceiver unit is used to modulate and demodulate the radio frequency signals, and the data processing unit is used to generate and parse node identity codes;

[0016] S13. Local electromagnetic interference detection module. The local electromagnetic interference detection module includes a multi-channel interference sensor, a signal conditioning circuit, and a digital comparison unit. The multi-channel interference sensor collects electromagnetic interference analog signals at different positions in the environment. The signal conditioning circuit amplifies and filters the electromagnetic interference analog signals. The digital comparison unit quantizes the processed electromagnetic interference analog signals to generate interference detection data.

[0017] S14. Adaptive frequency hopping control module. The adaptive frequency hopping control module includes a frequency control module and a preset frequency band storage unit. The frequency control module makes a judgment based on the interference detection data processed by the local electromagnetic interference detection module and the preset backup frequency band information, outputs a frequency switching instruction, and performs backup frequency band switching.

[0018] Optionally, S12 specifically includes:

[0019] S121. RF antenna. The RF antenna adopts a multi-band structure design, has the functions of transmitting and receiving multi-channel signals, and is electrically connected to the signal transceiver unit through an RF matching circuit.

[0020] S122. Signal transceiver unit. The signal transceiver unit includes an RF modulator, an RF demodulator, a power amplifier, and a low-noise amplifier. The RF modulator is used to modulate temperature data into an RF signal. The power amplifier amplifies the power of the RF signal output by the RF modulator. The low-noise amplifier is used to pre-amplify the low-power external RF signal received by the RF antenna. The RF demodulator is used to convert the RF signal pre-amplified by the low-noise amplifier into a baseband signal.

[0021] S123. Data processing unit. The data processing unit includes a microprocessor, a storage unit, and a communication interface module. The microprocessor is used to digitally process the baseband signal output by the signal transceiver unit. The storage unit is used to store node identity data and communication protocol parameters. The communication interface module is used to realize data exchange with other modules of the temperature measurement node.

[0022] S124. Impedance matching is achieved between the RF antenna and the signal transceiver unit through an RF matching circuit. The design of the RF matching circuit is based on the input impedance Z ant =R ant +jX ant of the RF antenna and the output impedance Z sr =R sr +jX sr for parameter calculation:

[0023]

[0024] Among them, Q is the quality factor of the matching network, ω is the working angular frequency, L is the value of the matching inductor, C is the value of the matching capacitor, and R ant represents the real part of the input impedance of the RF antenna, (j) represents the imaginary unit, which satisfies j 2 = -1, and X ant represents the imaginary part of the input impedance of the RF antenna, and R sr represents the real part of the output impedance of the signal transceiver unit, and X sr represents the imaginary part of the output impedance of the signal transceiver unit.

[0025] Optionally, the S13 specifically includes:

[0026] S131. A multi-channel interference sensor, which is composed of multiple independently arranged interference sensing elements, and each interference sensing element is used to collect the electromagnetic interference analog signal in its area;

[0027] S132. A signal conditioning circuit, which includes a multi-stage amplification module and a band-pass filtering module. Among them, the multi-stage amplification module is used to linearly amplify the low-amplitude electromagnetic interference analog signals output by each interference sensing element, and the band-pass filtering module is used to suppress signals in non-target frequency bands. Its processing process satisfies the following filtering convolution relationship:

[0028]

[0029] Among them, V in (t) is the input electromagnetic interference analog signal, h(t - τ) is the unit impulse response of the band-pass filter, and V out (t) is the output filtered signal;

[0030] S133. A digital comparison unit, which includes an analog-to-digital conversion module and an interference discrimination processor. The analog-to-digital conversion module is used to convert the conditioned electromagnetic interference analog signal into a discrete digital signal, and the interference discrimination processor performs weighted calculation and threshold comparison within a time window based on the digital signal values of multiple channels:

[0031]

[0032] Among them, I detected is the generated interference detection data, N is the number of channels, w i is the weight factor of the i-th channel, is the output value of the analog-to-digital converter of the i-th channel, n is the resolution of the analog-to-digital converter, V ref_max and V ref_min are the upper and lower limits of the reference voltage.

[0033] Optionally, the S14 specifically includes:

[0034] S141. The frequency control module in the adaptive frequency hopping control module. The frequency control module includes a judgment unit, an instruction generation unit, and a switching execution unit. The judgment unit receives the interference detection data generated after being processed by the local electromagnetic interference detection module and the spare frequency band information stored in the preset frequency band storage unit, and compares the interference levels of each spare frequency band information:

[0035]

[0036] where f sel is the selected spare frequency band information, F is the preset set of spare frequency bands, f i is the i-th frequency in the spare frequency band, I i is the interference detection data corresponding to the i-th frequency band, I th is the preset interference threshold. The instruction generation unit generates a frequency switching instruction according to the result of the judgment unit, and the switching execution unit performs frequency band switching on the frequency controller according to the frequency switching instruction;

[0037] S142. The preset frequency band storage unit is used to store the spare frequency band information and the corresponding preset interference threshold, and its stored content constitutes the set of spare frequency band parameters where f i is the i-th frequency in the spare frequency band, is the interference threshold corresponding to f i .

[0038] Optionally, the S3 specifically includes:

[0039] S31. The data receiving module receives the temperature data and the interference detection data through the wireless data transmission module, and performs preliminary parsing on the temperature data and the interference detection data by using the time slicing parsing algorithm. The parsing process can be expressed as:

[0040]

[0041] where T rec (t) represents the temperature data received at time t, I rec (t) represents the interference detection data, t j represents the j-th receiving time point, T j and I j respectively represent the temperature data and the interference detection data received at the j-th time, δ(t) is the Dirac function, and M is the number of received data;

[0042] S32. The storage module includes a random access memory and a read-only memory, and is used to store the temperature data and the interference detection data parsed by the data receiving module;

[0043] S33. Data processing module, which includes a digital signal processing unit and a control unit. The digital signal processing unit filters and corrects the data stored in the storage module, and the control unit uniformly formats and logically processes the data.

[0044] The beneficial effects of the present invention are as follows:

[0045] (1) By integrating a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and an adaptive frequency hopping control module in the temperature measurement node, the present invention realizes real-time anti-interference processing during the temperature data acquisition and wireless transmission process; by detecting local electromagnetic interference and automatically switching to a low-interference standby frequency band according to a preset algorithm, it significantly improves the stability of data transmission and the accuracy of temperature measurement, breaking through the limitations of the traditional fixed-frequency system with a limited coverage range and the defect that interference is likely to cause transmission interruption.

[0046] (2) The present invention adopts a variety of modular designs such as multi-stage amplification, band-pass filtering, and digital comparison to finely condition and quantify the signals from each independent interference sensing element; using filtering convolution and multi-channel weighted calculation formulas, it ensures the accurate generation of electromagnetic interference detection data, providing a reliable basis for subsequent frequency switching, thereby realizing the efficient management of multi-region temperature monitoring in a complex environment and overcoming the problems of rough signal processing and insufficient anti-interference ability in the prior art.

[0047] (3) The present invention uniformly stores and digitally processes the temperature data and interference detection data received by the wireless data transmission module through the central processing unit, and adopts processing methods such as time-slice parsing and data filtering and correction to realize the whole-process high-efficiency coordination of data acquisition, storage, and processing; this distributed processing architecture greatly improves the system's requirements for real-time performance and data consistency, breaks through the problems of delay and data inconsistency existing in the traditional centralized processing scheme, and effectively improves the reliability and practicality of the entire wireless temperature measurement system in large-scale Internet of Things applications. Description of the Drawings

[0048] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0049] Figure 1 It is a schematic diagram of the overall structure of a wireless temperature measurement system based on the Internet of Things proposed by the present invention. Detailed Embodiments

[0050] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0051] Reference Figure 1 , a wireless temperature measurement system based on the Internet of Things, comprising the following components:

[0052] S1. At least one temperature measurement node, the temperature measurement node includes a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and an adaptive frequency hopping control module. The temperature sensor is used to measure temperature data, the radio frequency identification module is used to implement node identity identification, the local electromagnetic interference detection module is used to detect the electromagnetic interference level in the area where the node is located in real time and generate interference detection data, and the adaptive frequency hopping control module is used to automatically switch to a low-interference standby frequency band according to the interference detection data;

[0053] S2. A wireless data transmission module, electrically connected to the temperature measurement node, for transmitting temperature data and interference detection data;

[0054] S3. A central processing unit, which receives temperature data and interference detection data through the wireless data transmission module, and stores and processes the temperature data and interference detection data;

[0055] S4. A power supply module, which provides working electrical energy for the temperature measurement node, the wireless data transmission module, and the central processing unit respectively.

[0056] In this embodiment, a multi-source independent power supply mechanism is adopted to provide distributed power supply for the temperature measurement node, the wireless data transmission module and the central processing unit. Among them, the temperature measurement node is encapsulated and powered by an embedded lithium battery module, and a supporting power management unit is used to realize the real-time detection of the battery voltage, discharge rate and remaining power. The wireless data transmission module integrates a solar photovoltaic panel and a backup battery pack to build a dynamically switched dual-channel power supply architecture. When the ambient light is sufficient, it is directly powered by solar energy and charged synchronously. When the light is weak or at night, it automatically switches to battery support to ensure the continuous and stable operation of the high-frequency data transmission process. The central processing unit is connected to an external regulated mains power system, and a UPS uninterruptible power supply module is configured to automatically take over the power supply in case of a sudden power outage of the external power grid and maintain the normal operation of the core processing link. A power status monitoring unit is configured inside the power module to collect the power supply status data of each node through a multi-channel voltage and current sampling interface, and periodically upload it to the central processing unit for unified storage and evaluation. All power supply parameters are normalized after being received and modeled and analyzed in combination with the node working status to construct a node-level power health portrait, improving the system's recognition ability and response accuracy for risks such as abnormal power consumption and power supply interruption, and providing a stable energy guarantee mechanism for the continuous operation and intelligent operation and maintenance of the wireless temperature measurement system in a complex on-site environment.

[0057] In this embodiment, S1 includes the following steps:

[0058] S11. A temperature sensor, which includes a temperature sensing element and an analog-to-digital conversion unit. The temperature sensing element is used to collect the ambient temperature analog signal, and the analog-to-digital conversion unit is used to convert the ambient temperature analog signal into temperature data;

[0059]

[0060] where, T is the temperature data, ADC value is the analog-to-digital conversion output value, n is the resolution of the analog-to-digital conversion unit, representing the number of bits of the analog-to-digital converter (used to quantize and represent the input ambient temperature analog signal within the digital range of 0 to 2 n ―1), V ref is the reference voltage, V offset is the voltage offset of the temperature sensor, and K is the sensor sensitivity coefficient;

[0061] This formula maps the digital value ADC value output by the analog-to-digital conversion unit to the corresponding analog voltage, and then subtracts the offset voltage V offset of the temperature sensor and divides it by the sensitivity coefficient K to realize the process of converting the voltage quantity into the temperature quantity. Among them, ADC value is a dimensionless integer value, 2 n-1 represents the maximum digital output of the analog-to-digital converter, which is dimensionless. After multiplying the ratio of the two by the reference voltage V ref (in volts, V), the analog signal voltage is obtained. After subtracting the bias voltage, it is still in volts. Finally, it is divided by the sensitivity coefficient K (in V / ℃), so that the dimension of the overall expression is converted from volts to degrees Celsius (℃), ensuring the physical dimension consistency and resolvability of this temperature calculation formula.

[0062] S12, a radio frequency identification module, which includes a radio frequency antenna, a signal transceiver unit, and a data processing unit. The radio frequency antenna is used to transmit and receive radio frequency signals. The signal transceiver unit is used to modulate and demodulate the radio frequency signals. The data processing unit is used to generate and analyze the node identity code;

[0063] S13, a local electromagnetic interference detection module, which includes a multi-channel interference sensor, a signal conditioning circuit, and a digital comparison unit. The multi-channel interference sensor respectively collects electromagnetic interference analog signals at different positions in the environment. The signal conditioning circuit amplifies and filters the electromagnetic interference analog signals. The digital comparison unit quantifies the processed electromagnetic interference analog signals to generate interference detection data;

[0064] S14, an adaptive frequency hopping control module, which includes a frequency control module and a preset frequency band storage unit. The frequency control module makes a judgment based on the interference detection data processed by the local electromagnetic interference detection module and the preset spare frequency band information, outputs a frequency switching instruction, and performs a spare frequency band switching.

[0065] In this embodiment, the temperature sensing element in the temperature sensor is deeply integrated with the analog-digital conversion unit, realizing the structured design of the real-time acquisition of the ambient temperature analog signal and the digital conversion process. The temperature sensing element converts the ambient temperature change into a linear analog voltage signal, and then through the high-resolution analog-to-digital conversion module combined with the reference voltage and bias voltage parameters for digital expression, forming standardized temperature data; at the same time, the radio frequency identification module uses a multi-stage radio frequency structure to bind the node identity information with the data transmission process, and through the cooperation of the independent radio frequency antenna, signal modulation unit and data processing unit, realizes the generation and parsing functions of the identity identification; on this basis, the local electromagnetic interference detection module completes the real-time acquisition, amplification and filtering of the interference signal through the multi-channel interference perception mechanism and signal conditioning path, and finally outputs the digital interference characteristics; the adaptive frequency hopping control module judges whether the interference level of the currently used frequency band exceeds the threshold according to the interference detection result, compares it with the pre-set backup frequency band, and outputs a frequency switching instruction to realize the local automatic frequency hopping adjustment. Through the modular hierarchical design and the in-structure closed-loop interference feedback control path, this embodiment not only improves the acquisition accuracy of temperature data and the transmission robustness, but also enhances the system's adaptive anti-interference ability and node identification stability in a strong electromagnetic interference environment, providing a multi-source collaborative functional guarantee and processing basis for subsequent data fusion, frequency hopping control and system stable operation.

[0066] In this embodiment, S12 specifically includes:

[0067] S121. A radio frequency antenna, which adopts a multi-band structure design, has the functions of transmitting and receiving multi-channel signals, and is electrically connected to the signal transceiver unit through a radio frequency matching circuit;

[0068] S122. A signal transceiver unit, which includes a radio frequency modulator, a radio frequency demodulator, a power amplifier and a low noise amplifier. The radio frequency modulator is used to modulate the temperature data into a radio frequency signal, the power amplifier performs power amplification processing on the radio frequency signal output by the radio frequency modulator, the low noise amplifier is used to pre-amplify the low-power external radio frequency signal received by the radio frequency antenna, and the radio frequency demodulator is used to convert the radio frequency signal pre-amplified by the low noise amplifier into a baseband signal;

[0069] S123. A data processing unit, which includes a microprocessor, a storage unit and a communication interface module. The microprocessor is used to digitally process the baseband signal output by the signal transceiver unit, the storage unit is used to store the node identity data and communication protocol parameters, and the communication interface module is used to realize data exchange with other modules of the temperature measurement node;

[0070] S124. The impedance matching between the RF antenna and the signal transceiver unit is achieved through an RF matching circuit. The design of the RF matching circuit is based on the input impedance Z of the RF antenna ant = R ant + jX ant and the output impedance Z of the signal transceiver unit sr = R sr + jX sr for parameter calculation:

[0071]

[0072] where Q is the quality factor of the matching network, ω is the operating angular frequency, L is the value of the matching inductor, C is the value of the matching capacitor, R ant represents the real part of the input impedance of the RF antenna, (j) represents the imaginary unit, which satisfies j 2 = -1, X ant represents the imaginary part of the input impedance of the RF antenna, R sr represents the real part of the output impedance of the signal transceiver unit, X sr represents the imaginary part of the output impedance of the signal transceiver unit.

[0073] This formula realizes the impedance matching between the input impedance of the RF antenna and the output impedance of the signal transceiver unit by calculating the quality factor Q, the matching inductor L, and the matching capacitor C in the impedance matching network. Among them, R ant and R sr represent the real parts of the impedances of the antenna and the transceiver unit, with the unit of ohm (Ω). Their ratio is dimensionless, so the quality factor Q is also a dimensionless quantity; for the matching inductor , ω is the operating angular frequency, with the unit of radian per second (rad / s), and R ant has the unit of ohm, so the unit of L is henry (H); for the matching capacitor , the dimension of the denominator is (rad / s)·Ω·(dimensionless), so the unit of C is farad (F). This formula maintains dimensional consistency, ensuring the feasibility and engineering operability of the matching network parameters in physical implementation.

[0074] This implementation combines a multi-channel RFID module with a high-precision RF modulation and demodulation system to achieve a deep integration of node identity recognition and wireless temperature data transmission. The system adopts an independent multi-band antenna structure to support the reception and transmission of RF signals at multiple frequencies, and cooperates with the power amplifier and low-noise amplifier to perform bidirectional gain adjustment on the uplink and downlink signals, significantly improving the effectiveness and anti-interference ability of long-distance data transmission in the communication link; at the same time, the signal transceiver path uses the RF matching circuit to perform impedance matching design between the RF antenna and the transceiver unit, and calculates the quality factor, matching inductance and capacitance parameters based on the complex form of the RF input impedance and output impedance to ensure accurate energy coupling within the target frequency band, effectively reducing the signal reflection and power loss caused by impedance mismatch; in terms of data signal processing, the system completes key steps such as baseband signal analysis, identity information encoding, and protocol structure encapsulation through the microprocessor and communication interface module, enhancing the data processing module's decoding and transmission support capabilities for high-frequency data. Through this structural design, this implementation not only realizes the separation processing of multi-node identity identification and data channels, but also significantly improves the communication robustness and node identification accuracy of the system in complex IoT application scenarios, and builds a stable, precise and scalable communication and identification architecture for the wireless temperature measurement system.

[0075] In this implementation manner, the S13 specifically includes:

[0076] S131, a multi-channel interference sensor, wherein the multi-channel interference sensor is composed of a plurality of independently arranged interference sensor elements, each interference sensor element is used to collect an electromagnetic interference analog signal in the area where it is located;

[0077] S132, signal conditioning circuit, the signal conditioning circuit includes a multi-stage amplification module and a bandpass filtering module, wherein the multi-stage amplification module is used to linearly gain amplify the low-amplitude analog signal output by each interference sensor element, and the bandpass filtering module is used to suppress non-target frequency band signals, and the processing process satisfies the following filter convolution relationship:

[0078]

[0079] Among them, V in (t) is the input electromagnetic interference analog signal, h(t) is the unit impulse response of the bandpass filter, V out (t) is the output filtered signal;

[0080] This formula is obtained by inputting the electromagnetic interference simulation signal V in (t) is convolved with the unit impulse response function h(t) of the bandpass filter to obtain the filtered output signal V out (t), essentially reflects the response characteristics of the filter in the linear time-invariant system to the input signal. In the formula, Vin (t) and V out (t) are both voltage signals with the unit of volt (V), h(t) is the unit impulse response with the dimension of per second (1 / s), which is used to maintain the consistency of the integration result in the time domain. The product h(t−τ)·V on the right side of the convolution integral in (τ) has the unit of volt per second (V / s), and it is restored to volt (V) after integrating with respect to the time variable τ, which is consistent with the unit of the output signal V out (t). The overall expression is dimensionally consistent, ensuring the physical realizability of the filtering system and the interpretability of signal processing.

[0081] S133, a digital comparison unit, which includes an analog-to-digital conversion module and an interference discrimination processor. The analog-to-digital conversion module is used to convert the conditioned analog signal into a discrete digital signal. The interference discrimination processor performs weighted calculation within a time window and threshold comparison based on the digital signal values of multiple channels:

[0082]

[0083] where, I detected is the generated interference detection data, N is the number of channels, w i is the weight factor of the i-th channel, is the output value of the analog-to-digital converter of the i-th channel, n is the resolution of the analog-to-digital converter, V ref_max and V ref_min are the upper and lower limits of the reference voltage.

[0084] This formula performs normalization on the analog-to-digital conversion output values of multiple channels and then performs weighted summation with the corresponding weight factor w i to obtain the digitized interference detection result I detected . Among them, is the dimensionless integer value output by the analog-to-digital converter, and the denominator 2 n −1 represents the maximum digital output value, which is also dimensionless. The ratio of the two is the unit interval normalization coefficient; multiplying by (V ref_max −V ref_min ) restores it to the analog voltage amplitude with the unit of volt (V), and then adding V ref_min (V) represents the final corresponding channel analog input voltage, still in volts. Since the weight factor w i is a dimensionless coefficient, the finally obtained I detected has the dimension of volt (V), representing the equivalent voltage amplitude of the overall interference intensity, with a clear electrical physical meaning. The parameters of this formula are highly consistent in dimension, ensuring the accuracy and comparability of the calculation of interference detection data.

[0085] This embodiment integrates the design of multi-channel interference perception, analog signal conditioning, and digital discrimination mechanisms, achieving real-time acquisition, filtering, and digital output of the electromagnetic interference intensity in the area where the node is located. The system constructs an electromagnetic perception network for different directions and frequency bands by arranging independent interference sensing elements at multiple spatial positions, ensuring comprehensive coverage of local interference sources in complex environments. The signal conditioning circuit adopts a linkage design of a multi-stage amplification module and a band-pass filtering structure, which can not only linearly amplify low-amplitude interference analog signals but also dynamically suppress signals in non-target frequency bands, enhancing the system's ability to extract electromagnetic disturbances in the target frequency range. On this basis, the digital comparison unit converts the analog signal into a high-precision digital quantity through an analog-to-digital conversion module, and uses a weighted summation and threshold comparison mechanism to extract the interference feature intensity index within a time window to form an interference detection result. The formulaic processing combines channel weights, adaptive voltage mapping, and reference voltage range parameters, which not only improves the detection accuracy but also enhances the system's adaptability to different interference forms. This embodiment constructs a three-in-one interference detection framework of "spatial perception - analog conditioning - digital discrimination", significantly improving the recognition ability of the temperature measurement node for strong interference areas and the response efficiency of anti-interference switching, supporting the stable operation of the system in complex environments such as industry, high voltage, and electromechanics.

[0086] In this embodiment, S14 specifically includes:

[0087] S141. The frequency control module in the adaptive frequency hopping control module. The frequency control module includes a judgment unit, an instruction generation unit, and a switching execution unit. The judgment unit receives the interference detection data generated after being processed by the local electromagnetic interference detection module and the spare frequency band information stored in the preset frequency band storage unit, and compares the interference levels of each spare frequency band:

[0088]

[0089] where, f sel is the selected spare frequency band frequency, F is the set of preset spare frequency bands, f i is the i-th frequency in the spare frequency band, I i is the interference detection data corresponding to the i-th frequency band, I th is the preset interference threshold. The instruction generation unit generates a frequency switching instruction according to the result of the judgment unit, and the switching execution unit performs frequency band switching on the frequency controller according to this instruction;

[0090] This formula screens out the frequency bands with interference intensity I i less than the preset interference threshold I th from all the preset spare frequency band sets F, and selects the one with the smallest frequency f selAs the target frequency of the current frequency hopping. In the formula, f i and f sel are both frequency parameters, with the unit of Hertz (Hz); the interference detection value I i and the threshold I th both represent the voltage amplitude or equivalent intensity corresponding to the interference, with the unit of Volt (V) or an optional dimensionless normalized value, which is specifically determined by the system implementation method. Since the judgment condition only involves numerical comparison, and the finally output f sel maintains the same physical dimension as the input frequency f i , the overall formula has dimensional consistency in the frequency selection logic and is applicable to the adaptive determination and instruction generation of the low-interference frequency band in the frequency hopping control module.

[0091] S142. A preset frequency band storage unit, which is used to store the spare frequency band information and the corresponding preset interference thresholds. The stored content constitutes a set of spare frequency band parameters, denoted as F = {(f i , I thi )}, where f i is the i-th frequency in the spare frequency band, and I thi is the interference threshold corresponding to f i .

[0092] In the temperature measurement node, the temperature sensor uses a high-precision temperature sensing element. The output analog temperature signal is converted into digital temperature data by the analog-to-digital conversion unit and transmitted to the subsequent processing module through the internal data bus; the radio frequency identification module is integrated in the temperature measurement node, using a built-in radio frequency antenna and a radio frequency matching circuit, and realizes node identity identification through modulation, demodulation, and digital signal processing to ensure that each node has a unique identifier in the entire system; the local electromagnetic interference detection module is composed of multiple independently arranged interference sensing elements. Each sensing element collects the electromagnetic interference analog signal in the environment at different spatial positions. These signals are amplified in multiple stages and band-pass filtered by a dedicated signal conditioning circuit, and then converted into digital interference detection data by the analog-to-digital conversion module; the adaptive frequency hopping control module is equipped with a frequency control logic. By receiving the interference detection data generated by the above local electromagnetic interference detection module, it automatically calculates the current best spare frequency band using a preset frequency judgment algorithm and outputs a frequency switching instruction to drive the wireless data transmission module to switch to the low-interference frequency band in real time.

[0093] In this embodiment, a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and an adaptive frequency hopping control module are integrated into the temperature measurement node. By collecting and processing temperature data and local electromagnetic interference data in real time, the stable acquisition and transmission of temperature data in a complex electromagnetic environment are ensured. When the node detects a high-interference signal, it can automatically switch to a low-interference standby frequency band, effectively improving the overall monitoring accuracy and data transmission reliability of the system, providing a solid technical guarantee for large-scale Internet of Things temperature monitoring systems, and thus enhancing the real-time performance of temperature monitoring and the anti-interference performance of the system.

[0094] In this embodiment, S3 includes the following steps:

[0095] S31. A data receiving module. The data receiving module receives temperature data and interference detection data through the wireless data transmission module, and uses a time-slice parsing algorithm to preliminarily parse the temperature data and interference detection data. The parsing process can be expressed as:

[0096]

[0097] Among them, T rec (t) represents the temperature data received at time t, I rec (t) represents the interference detection data, t j represents the time point of the jth reception, T j and I j respectively represent the temperature data and interference detection data received at the jth time, δ(t) is the Dirac function, and M is the number of received data;

[0098] This formula constructs the continuous-time temperature reception signal T j by performing weighted summation of the Dirac function δ(t - t j on the temperature data T j and the interference detection data I j ) received at discrete time points t rec (t) and the interference detection signal I rec (t), realizing the structured reconstruction from discrete data to a time function. In the formula, T j represents the temperature data received at the jth time, with the unit of degree Celsius (°C); I j represents the interference detection data received at the jth time, with the unit of volt (V); δ(t - t j ) is the Dirac function, with the unit of reciprocal time (1 / s), which is used to locate the sampling moment during the summation process. The finally obtained T rec (t) and I rec(t) represents the temperature function value and interference signal function value at any moment t, with the units of °C and V respectively, which are consistent with the original data. This formula has good consistency and separability in dimension and is applicable to the synchronous modeling and time-series processing analysis of temperature and interference data by the central processing unit.

[0099] S32. A storage module, which includes a random access memory and a read-only memory, and is used to store the temperature data and interference detection data parsed by the data receiving module. The interference detection data includes node numbers, acquisition times, interference signal voltage values of each channel, weighted calculated interference intensity values, and corresponding interference levels and frequency hopping suggestion identifiers.

[0100] S33. A data processing module, which includes a digital signal processing unit and a control unit. The digital signal processing unit filters and corrects the data stored in the storage module, and the control unit uniformly formats and logically processes the data.

[0101] This embodiment centrally manages the outputs of the data receiving, storage, and processing modules in the central processing unit. Through the real-time acquisition, filtering, correction, and formatting of temperature data and interference detection data, it realizes the efficient integration and time-series dynamic analysis of data. It can not only timely reflect the current states of each temperature measurement node but also capture the trend of data evolution over time, improving the real-time performance and accuracy of data processing, integrating the advantages of multi-node data centralized management and intelligent data processing, and providing efficient and stable digital support for large-scale Internet of Things temperature monitoring systems.

[0102] Example:

[0103] A specific embodiment of the present invention is given below to illustrate the application effect of the present invention in temperature monitoring under a complex electromagnetic interference environment. In November 2024, in a large electronic manufacturing factory in Suzhou, Jiangsu Province, due to the extensive use of high-power equipment and welding processes during the production process, the on-site electromagnetic interference was relatively serious. At the same time, the temperature distribution in the workshop was uneven and local hot spots occurred frequently. In this environment, traditional temperature monitoring systems often had problems such as data loss and inaccurate measurement due to signal transmission interference, seriously affecting production safety and equipment operation. To solve this problem, the factory introduced the wireless temperature measurement system based on the Internet of Things of the present invention, deployed 50 temperature measurement nodes in the factory area, each node integrated a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and an adaptive frequency hopping control module, used the wireless data transmission module to send the real-time acquired temperature data and interference detection data to the central processing unit, and the central processing unit uniformly stored, parsed, and processed the relevant data. The overall system adopted a distributed power supply design to ensure long-term stable operation.

[0104] In this scenario, the applications of the system are mainly reflected in the following aspects: First, the temperature measurement nodes use high-precision temperature sensors to monitor the ambient temperature of each area in the workshop in real time. The data conversion process undergoes multiple levels of analog-to-digital conversion and calibration to ensure that each node can provide accurate temperature data. Second, the radio frequency identification module integrated inside each node ensures that the nodes have unique identity identifiers during large-scale deployment, facilitating the central processing unit to distinguish and integrate data from different areas. At the same time, the local electromagnetic interference detection module uses multiple interference sensing elements arranged at different positions to collect high-frequency electromagnetic noise signals in the workshop in real time. After amplification, filtering, and digital comparison processing, interference detection data is generated, providing an accurate basis for the adaptive frequency hopping control module. The adaptive frequency hopping control module automatically calculates the current best standby frequency band based on the interference detection data and the pre-set standby frequency band information, and outputs a frequency switching instruction to ensure that wireless data transmission remains stable even when the electromagnetic environment changes violently, thus avoiding the loss or incorrect transmission of temperature data caused by interference. The central processing unit receives the temperature data and interference detection data sent by each node through the wireless data transmission module, preliminarily analyzes the data using the time-slice parsing algorithm, and after hierarchical storage in the storage module, filters, corrects, and converts the format of the data through the digital signal processing module. Finally, a complete temperature monitoring record is formed and presented in real-time visualization on the monitoring platform, providing intuitive data reference and warning information for on-site management personnel.

[0105] In this embodiment, the system has been running continuously since November 1, 2024. After 24 hours of uninterrupted monitoring, the following data records were obtained during critical periods (see the table below). Table 1 shows the data acquisition results of the wireless temperature measurement system, recording the temperature data, interference detection data, and the instruction information for the system to automatically switch frequency bands when interference is high at different times. According to the data in the table, the temperature data of the traditional system in the same area fluctuates greatly and there are data interruptions in many places. However, after the system of the present invention automatically switches to the standby low-interference frequency band during high-interference periods, the temperature data remains stable, with smooth and continuous numerical changes. The record shows that around 14:30 on November 3, some areas of the factory area were affected by strong electromagnetic interference from large welding equipment, and the peak value of the interference detection data reached 850 mV. At this time, the system quickly calculated the frequency of the standby frequency band and output a frequency switching instruction. Then, the temperature measurement nodes resumed normal data transmission, and their temperature data fluctuated around 35°C. The data stability and continuity are better than those of the traditional system.

[0106] In addition, during the continuous operation of the system, when comparing the data transmission stability of the traditional fixed-frequency wireless temperature measurement system, the temperature data loss rate of this system is controlled within 0.2% within 12 hours of continuous monitoring, while the loss rate of the traditional system is as high as over 5%, and the data fluctuation range is reduced by nearly 60%. After the system receives the temperature data from each sensing node, through the digital filtering and data correction algorithms built into the central processing unit, the accuracy of data analysis is further improved, and its processing error is controlled within ±0.3°C, far lower than the error range of the traditional system (about ±1.5°C). At the same time, when dealing with sudden high electromagnetic interference, the system completes the calculation and execution of the frequency switching instruction within 2 seconds, achieving a rapid switch from the interference peak period to stable data transmission. This response speed greatly reduces the safety risks caused by abnormal temperature data in the actual production environment.

[0107] At the monitoring site of the chemical plant, the central processing unit and the remote monitoring center achieve data sharing through a dedicated data interface. Managers can monitor the status of each temperature measurement node in the plant area in real time and adjust the production process and safety measures in a timely manner. After the system is deployed, through two consecutive weeks of on-site testing, the data shows that high-precision data collection and stable transmission can be maintained under different environmental temperatures and different electromagnetic interference intensities. The on-site temperature monitoring accuracy rate reaches 98.7%, and the data transmission delay is less than 1 second, greatly improving the efficiency of on-site safety management and equipment maintenance. During the testing period, more than 1,200,000 pieces of data were collected. After the data automatically processed and stored by the system was statistically analyzed, the average error was less than 0.28°C, and the standard deviation was only 0.15°C, fully demonstrating the stability and efficiency of the system of the present invention in harsh environments.

[0108] In summary, through the reasonable configuration of the temperature measurement node, wireless data transmission module, central processing unit, and power supply module in a complex electromagnetic interference environment in this embodiment, accurate collection, real-time storage, and intelligent processing of temperature data are realized. The function of the system automatically switching to the standby frequency band effectively solves the problems of data interruption and unstable temperature measurement caused by electromagnetic interference in the traditional wireless temperature measurement system, providing an efficient, reliable, and real-time intelligent management platform for large-scale Internet of Things temperature monitoring applications.

[0109] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A wireless temperature measurement system based on the Internet of Things, characterized in that, The system includes: S1. At least one temperature measurement node, which includes a temperature sensor, a radio frequency identification module, a local electromagnetic interference detection module, and an adaptive frequency hopping control module. The temperature sensor is used to measure temperature data, the radio frequency identification module is used to implement node identity identification, the local electromagnetic interference detection module is used to detect the electromagnetic interference level in the node's area in real time and generate interference detection data, and the adaptive frequency hopping control module is used to automatically switch to a low-interference standby frequency band according to the interference detection data; S2. A wireless data transmission module, electrically connected to the temperature measurement node, for transmitting temperature data and interference detection data; S3. A central processing unit, which receives temperature data and interference detection data through the wireless data transmission module, and stores and processes the temperature data and interference detection data; S4. A power supply module, which provides working electrical energy for the temperature measurement node, the wireless data transmission module, and the central processing unit respectively.

2. The wireless temperature measurement system based on the Internet of Things according to claim 1, characterized in that The specific content of S1 includes: S11. A temperature sensor, which includes a temperature sensing element and an analog-to-digital conversion unit. The temperature sensing element is used to collect the ambient temperature analog signal, and the analog-to-digital conversion unit is used to convert the ambient temperature analog signal into temperature data; Among them, T is the temperature data, and ADC value is the analog-to-digital conversion output value, n is the resolution of the analog-digital conversion unit, representing the number of bits of the analog-to-digital converter, V ref is the reference voltage, V offset is the voltage bias of the temperature sensor, and K is the sensor sensitivity coefficient; S12. A radio frequency identification module, which includes a radio frequency antenna, a signal transceiver unit, and a data processing unit. The radio frequency antenna is used to transmit and receive radio frequency signals, the signal transceiver unit is used to modulate and demodulate the radio frequency signals, and the data processing unit is used to generate and parse the node identity code; S13. A local electromagnetic interference detection module, which includes a multi-channel interference sensor, a signal conditioning circuit, and a digital comparison unit. The multi-channel interference sensor respectively collects the electromagnetic interference analog signals at different positions in the environment, the signal conditioning circuit amplifies and filters the electromagnetic interference analog signals, and the digital comparison unit quantifies the processed electromagnetic interference analog signals to generate interference detection data; S14. An adaptive frequency hopping control module, which includes a frequency control module and a preset frequency band storage unit. The frequency control module makes a judgment based on the interference detection data processed by the local electromagnetic interference detection module and the preset standby frequency band information, outputs a frequency switching instruction, and performs standby frequency band switching.

3. The wireless temperature measurement system based on the Internet of Things according to claim 2, characterized in that, The specific content of S12 includes: S121. A radio frequency antenna, which adopts a multi-band structure design, has the function of transmitting and receiving multi-channel signals, and is electrically connected to the signal transceiver unit through a radio frequency matching circuit; S122. A signal transceiver unit, which includes a radio frequency modulator, a radio frequency demodulator, a power amplifier, and a low-noise amplifier. The radio frequency modulator is used to modulate the temperature data into a radio frequency signal, the power amplifier amplifies the power of the radio frequency signal output by the radio frequency modulator, the low-noise amplifier is used to pre-amplify the low-power external radio frequency signal received by the radio frequency antenna, and the radio frequency demodulator is used to convert the radio frequency signal pre-amplified by the low-noise amplifier into a baseband signal; S123. Data processing unit, which includes a microprocessor, a storage unit, and a communication interface module. The microprocessor is used to digitally process the baseband signal output by the signal transceiver unit. The storage unit is used to store node identity data and communication protocol parameters. The communication interface module is used to realize data exchange with other modules of the temperature measurement node. Between the S124, radio frequency antenna and the signal transceiver unit, impedance matching is achieved through a radio frequency matching circuit. The design of the radio frequency matching circuit is based on the input impedance Z of the radio frequency antenna ant = R ant + jX ant and the output impedance Z of the signal transceiver unit sr = R sr + jX sr for parameter calculation: Among them, Q is the quality factor of the matching network, ω is the operating angular frequency, L is the value of the matching inductor, C is the value of the matching capacitor, and R ant represents the real part of the input impedance of the RF antenna, and (j) represents the imaginary unit, which satisfies j 2 = -1, and X ant represents the imaginary part of the input impedance of the RF antenna, and R sr represents the real part of the output impedance of the signal transceiver unit, and X sr represents the imaginary part of the output impedance of the signal transceiver unit.

4. The wireless temperature measurement system based on the Internet of Things according to claim 2, wherein The S13 specifically includes: S131. Multi-channel interference sensor, which is composed of multiple independently arranged interference sensing elements. Each interference sensing element is used to collect the electromagnetic interference analog signal in its area. S132. Signal conditioning circuit, which includes a multi-stage amplification module and a band-pass filtering module. The multi-stage amplification module is used to linearly amplify the low-amplitude electromagnetic interference analog signal output by each interference sensing element. The band-pass filtering module is used to suppress signals in non-target frequency bands, and its processing process satisfies the following filtering convolution relationship: Among them, V in (t) is the input electromagnetic interference simulation signal, h(t−τ) is the unit impulse response of the band-pass filter, and V out (t) is the output filtered signal; S133. Digital comparison unit, which includes an analog-to-digital conversion module and an interference discrimination processor. The analog-to-digital conversion module is used to convert the conditioned electromagnetic interference analog signal into a discrete digital signal. The interference discrimination processor performs weighted calculation within a time window and threshold comparison based on the digital signal values of multiple channels: Among them, I detected is the generated interference detection data, N is the number of channels, and w i is the weight factor of the i-th channel, is the output value of the analog-to-digital converter of the i-th channel, n is the resolution of the analog-to-digital converter, V ref_max and V ref_min are the upper and lower limits of the reference voltage.

5. A wireless temperature measurement system based on the Internet of Things according to claim 1, characterized in that, The S14 specifically includes: S141. Frequency control module in the adaptive frequency hopping control module. The frequency control module includes a judgment unit, an instruction generation unit, and a switching execution unit. The judgment unit receives the interference detection data generated after being processed by the local electromagnetic interference detection module and the spare frequency band information stored in the preset frequency band storage unit, and compares the interference levels of each spare frequency band information: Among them, f sel is the selected standby frequency band information, F is the preset set of standby frequency bands, and f i is the i-th frequency in the standby frequency band, and I i is the interference detection data corresponding to the i-th frequency band, and I th is the preset interference threshold. The instruction generation unit generates a frequency switching instruction according to the result of the judgment unit, and the switching execution unit performs a frequency band switching on the frequency controller according to the frequency switching instruction; S142. A preset frequency band storage unit which is used to store spare frequency band information and corresponding preset interference thresholds, and the stored content constitutes a spare frequency band parameter set F = {(f i , I thi )}, where f i is the i-th frequency in the spare frequency band, and I thi is the interference threshold corresponding to f i .

6. The wireless temperature measurement system based on the Internet of Things according to claim 1, characterized in that The S3 specifically includes: S31. Data receiving module, which receives temperature data and interference detection data through the wireless data transmission module, and uses a time-slice parsing algorithm to preliminarily parse the temperature data and interference detection data. Its parsing process can be expressed as: Among them, T rec (t) represents the temperature data received at time t, I rec (t) represents the interference detection data, t j represents the time point of the j-th reception, T j and I j respectively represent the temperature data and the interference detection data received at the j-th time, δ(t) is the Dirac function, and M is the number of times of receiving data; S32. Storage module, which includes a random access memory and a read-only memory, and is used to store the temperature data and interference detection data parsed by the data receiving module. S33. Data processing module, which includes a digital signal processing unit and a control unit. The digital signal processing unit filters and corrects the data stored in the storage module, and the control unit uniformly formats and logically processes the data.

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