Portable wi-fi based thermal comfort level sensing device

Abstract

The invention provides a portable Wi-Fi (Wireless Fidelity) thermal comfort sensing device, which comprises a shell, a wireless communication module, a wireless communication module, a wireless communication module, a wireless communication module, a wireless communication module, a wireless communication module and a wireless communication module, the environment sensor array is integrated in the upper shell; the environment sensor array at least comprises an air dry-bulb temperature sensor; a humidity sensor; a black ball thermometer; an ultrasonic anemometer; the control unit is arranged in the base; the control unit is configured to periodically acquire measurement data from the environment sensor array; calculating the average heat radiation temperature; receiving personal parameters (including a new dust metabolism rate, a clothes and furniture heat insulation law and the like) of a user; calculating a predicted average voting (PMV) value; uploading the measurement data and the PMV value obtained by calculation to a remote server; according to the technical scheme, the defects that in the prior art, parameter measurement of thermal comfort monitoring equipment is incomplete, personal factors cannot be integrated, deployment is not flexible, and data interaction is poor are overcome.

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202610419801.4 (22) Application Date 2026.04.01 (71) Applicant: Lai Fung Technology Research Co., Ltd. Address: 7 / F, Southeast Industrial Building, 611-619 Castle Peak Road, Tsuen Wan, New Territories, Hong Kong, China (72) Inventors: Su Tingbi, Luo Weijian, Liu Tianrong (74) Patent Agency: Beijing Xiudian Patent Agency Co., Ltd. 11424 Patent Attorney: Yang Fangcheng (51) Int.Cl. G01W 1 / 02 (2006.01) G01D 21 / 02 (2006.01) H04W 4 / 38 (2018.01) (54) Invention Title: A Portable Wi-Fi Thermal Comfort Sensing Device (57) Abstract: This application provides a portable Wi-Fi thermal comfort sensing device, which includes: a housing, the housing including an upper housing and a base; an environmental sensor array integrated in the upper housing, the environmental sensor array including at least: an air dry-bulb temperature sensor; a humidity sensor; a black bulb thermometer; an ultrasonic anemometer; and a control unit disposed in the base, the control unit being configured to: periodically collect measurement data from the environmental sensor array; calculate the average thermal radiation temperature; receive user personal parameters (including new dust metabolism rate and clothing and furniture thermal insulation law, etc.); calculate the predicted average vote PMV value; and upload the measurement data and the calculated PMV value to a remote server; In the above technical solution, the defects of the prior art thermal comfort monitoring device, such as incomplete parameter measurement, inability to integrate personal factors, inflexible deployment, and poor data interactivity, are overcome. Claims 3 pages, Description 15 pages, Drawings 1 page, CN 122239195 A 2026.06.19 CN 1 22 23 91 95 A 1. A portable Wi-Fi thermal comfort sensing device, characterized in that it comprises: a housing, the housing including an upper housing and a base; an environmental sensor array integrated in the upper housing, the environmental sensor array including at least: an air temperature sensor for measuring dry-bulb temperature ta; a humidity sensor for measuring relative humidity RH; a black bulb thermometer for measuring black bulb temperature tg; an ultrasonic anemometer for measuring low air velocity var; a control unit disposed in the base, wherein the control unit is configured to: periodically acquire measurement data from the environmental sensor array; calculate an average thermal radiation temperature tr based on the black bulb temperature tg, the air temperature ta, and the air velocity var; receive user personal parameters, the personal parameters including at least metabolic rate M and clothing thermal resistance Icl; and based on the air dry-bulb temperature ta, the average thermal radiation temperature tr, the relative humidity RH, and the air dry-bulb temperature ta...The water vapor partial pressure pa derived from ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl are used to calculate the predicted average vote PMV value based on a pre-stored thermal comfort model; the measured data and the calculated PMV value are uploaded to a remote server. 2. The portable Wi-Fi thermal comfort sensing device according to claim 1, wherein the control unit includes a microcontroller and a Wi-Fi communication module. 3. The portable Wi-Fi thermal comfort sensing device according to claim 2, characterized in that the microcontroller comprises: a data acquisition module for periodically acquiring measurement data from the environmental sensor array; an average radiant temperature calculation module for calculating the average radiant temperature tr based on the black bulb temperature tg, the dry bulb temperature ta, and the air velocity var; a personal parameter receiving module for receiving user personal parameters, the personal parameters including at least metabolic rate M and clothing thermal resistance Icl; an average vote PMV value calculation module for calculating a predicted average vote PMV value based on the dry bulb temperature ta, the average radiant temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and the air temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, according to a pre-stored thermal comfort model; finding the saturated water vapor pressure ps from a table using ta, and then calculating pa = (RH / 100) ∙ ps; and a data upload module for uploading the measurement data and the calculated PMV value to a remote server via the Wi-Fi communication module. 4. The portable Wi-Fi thermal comfort sensing device according to claim 3, wherein the microcontroller further comprises: a prediction module, used to further calculate the predicted percentage of dissatisfaction (PPD) and / or operating temperature (tO) based on the calculated PMV value. 5. The portable Wi-Fi thermal comfort sensing device according to claim 4, wherein the environmental sensor array further comprises a carbon dioxide sensor for measuring the ambient CO2 concentration. 6. The portable Wi-Fi thermal comfort sensing device according to claim 5, wherein the black sphere thermometer comprises a hollow sphere coated with a high emissivity coating and a temperature probe placed at the center of the sphere. 7. The portable Wi-Fi thermal comfort sensing device according to claim 6, wherein when the air velocity var ≤ 1 m / s, the formula for calculating the average radiant temperature tr is: ; when the air velocity var > 1 m / s, the formula for calculating the average radiant temperature tr is: ; where ; is the diameter of the hollow sphere. 8. The portable Wi-Fi thermal comfort sensing device according to claim 7, wherein the formula for calculating the predicted average vote PMV value is: ; ; ; ; ; ;Wherein, W is the work done by the party at that time, which is generally zero in the office; According to the above equation, tcl is obtained through iteration: ; ; ; ; ; ; ; ; Wherein, is the initial value; Claims 2 / 3 Page 3 CN 122239195 A The condition for the iteration to end is: . 9. The portable Wi-Fi thermal comfort sensing device according to claim 8, wherein the calculation formula for the predicted percentage of dissatisfaction PPD is: . 10. The portable Wi-Fi thermal comfort sensing device according to claim 9, wherein the calculation formula for the operating temperature tO is: ; Wherein, A is a variable. Claims 3 / 3 Page 4 CN 122239195 A A portable Wi-Fi thermal comfort sensing device Technical Field

[0001] This application relates to the cross-technical fields of environmental monitoring, Internet of Things and ergonomics, and particularly to a portable Wi-Fi thermal comfort sensing device. Background Art

[0002] Thermal comfort is a key environmental factor affecting human health, cognitive function, work efficiency and quality of life. In professional environments, deviations from thermal neutrality can significantly impair attention, decision-making ability, and productivity, leading to increased human error. In residential and sleep environments, thermal discomfort can disrupt circadian rhythms, affecting sleep quality and physical recovery. Therefore, creating and maintaining a suitable thermal environment has become one of the core objectives of modern building design and operation.

[0003] Internationally, the assessment of thermal comfort mainly follows two standards: the American ASHRAE Standard 55 "Human Living Thermal Environment Conditions" and the International Organization for Standardization ISO 7730 "Ergonomics of Thermal Environments—Analysis, determination, and interpretation of thermal comfort using PMV and PPD indices and local thermal comfort standards". These standards clearly state that human thermal sensation is expressed as the predicted average vote PMV and the resulting percentage of dissatisfaction (PPD) depends on six core parameters: four environmental parameters (air dry-bulb temperature ta, mean radiant temperature tr, relative humidity RH or water vapor partial pressure pa, air velocity var) and two personal parameters (human metabolic rate M, clothing thermal resistance Icl). The PMV model integrates these six parameters into a scalar ranging from -3°C to +3°C using complex heat transfer equations, while PPD quantitatively represents the proportion of people who are dissatisfied with a given environment.

[0004] Although the PMV-PPD model is widely accepted in theory, its comprehensive application faces significant challenges in the actual continuous verification of building performance and green building certification practices. Current mainstream green building certification systems, such as LEED Energy & Environmental Design Pioneer and WELL Building Standard, all require "thermal comfort monitoring" in the "Indoor Environmental Quality" or "Comfort" categories. For example, WELL v2Clause T06 aims to ensure that the thermal environment meets the needs of residents through continuous monitoring. However, existing market technologies have serious limitations:

[0005] Incomplete parameter measurement: Most so-called "thermal comfort monitors" or indoor environmental monitoring stations on the market can only measure air temperature and humidity to meet the minimum requirements of LEED, and cannot measure mean radiant temperature (TR) and air velocity (var), two key parameters that have an equal or even greater impact on thermal balance. Mean radiant temperature characterizes the effect of the surface temperature of surrounding walls, windows, equipment, etc., on radiant heat transfer to the human body, and is crucial in the presence of cold windows, radiant heating / cooling panels, or strong sunlight. Air velocity directly affects convective heat loss and skin evaporation. Ignoring these two parameters leads to distorted PMV calculations, and the monitoring results lose scientific meaning, failing to provide a reliable basis for precise environmental control.

[0006] Lack of personal parameter input: Most existing devices are fixed-installation unattended sensors, which cannot conveniently acquire or integrate personal parameters of users at specific locations, such as metabolic rate (M) and clothing thermal resistance (Icl). This results in calculated PMV values ​​based on standard assumptions such as sitting still and wearing standard clothing, which cannot reflect the actual thermal sensation of individuals in real-world scenarios, limiting the personalization and accuracy of the assessment.

[0007] Inflexible deployment and data silos: Environmental sensors in traditional building management systems (BMS) are usually fixed installations with wired connections, resulting in high deployment costs and poor flexibility. They are difficult to deploy quickly in areas where spatial functions change or where key monitoring is needed, such as workstations, hospital beds, and classroom seats. Moreover, data is often confined to the BMS and is difficult to interact directly with mobile applications, cloud platforms, and users. Manual 1 / 15 pages 5 CN 122239195 A

[0008] Unable to meet future standard evolution requirements: With the increasing demand for healthy buildings and precise environmental control, green building standards are expected to further increase the requirements for thermal comfort monitoring, shifting from monitoring only temperature and humidity to requiring complete continuous PMV monitoring. Existing technical solutions cannot meet this forward-looking requirement.

[0009] This application provides a portable Wi-Fi thermal comfort sensing device to overcome the shortcomings of existing thermal comfort monitoring devices, such as incomplete parameter measurement, inability to integrate personal factors, inflexible deployment, and poor data interactivity.

[0010] This application provides a portable Wi-Fi thermal comfort sensing device, comprising:

[0011] a housing, the housing including an upper housing and a base;

[0012] an environmental sensor array integrated into the upper housing, the environmental sensor array including at least:

[0013] an air temperature sensor for measuring the dry-bulb temperature ta;

[0014] a humidity sensor for measuring the relative humidity RH;

[0015] a black bulb thermometer for measuring the black bulb temperature tg;

[0016] an ultrasonic anemometer for measuring the air velocity var;

[0017] A control unit disposed within the base is configured to:

[0018] periodically acquire measurement data from the environmental sensor array;

[0019] calculate the average radiant temperature tr based on the dry-bulb temperature tg, air temperature ta, and air velocity var;

[0020] receive user personal parameters, the personal parameters including at least metabolic rate M and clothing thermal resistance Icl;

[0021] calculate a predicted average vote PMV value based on the dry-bulb temperature ta, the average radiant temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and air temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, according to a pre-stored thermal comfort model;

[0022] upload the measurement data and the calculated PMV value to a remote server.

[0023] In the above technical solution, a housing is provided, comprising an upper housing and a base; an environmental sensor array is integrated within the upper housing, the environmental sensor array including at least: an air dry-bulb temperature sensor for measuring air temperature ta; a humidity sensor for measuring relative humidity RH; a black-bulb thermometer for measuring black-bulb temperature tg; and an ultrasonic anemometer for measuring air velocity var; and a control unit disposed within the base, wherein the control unit is configured to: periodically acquire measurement data from the environmental sensor array; and calculate average radiation based on earth temperature tg, air temperature ta, and air velocity var. Temperature tr; Receive user personal parameters, which include at least metabolic rate M and clothing thermal resistance Icl; Based on the air temperature ta, the average radiant temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and air temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, calculate the predicted average vote PMV value according to the pre-stored thermal comfort model; Upload the measured data and the calculated PMV value to a remote server; Overcome the shortcomings of existing thermal comfort monitoring devices, such as incomplete parameter measurement, inability to integrate personal factors, inflexible deployment, and poor data interactivity.

[0024] In a specific implementation, the control unit includes a microcontroller and a Wi-Fi communication module.

[0025] In one specific implementation, the microcontroller includes:

[0026] a data acquisition module for periodically acquiring measurement data from the environmental sensor array;

[0027] an average radiation temperature calculation module for calculating the average radiation temperature tr based on the black sphere temperature tg, the dry-bulb air temperature ta, and the air velocity var;

[0028] a personal parameter receiving module for receiving user personal parameters, the personal parameters including at least the metabolic rate M and the thermal resistance Icl of the clothing;

[0029] An average voting PMV value calculation module is used to calculate and predict the average voting PMV value based on the air temperature ta, the average radiation temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and air temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, according to a pre-stored thermal comfort model;

[0030] A data upload module is used to upload the measurement data and the calculated PMV value to a remote server via the Wi-Fi communication module.

[0031] In a specific implementation, the microcontroller further includes:

[0032] A prediction module, used to further calculate the predicted percentage of dissatisfaction (PPD) and / or the operating temperature tO based on the calculated PMV value.

[0033] In a specific implementation, the environmental sensor array further includes a carbon dioxide sensor for measuring the ambient CO2 concentration.

[0034] In a specific implementation, the black sphere thermometer includes a hollow sphere with a high emissivity coating on its surface and a temperature probe placed at the center of the sphere.

[0035] In one specific implementation scheme, when the air velocity var ≤ 1 m / s, the formula for calculating the average radiation temperature tr is:

[0036] ;

[0037] When the air velocity var > 1 m / s, the formula for calculating the average radiation temperature tr is:

[0038] ;

[0039] Where, ; is the diameter of the hollow sphere.

[0040] In one specific implementation, the formula for calculating the predicted average vote PMV value is:

[0041] ;

[0042] ;

[0043] ;

[0044] ;

[0045] ;

[0046] Wherein, W is the work done by the party at that time, which is generally zero in the office;

[0047] According to the above equation, tcl is obtained through iteration: Specification 3 / 15 page 7 CN 122239195 A

[0048] ;

[0049] ;

[0050] ; ;

[0051] ;

[0052] ;

[0053] ;

[0054] Wherein, is the initial value of;

[0055] The condition for ending the iteration is: .

[0056] In one specific implementation, the formula for calculating the predicted percentage of dissatisfaction PPD is:

[0057] .

[0058] In one specific implementation scheme, the formula for calculating the operating temperature tO is:

[0059] ;

[0060] Wherein, A is a variable, which can be obtained from Table 1:

[0061]

[0062] Table 1 Values ​​of Variable A

[0063] Figure 1 is a block diagram of the external structure of the portable Wi-Fi thermal comfort sensing device provided in the embodiment of this application;

[0064] Figure 2 is an electrical block diagram of a portable Wi-Fi thermal comfort sensing device provided in an embodiment of this application.

[0065] Wherein, 1-housing, 2-black ball thermometer, 3-tripod. Detailed Description

[0066] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. Through these descriptions, the features and advantages of the present application will become clearer and more apparent.

[0067] The term “exemplary” as used herein means “used as an example, embodiment or illustration”. Any embodiment described herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments. Although various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

[0068] Furthermore, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0069] To facilitate understanding of the portable Wi-Fi thermal comfort sensing device provided in the embodiments of this application, the application scenario of its specification page 4 / 15, 8 CN 122239195 A, will be explained first. The portable Wi-Fi thermal comfort sensing device provided in this application aims to overcome the shortcomings of existing thermal comfort monitoring devices, such as incomplete parameter measurement, inability to integrate personal factors, inflexible deployment, and poor data interactivity. Existing market technologies have serious limitations: Incomplete parameter measurement: Most so-called "thermal comfort monitors" or indoor environmental monitoring stations on the market can only measure air temperature and humidity to meet the minimum requirements of LEED, completely failing to measure mean radiant temperature (tr) and air velocity (var), two key parameters that have an equal or even greater impact on thermal balance. Mean radiant temperature characterizes the effect of the surface temperature of surrounding walls, windows, equipment, etc., on radiant heat transfer to the human body, and is crucial in the presence of cold windows, radiant heating / cooling panels, or strong sunlight. Air velocity directly affects convective heat loss and skin evaporation. Ignoring these two parameters leads to distorted PMV calculations, rendering the monitoring results scientifically meaningless and unable to provide a reliable basis for precise environmental control. Lack of personal parameter input: Existing devices are mostly fixed, unattended sensors, unable to conveniently acquire or integrate personal parameters of users at specific locations, such as metabolic rate (M) and clothing thermal resistance (Icl). This results in calculated PMV values ​​based on standard assumptions such as sitting still and wearing standard clothing, failing to reflect an individual's actual thermal sensation in real-world scenarios and limiting the personalization and accuracy of the assessment. Inflexible deployment and data silos: Environmental sensors in traditional Building Management Systems (BMS) are typically fixed installations with wired connections, leading to high deployment costs and poor flexibility. They are difficult to deploy quickly in areas with changing spatial functions or requiring focused monitoring, such as workstations, hospital beds, or classroom seating. Furthermore, data is often confined to the BMS, making direct interaction with mobile applications, cloud platforms, and users difficult. Inability to meet future standard evolution needs: With increasing demands for healthy buildings and precise environmental control, green building standards...It is anticipated that the requirements for thermal comfort monitoring will further increase, shifting from monitoring only temperature and humidity to requiring continuous monitoring of complete PMV. Existing technical solutions cannot meet this forward-looking demand. To address this, this application provides a portable Wi-Fi thermal comfort sensing device to overcome the shortcomings of existing thermal comfort monitoring devices, such as incomplete parameter measurement, inability to integrate personal factors, inflexible deployment, and poor data interactivity. The following detailed description is provided with reference to specific accompanying drawings and embodiments.

[0070] Referring to Figures 1 and 2, Figure 1 is an external structural block diagram of the portable Wi-Fi thermal comfort sensing device provided in this application embodiment; Figure 2 is an electrical block diagram of the portable Wi-Fi thermal comfort sensing device provided in this application embodiment.

[0071] In Figures 1 and 2, an embodiment of this application provides a portable Wi-Fi thermal comfort sensing device, comprising:

[0072] a housing 1, the housing including an upper housing and a base;

[0073] an environmental sensor array integrated in the upper housing, the environmental sensor array including at least:

[0074] an air temperature sensor for measuring the dry-bulb temperature ta;

[0075] a humidity sensor for measuring relative humidity RH;

[0076] a black-bulb thermometer 2 for measuring the black-bulb temperature tg;

[0077] an ultrasonic anemometer for measuring air velocity var;

[0078] a control unit disposed in the base, wherein the control unit is configured to:

[0079] periodically acquire measurement data from the environmental sensor array;

[0080] calculate the average radiant temperature tr based on the black-bulb temperature tg, the dry-bulb temperature ta, and the air velocity var;

[0081] receive user personal parameters, the personal parameters including at least metabolic rate M and clothing thermal resistance Icl;

[0082] Based on the air temperature ta, the average radiation temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and air temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, the predicted average vote PMV value is calculated according to the pre-stored thermal comfort model;

[0083] The measured data and the calculated PMV value are uploaded to a remote server.

[0084] In the above technical solution, by setting a housing, the housing includes an upper housing and a base; an environmental sensor array integrated in the upper housing, the environmental sensor array includes at least: an air temperature sensor for measuring the dry-bulb temperature ta; a humidity sensor for measuring the relative humidity RH; a black sphere thermometer for measuring the Earth temperature tg; an ultrasonic anemometer for measuring the air velocity var; and a control unit set in the base, wherein the control unit isThe configuration is as follows: periodically collect measurement data from the environmental sensor array; calculate the average radiation temperature tr based on the Earth temperature tg, the dry-bulb temperature ta, and the air velocity var; receive user personal parameters, which include at least the metabolic rate M and the clothing thermal resistance Icl; calculate the predicted average voting PMV value based on the air temperature ta, the average radiation temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and the dry-bulb temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, according to a pre-stored thermal comfort model; upload the measurement data and the calculated PMV value to a remote server; overcome the shortcomings of existing thermal comfort monitoring devices, such as incomplete parameter measurement, inability to integrate personal factors, inflexible deployment, and poor data interactivity.

[0085] Specifically, the beneficial effects include:

[0086] First, in terms of parameter measurement, comprehensive and accurate monitoring is achieved. The device integrates multiple environmental sensors: an air temperature sensor to accurately measure air temperature (ta), a humidity sensor to accurately obtain relative humidity (RH), a black sphere thermometer to measure Earth temperature (tg), and an ultrasonic anemometer to measure air velocity (var). These sensors work together to collect environmental parameters comprehensively, avoiding inaccurate thermal comfort assessments due to incomplete parameter measurements, and providing a solid data foundation for accurate calculation of thermal comfort indices.

[0087] Secondly, the device fully considers the impact of individual factors on thermal comfort. The control unit can receive user-specific parameters, including metabolic rate (M) and clothing thermal resistance (Icl). Different individuals have different feelings and needs regarding the thermal environment due to factors such as activity intensity, physical condition, and clothing differences. By incorporating these individual parameters into the calculation system, the device can calculate and predict the average vote PMV value in a personalized manner based on each individual's specific situation, making the thermal comfort assessment more realistic and meeting the needs of different users in different scenarios, greatly improving the accuracy and practicality of the thermal comfort assessment. Furthermore, this technology also has the ability to measure CO2 concentration and calculate PPD and operating temperature (t0).

[0088] Furthermore, deployment is flexible and convenient. The device adopts a shell design, consisting of an upper shell and a base, with a compact and reasonable structure. This design makes the device small in size and light in weight, easy to carry and install. It can be easily deployed in different scenarios such as indoor offices, commercial buildings, and outdoor public areas, without complicated installation procedures and fixed facilities. The monitoring position can be flexibly adjusted according to actual needs to obtain thermal comfort information of different areas in a timely manner, providing timely basis for environmental optimization and control.

[0089] In addition, data interactivity is strong. After completing data acquisition and calculation, the control unit will upload the measured data and the calculated PMV and PPD values ​​to a remote server via Wi-Fi for storage for future statistics and analysis. This function...It enables real-time data sharing and remote monitoring, allowing relevant managers or researchers to access the server anytime, anywhere via the Internet to obtain data monitored by the equipment. This not only facilitates centralized management and analysis of multiple monitoring points but also enables timely detection of thermal environment problems and the implementation of corresponding measures, improving management efficiency. Simultaneously, the accumulation of a large amount of data provides rich material for in-depth research and optimization of thermal comfort models, contributing to the technological development of thermal comfort-related fields and facilitating the submission of reports to LEED and WELL.

[0090] In a specific implementation scheme, the control unit includes a microcontroller and a Wi-Fi communication module. All communication is conducted via Wi-Fi, using a web portal on a cloud server as the central hub.

[0091] Specifically, the beneficial effects include:

[0092] Efficient data processing and control: The microcontroller, as the core of the control unit, possesses powerful data processing capabilities. It can quickly and accurately collect various measurement data periodically from the environmental sensor array, such as dry-bulb temperature, relative humidity, black bulb temperature, and air velocity. Meanwhile, based on the default algorithm, the average radiation temperature is accurately calculated based on the black sphere temperature, dry-bulb air temperature, and air velocity. It can also combine user-specific parameters and quickly calculate the pre-stored thermal comfort model to obtain the measured average PMV and PPD values, ensuring the entire calculation process is efficient and accurate, providing reliable support for subsequent data transmission and thermal environment assessment.

[0093] Flexible and diverse communication methods: The combination of a Wi-Fi communication module and a Bluetooth communication module (in another embodiment of the invention, Bluetooth service may be absent) enables the device to have flexible data transmission capabilities. The Wi-Fi communication module can achieve high-speed and stable connection between the device and a remote server, and can promptly upload the measured data and calculated PMV values ​​to the remote server, facilitating remote monitoring and data analysis by management personnel, and is suitable for large-scale, long-distance data transmission scenarios. The Bluetooth communication module (in another version of the invention, there is no Bluetooth service; all communication is conducted via Wi-Fi through a network portal on a cloud server) provides a short-range, low-power communication method, facilitating quick pairing and data interaction between the device and nearby mobile terminals (such as mobile phones and tablets). Users can obtain real-time data from the device at any time through their mobile devices for local viewing and simple operation, enhancing the device's practicality and convenience. This dual-communication module design meets the data transmission needs in different scenarios, improving the device's applicability and user experience.

[0094] In one specific implementation scheme, the microcontroller includes:

[0095] a data acquisition module, used to periodically acquire measurement data from the environmental sensor array;

[0096] The average radiation temperature calculation module is used to calculate the average radiation temperature tr based on the black bulb temperature tg, the dry bulb temperature ta, and the air velocity var;

[0097] The personal parameter receiving module is used to receive user personal parameters, which include at least the metabolic rate M and the clothing thermal resistance Icl;

[0098] The average vote PMV value calculation module is used to calculate and predict the average vote PMV value based on the dry bulb temperature ta, the average radiation temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and the dry bulb temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, according to a pre-stored thermal comfort model;

[0099] The data upload module is used to upload the measurement data and the calculated PMV, PPD, and to values ​​to a remote server through the Wi-Fi communication module.

[0100] Specifically, the beneficial effects include:

[0101] Accurate data acquisition and processing: The acquisition module can stably and accurately acquire multiple measurement data such as air temperature and relative humidity from the environmental sensor array according to the set cycle, providing a reliable basis for subsequent calculations. The average radiation temperature calculation module accurately calculates the average radiation temperature based on specific parameters, ensuring the accuracy of key indicators for thermal comfort assessment.

[0102] Personalized assessment support: The personal parameter receiving module receives personal parameters such as user metabolic rate and clothing thermal resistance via Bluetooth communication (in another version of this invention, there is no Bluetooth service). Different individuals have different perceptions of the thermal environment due to differences in activity levels and clothing. This module enables the device to calculate and predict the average vote PMV value based on personal factors, making the thermal comfort assessment more in line with the actual situation and meeting personalized needs.

[0103] Efficient calculation and upload: The average vote PMV value calculation module quickly calculates the PMV value based on multiple parameters and pre-stored models. The calculation process is efficient and scientific. The data upload module uses the Wi-Fi communication module to upload the measurement data and calculation results to the remote server in a timely manner, facilitating remote monitoring and analysis by management personnel. It can quickly identify thermal environment problems and take measures to improve management efficiency.

[0104] Modular design advantages: Each module has a clear division of labor and cooperates with each other. This modular design makes the system structure clear and easy to maintain and upgrade. If a certain module has a problem, it can be repaired or optimized in a targeted manner without affecting the normal operation of other modules, thus improving the stability and reliability of the equipment.

[0105] In a specific implementation scheme, the microcontroller further includes:

[0106] a prediction module, used to further calculate the predicted dissatisfaction percentage (PPD) and / or operating temperature tO based on the calculated PMV value.

[0107] Specifically, the beneficial effects include:

[0108] Enriching the dimensions of thermal comfort assessment: the prediction module, based on the calculated predicted average voteBased on the PMV value, the predicted percentage of dissatisfaction (PPD) and / or operating temperature (to) are further calculated, so that thermal comfort assessment is no longer limited to a single PMV value. PPD can intuitively reflect the proportion of people who are dissatisfied with the current thermal environment, while operating temperature integrates the comprehensive thermal feeling of people from multiple environmental factors. Multi-dimensional assessment makes the results more comprehensive and accurate, and can more accurately grasp the thermal environment status.

[0109] Provide more practical decision-making basis: For practical application scenarios such as building environment management and HVAC system control, PPD and operating temperature (to) can provide more targeted decision-making references. For example, based on the PPD value, it can be determined to the extent that the thermal environment needs to be improved to meet the needs of most people; based on the operating temperature (to), indoor temperature, humidity and other parameters can be adjusted more reasonably to optimize the thermal environment, improve the comfort of people, and avoid excessive energy consumption.

[0110] Enhance the completeness of system functions: The addition of this module improves the functional system of the microcontroller, upgrading the equipment from simple data acquisition and PMV value calculation to a system that can provide comprehensive thermal comfort analysis results. This not only enhances the value of the equipment itself, but also makes it more competitive in the market, and better meets the diverse needs of different users for thermal comfort monitoring and analysis.

[0111] Promote the application of thermal comfort research: The rich calculation results provide more valuable data for scientific research in the field of thermal comfort, which helps to explore the relationship between thermal environment and human sensation, promote the development of related theories, and also provide more scientific guidance for practical engineering applications, promoting the widespread application of thermal comfort technology in various fields.

[0112] In a specific implementation scheme, the environmental sensor array also includes a carbon dioxide sensor for measuring the environmental CO2 concentration.

[0113] Specifically, the beneficial effects include:

[0114] Comprehensive air quality monitoring: The newly added carbon dioxide sensor makes the environmental sensor array more complete. In addition to measuring conventional parameters such as air temperature and relative humidity, it can also accurately measure the CO2 concentration in the environment. CO2 is a key indicator affecting indoor air quality. Its high concentration can cause dizziness, fatigue and other discomfort. By monitoring the CO2 concentration, the air quality status can be fully understood, providing richer data support for creating a healthy and comfortable environment.

[0115] Improve the accuracy of thermal comfort assessment: CO2 concentration is closely related to human activity, and CO2 concentration is often higher in densely populated areas, which can also affect people's perception of the thermal environment. Including it in the monitoring scope allows for a more comprehensive consideration of factors affecting human comfort when calculating predicted average vote PMV values ​​and other related thermal comfort indicators, making the assessment results closer to reality and improving the accuracy and reliability of thermal comfort assessment.

[0116] Assist in ventilation system optimization: Real-time acquisition of CO2 concentration data helps determine the effectiveness of indoor ventilation. When CO2 concentration...When the temperature exceeds a certain threshold, the operating parameters of the ventilation system can be adjusted in a timely manner, such as increasing the fresh air volume and adjusting the ventilation frequency, to improve indoor air quality, avoid discomfort caused by poor ventilation, and protect the health and work efficiency of personnel.

[0117] Meets diverse application needs: In various scenarios, such as offices, schools, shopping malls, etc., monitoring of CO2 concentration is essential. After the device is equipped with a carbon dioxide sensor, it can better meet the diverse needs of environmental monitoring and thermal comfort assessment in different scenarios, and has a wider application prospect and market value.

[0118] In a specific implementation scheme, the black ball thermometer includes a hollow sphere with a high emissivity coating on its surface and a temperature probe placed at the center of the sphere.

[0119] Specifically, the beneficial effects include:

[0120] More accurate measurement: The high emissivity coating on the surface of the hollow sphere can significantly enhance the sphere's ability to absorb and emit thermal radiation from the surrounding environment. This allows the black sphere thermometer to capture comprehensive thermal radiation information in the environment more efficiently and accurately, reducing measurement errors caused by insufficient emissivity, making the measured black sphere temperature tg closer to the true value, providing a reliable basis for the accurate calculation of the subsequent average radiation temperature tr, and thus improving the accuracy of the overall thermal comfort assessment.

[0121] Faster response: The hollow sphere's structural design results in a relatively small heat capacity. Compared to a solid sphere, when the ambient temperature changes, the hollow sphere can reach a state of thermal equilibrium with the surrounding environment more quickly, and the temperature probe can also sense the temperature change of the sphere more quickly and respond. This greatly shortens the measurement time, improves the real-time monitoring capability of the device, and can reflect the dynamic changes of the thermal environment in a timely manner.

[0122] More reasonable structure: Placing the temperature probe in the center of the sphere allows the probe to receive thermal radiation from all directions of the sphere evenly, avoiding local measurement deviations caused by improper probe position. This reasonable structural design ensures the stability and consistency of the black sphere thermometer measurement. Regardless of how the sphere is placed or how the direction of environmental heat radiation changes, relatively accurate measurement results can be obtained.

[0123] In a specific implementation scheme, when the air velocity var ≤ 1 m / s, the formula for calculating the average radiation temperature tr is:

[0124] ;

[0125] When the air velocity var > 1 m / s, the formula for calculating the average radiation temperature tr is:

[0126] ;

[0127] Wherein, ; is the diameter of the hollow sphere.

[0128] In a specific implementation scheme, the formula for calculating the predicted average vote PMV value is:

[0129] ;

[0130] ;

[0131] ;

[0132] ;

[0133] ;

[0134] Wherein, W is the work done by the party at that time, which is generally zero in the office;

[0135] According to the above equation, tcl is obtained through iteration:

[0136] ; Specification 9 / 15 page 13 CN 122239195 A

[0137] ;

[0138] ; ;

[0139] ;

[0140] ;

[0141] ;

[0142] Wherein, is the initial value of ;

[0143] The condition for the iteration to end is: .

[0144] In a specific implementation scheme, the calculation formula for the predicted percentage of dissatisfaction (PPD) is:

[0145] .

[0146] In one specific implementation, the formula for calculating the operating temperature tO is:

[0147] ;

[0148] Wherein, A is a variable, which can be obtained through Table 1:

[0149]

[0150] Table 1 Value table of variable A

[0151] In one specific implementation, the portable Wi-Fi thermal comfort sensing device aims to achieve: full parameter measurement: integrating dedicated sensors, for the first time simultaneously and accurately measuring all four environmental parameters (ta, tr, RH, var) required for calculating PMV on a portable device at the same point. Convenient input of personal parameters: through a wireless mobile application, users can conveniently input or select the current activity level (metabolic rate M) and clothing status (clothing thermal resistance Icl) to achieve personalized PMV calculation. Flexible deployment and wireless interconnection: powered by battery / USB, it supports tripod or desktop placement, can access the local network or Internet via Wi-Fi, and can be directly connected to personal mobile devices via Bluetooth (in another version of the invention, there is no Bluetooth service) to achieve highly flexible deployment and bidirectional data flow. Meets and leads standards: Not only does it meet the current LEED / WELL requirements for continuous temperature and humidity monitoring, but it also has the capability to continuously monitor PMV to meet the requirements of future standards, and provides derivative indicators such as PPD and operating temperature. Extended environmental quality monitoring: Optional integration of carbon dioxide (CO2) or other indoor environmental quality (IEQ) sensors to provide a more comprehensive environmental health assessment. Includes:

[0152] I. Equipment hardware architecture

[0153] As shown in Figure 1, the sensing device adopts an integrated and compact industrial design, mainly including the following modules:

[0154] 1. Main housing and mechanical structure:

[0155] Upper housing: Usually white or light-colored to reduce the impact of solar radiation absorption on the sensor. It houses the core environmental sensor.

[0156] Black sphere thermometer: A hollow sphere (usually 40mm or 150mm in diameter) with a surface coated with standard emissivity matte black paint, fixed to the top of the device. A high-precision digital temperature sensor (such as a platinum resistance thermometer PT1000 or a precision NTC thermistor) is installed at the center of the sphere to measure the sphere's temperature (tg). The black sphere is used for comprehensive sensing of radiative heat exchange. (Instruction manual, pages 10 / 15, 14 CN)122239195 A

[0157] Lower housing / base: houses the main control circuit board, wireless communication module, and power system. The base design ensures that the device can be stably placed on a horizontal table. The bottom is equipped with a standard tripod thread interface (such as 1 / 4 inch-20 UNC), compatible with universal photography tripods, allowing for flexible height and position adjustments.

[0158] 2. Environmental sensor array (integrated in the upper housing):

[0159] Air temperature sensor: uses a high-precision, low-heat-capacity digital temperature sensor (such as DS18B20, SHT series integrated sensor) to measure dry bulb temperature ta. The sensor is placed in a well-ventilated radiation shield to avoid the effects of radiation and self-heating.

[0160] Relative humidity sensor: uses a capacitive digital humidity sensor (such as Sensirion SHT4x, TE HTU21D) to measure relative humidity RH. This sensor is usually integrated with the air temperature sensor on the same chip or module to ensure consistent measurement points. The sensor that can be used is the SHT-45, a high-precision MEMS RH sensor that can simultaneously measure temperature and relative humidity.

[0161] Ultrasonic anemometer: A miniature ultrasonic anemometer is used. Its working principle is to measure the time difference of ultrasonic pulses propagating with and against the wind between a pair of transducers at a fixed distance. This technology has no moving parts, low starting wind speed, and high accuracy, making it very suitable for measuring low indoor wind speeds (0.05 m / s to 5 m / s). The device typically integrates two pairs of orthogonal ultrasonic transducers to measure two-dimensional wind speed and calculates the wind speed magnitude var by vector synthesis. The sensor probe is exposed to the airflow, and the housing design ensures that it is sensitive to airflow from all directions.

[0162] Optionally, an indoor environmental quality sensor: such as a non-dispersive infrared (NDIR) carbon dioxide sensor, is used to continuously measure CO2 concentration (ppm) as an indicator of indoor air quality.

[0163] 3. Electronic System (located inside the base):

[0164] Microcontroller Unit: As the brain of the device, it is responsible for sensor data acquisition, preprocessing, PMV / PPD / operating temperature calculation, system control, and communication scheduling. Low-power, high-performance MCUs are preferred, such as those based on ARM Cortex-M.

[0165] Wireless Communication Module:

[0166] Wi-Fi Module: Supports 802.11 b / g / n protocols, enabling the device to access a local area network (LAN) or connect to the Internet via a router, uploading data to a cloud server or local data gateway.

[0167] Bluetooth Module (in another version of the invention, there is no Bluetooth service): Supports Bluetooth. In another version of the invention, there is no Bluetooth service; all communication uses Wi-Fi through a web portal on the cloud server.Okay. Low power consumption, used to establish a short-range direct connection with the user's smartphone, tablet computer and other mobile devices for device configuration, personal parameter input and real-time data viewing.

[0168] Power Management Unit:

[0169] Rechargeable Battery: such as a lithium polymer battery, providing at least 1 hour of battery life for the device in the event of movement or power failure.

[0170] USB-C Charging / Powering Interface: supports 5V DC input, can charge the battery or directly power the device. When connected to USB power, the device prioritizes the use of external power and charges the battery.

[0171] Power Switch and LED Indicator: The button controls the device switch. The LED indicator shows the status with different colors and flashing patterns (e.g., solid red - battery powered only; slow flashing green - normal operation and communication; fast flashing - configuration mode, etc.).

[0172] II. Core Measurement and Calculation Methods

[0173] The device firmware embeds algorithms based on ISO 7730 and ASHRAE 55 standards to achieve the following calculations:

[0174] 1. Measurement and Conversion of Basic Parameters:

[0175] Air temperature ta and relative humidity RH are read directly from the sensor.

[0176] Calculation of water vapor partial pressure pa: Based on the known ta, the saturated total water vapor pressure ps is calculated using formulas such as Arden Buck formula. Then pa = (RH / 100) * ps.

[0177] Air velocity var: The raw data is read from the ultrasonic anemometer, calibrated and filtered, and the vector summation of the two vertical measurement values ​​is taken.

[0178] Calculation of average radiation temperature tr: The black sphere temperature method is used. When var ≤ 1 m / s (typical indoor environment), use the simplified formula:

[0179] ;

[0180] For higher wind speeds (e.g., var > 1 m / s), use a more accurate formula, considering a more complex model of the convective heat transfer coefficient:

[0181] .

[0182] Calculation of operating temperature to: According to ASHRAE 55, the operating temperature is a weighted average of air temperature and mean radiant temperature: to = A * ta + (1-A) * tr. The weighting coefficient A is determined by looking up the air velocity var in a table (e.g.: var < 0.2 m / s, A=0.5; 0.2 ≤ var < 0.6, A=0.6; 0.6 ≤ var < 1.0, A=0.7).

[0183] 2. PMV and PPD Calculation:

[0184] Personal Parameter Input: Users select the current activity type (corresponding to metabolic rate M, unit: met or W / m², data source: ISO 8996) and clothing combination (corresponding to clothing thermal resistance Icl, unit: clo or m²·K / W, data source: ISO 8996) from a preset table via a mobile application.9920). These values ​​are sent to the device via Bluetooth (in another version of the invention, there is no Bluetooth service).

[0185] PMV calculation: The device MCU executes the PMV algorithm defined in ISO 7730. The algorithm is based on the human body heat balance equation, considering the above six input parameters (ta, tr, pa, var, M, Icl), and calculates the PMV value (-3 to +3) by iteratively solving physiological parameters such as skin temperature and sweating rate:

[0186] The formula for calculating the predicted average vote PMV value is:

[0187] ;

[0188] ;

[0189] ;

[0190] ;

[0191] ;

[0192] PPD calculation: Based on the calculated PMV value, the PPD is calculated using the formula given in ISO 7730: Specification 12 / 15 pages 16 CN 122239195 A

[0193] .

[0194] III. Software and System Architecture

[0195] The system consists of a device, a mobile application, and a cloud service platform.

[0196] 1. Device Firmware:

[0197] Responsible for periodically (e.g., every minute) waking up the sensor for measurement.

[0198] Performs all the above calculations.

[0199] Manages wireless connectivity: maintains Wi-Fi connectivity to upload data to the cloud; maintains Bluetooth (in another version of the invention, there is no Bluetooth service) broadcast, allowing mobile devices to discover and connect.

[0200] Responds to configuration queries and setting commands from the cloud or mobile application.

[0201] Manages power status and optimizes power consumption to extend battery life.

[0202] 2. Mobile Application:

[0203] Device Management: Search, pair, and connect devices via Bluetooth (in another version of the invention, there is no Bluetooth service; all communication between the user and the device is conducted via Wi-Fi through a web portal on a cloud server, which acts as a central hub). Configure device name, location, Wi-Fi network credentials, data upload frequency, etc.

[0204] Personal Parameter Settings: Provide an intuitive interface that allows users to select their current activity (e.g., sedentary work, walking, housework) and clothing (e.g., summer business attire, winter casual wear, pajamas) from a tiered list. The application sends the corresponding M and Icl values ​​to the device.

[0205] Data Visualization: Display all environmental parameters (ta, RH, tg, var, CO2) measured by the device in real time in numerical and graphical form, as well as the calculated tr, PMV, PPD, and to values. Provide historical data trend charts.

[0206] Warnings and Notifications: Users can set thresholds for PMV or specific parameters (such as CO2), and receive push notifications when the value exceeds the range.

[0207] Local Data Log: Data stored locally on the phone for a period of time can be viewed offline.

[0208] 3. Cloud Service Platform:

[0209] Device Access and Management: Receives data streams from numerous devices via protocols such as MQTT and HTTP. Maintains a device database, recording device ID, location, configuration, and status.

[0210] Data Storage and Analysis: Stores time-series data in a time-series database. Provides functions for data query, aggregation analysis, and report generation.

[0211] Dashboard and Visualization: Provides a Web dashboard for building managers to centrally monitor the status and thermal environment indicators of all deployed devices, and perform building-level thermal comfort analysis and spatial comparison.

[0212] Advanced Functions:

[0213] Data Verification and Calibration: The cloud can compare data from multiple devices in the same area, identify abnormal sensors, and send calibration offset commands to the devices.

[0214] Benchmark Update: The cloud can manage and push the latest activity metabolic rate table (ISO 8996) and clothing thermal resistance table (ISO 9920) to the devices to ensure that the calculation basis is up-to-date.

[0215] Integration with building automation systems: Provides an API interface to feed back real-time PMV, PPD, or operating temperature to data to the building management system (BMS), making it possible to achieve dead-loop control based on thermal comfort (rather than just temperature).

[0216] Compliance reports: Automatically generates thermal comfort monitoring reports that meet LEED IEQ or WELL v2 T06 requirements.

[0217] In this embodiment, the beneficial effects include: Specification 13 / 15 pages 17 CN 122239195 A

[0218] Compared with the prior art, the present invention has the following significant beneficial effects:

[0219] 1. Revolution in measurement integrity: For the first time, sensors for all four environmental parameters (ta, tr, RH, var) required for measuring PMV are integrated into a portable, independent device, filling a market gap and making it possible to scientifically monitor local thermal comfort in real time in accordance with international standards (ISO 7730, ASHRAE 55).

[0220] 2. Personalized Assessment: Personal activity and clothing parameters are conveniently integrated via a Bluetooth mobile application (in another version of this invention, without Bluetooth service), elevating PMV calculation from being based on the "standard person" assumption to reflecting the "actual user's" state, making the assessment results more personalized and valuable.

[0221] 3. Deployment Flexibility and Scalability: Portable design, multiple power supply methods, and wireless connectivity allow for rapid deployment at any monitoring location (such as specific workstations in open-plan offices, hospital wards, school classrooms, and home rooms), forming a high-density, low-cost thermal environment sensing network.

[0222] 4. Forward-Looking to Meet High Standards: To meet future green building certification standards (such as LEED and WELL, and potential upgrades)...The requirements for continuous monitoring of complete PMV (Level 1) provide readily available technical solutions, which help projects obtain higher scores.

[0223] 5. Data-driven decision support: Through the cloud platform, it provides facility managers with unprecedented, granular thermal environment data insights, which can be used to diagnose HVAC system problems, optimize energy distribution, verify design effectiveness, and improve occupant satisfaction.

[0224] 6. Integrated IEQ monitoring: Optional CO2 sensors expand the device's functionality, making it a comprehensive indoor environmental quality monitoring station, multiplying its value.

[0225] 7. User-friendly and interactive: The mobile application enables end users to understand the thermal comfort status of their own microenvironment and can proactively improve comfort by adjusting clothing, activities, or requesting environmental adjustments, enhancing user experience and a sense of control over the environment.

[0226] In one specific implementation scheme, the deployment process of the portable Wi-Fi thermal comfort sensing device for thermal comfort auditing in open-plan offices is as follows:

[0227] 1. Device deployment:

[0228] Auditors carry multiple devices of this application into the target office area.

[0229] In each area to be evaluated (e.g., window workstation, central workstation, workstation near air conditioning vent, meeting room), place the device on a desktop (approximately 0.6 meters) representing the occupant's sitting height using a tripod 3, or place it directly using its own base.

[0230] Power on each device (connect to USB power or use batteries), and quickly configure the device name (e.g., "Area_A_Window_Desk") and location information via Bluetooth on a mobile phone (in another version of the invention, there is no Bluetooth service; all communication between the user and the device is conducted via Wi-Fi through a web portal on a cloud server). Then, add the device to the office area's Wi-Fi network.

[0231] 2. Data Acquisition and Personal Parameter Input:

[0232] The device starts working automatically, measuring ta, RH, tg, var, and CO2 every minute.

[0233] Employees located in the area are invited to use a mobile app (in another version of the invention, there is no app on the phone; the user logs into a web portal on a cloud server (acting as a central hub), which communicates with the device to perform all settings and data transfers). The employee opens the app and connects to a nearby device via Bluetooth (in another version of the invention, there is no Bluetooth service).

[0234] In the app, the employee selects their current activity (e.g., "sedentary, typing at work", metabolic rate approximately 1.2 met) and clothing (e.g., "long-sleeved shirt + trousers", clothing thermal resistance approximately 0.7 clo) from a list.

[0235] The app sends these personal parameters to the device. The device firmware immediately incorporates the latest environmental parameters and calculates the employee's... (Page 14 / 15, 18 CN)122239195 A Personalized PMV, PPD, and operating temperature.

[0236] 3. Data upload and cloud monitoring:

[0237] The device periodically (e.g., every 5 minutes) uploads data packets containing timestamps, all measurement parameters, calculated PMV / PPD / to values, and associated user IDs (anonymized) to the cloud platform via Wi-Fi.

[0238] The facilities management team can view the thermal environment "map" of the entire office area in real time on the cloud dashboard. They can find that: in the afternoon, the tr and PMV of the window area increase significantly due to strong solar radiation; the var of the area near the air conditioning vent is too high, which may cause a localized draft; the CO2 concentration in a corner increases after the afternoon meeting.

[0239] The platform automatically generates reports showing the percentage of time that the PMV of each area is within the ASHRAE comfort zone (-0.5 < PMV < +0.5), providing data support for WELL certification.

[0240] 4. Decision-making and optimization:

[0241] Based on the data, the management team can adjust the zoning settings of the HVAC system, for example, slightly reducing the cooling temperature of the west-facing area in the afternoon, or adjusting the angle of the air valves near the air outlets.

[0242] They can also combine this data with anonymous employee feedback surveys to quantify the impact of thermal environment improvements on work efficiency and satisfaction.

[0243] For long-term monitoring, the equipment can be permanently deployed in key locations to continuously provide data for fault detection and preventative maintenance.

[0244] Those skilled in the art will recognize that this application can be implemented as a system, method, or computer program product.

[0245] Therefore, this disclosure can be specifically implemented in the following forms: it can be entirely hardware, entirely software including firmware, resident software, microcode, etc., or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this application can also be implemented as a computer program product in one or more computer-readable media containing computer-readable program code.

[0246] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical memory, magnetic memory, or...Any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0247] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application. Based on this, various substitutions and improvements can be made to this application, all of which fall within the protection scope of this application. Instruction sheet 15 / 15 Page 19 CN 122239195 A Figure 1 Figure 2 Instruction drawing 1 / 1 Page 20 CN 122239195 A Abstract A portable Wi-Fi thermal comfort monitoring device is provided, comprising a housing including an upper casing and a base, wherein an environmental sensor array is integrated within the upper casing. The environmental sensor array includes at least a dry-bulb air temperature sensor, a humidity sensor, a globe thermometer, and an ultrasonic anemometer. A control unit is disposed within the base and is configured to periodically acquire measurement data from the environmental sensor array, calculate a mean radiant temperature(MRT), receive user-specific parameters including metabolic rate and clothing insulation, and compute a Predicted Mean Vote (PMV) value based on the measured data and theuser-specific parameters. The control unit is further configured to transmit the measurement data together with the calculated PMV value to a remote server via a Wi-Fi connection. By virtue of the above arrangement, the device addresses the limitations of conventional thermal comfort monitoring systems, including incomplete parameter measurement, lack of integration of personal factors, inflexible deployment, and insufficient data connectivity.

Claims

1. A portable Wi-Fi thermal comfort sensing device, characterized in that, include: The housing includes an upper housing and a base; An environmental sensor array integrated into the upper housing, the environmental sensor array comprising at least: An air temperature sensor used to measure the dry-bulb temperature ta of air; A humidity sensor used to measure relative humidity (RH); A black sphere thermometer used to measure the temperature tg of a black sphere; Ultrasonic anemometer for measuring low air velocity (var); A control unit disposed within the base, wherein the control unit is configured to: Measurement data is periodically collected from the array of environmental sensors; The average thermal radiation temperature tr is calculated based on the black sphere temperature tg, the air temperature ta, and the air velocity var. Receive user personal parameters, which include at least metabolic rate M and clothing thermal resistance Icl; Based on the dry-bulb temperature ta, the average thermal radiation temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and the dry-bulb temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, the predicted average vote PMV value is calculated according to the pre-stored thermal comfort model. The measurement data and the calculated PMV value are uploaded to a remote server.

2. The portable Wi-Fi thermal comfort sensing device according to claim 1, characterized in that, The control unit includes a microcontroller and a Wi-Fi communication module.

3. The portable Wi-Fi thermal comfort sensing device according to claim 2, characterized in that, The microcontroller includes: The data acquisition module is used to periodically acquire measurement data from the array of environmental sensors; The mean radiation temperature calculation module is used to calculate the mean radiation temperature tr based on the black sphere temperature tg, the dry-bulb air temperature ta, and the air velocity var. A personal parameter receiving module is used to receive user personal parameters, which include at least metabolic rate M and clothing thermal resistance Icl; The average vote PMV value calculation module is used to calculate and predict the average vote PMV value based on the dry-bulb temperature ta, the average radiation temperature tr, the water vapor partial pressure pa derived from the relative humidity RH and the air temperature ta, the air velocity var, the metabolic rate M, and the clothing thermal resistance Icl, according to a pre-stored thermal comfort model; the saturated water vapor pressure ps is found from the table by ta, and then pa = (RH / 100) ∙ ps is calculated. The data upload module is used to upload the measurement data and the calculated PMV value to a remote server via the Wi-Fi communication module.

4. The portable Wi-Fi thermal comfort sensing device according to claim 3, characterized in that, The microcontroller also includes: The prediction module is used to further calculate the predicted percentage of unsatisfactory performance (PPD) and / or the operating temperature (t) based on the calculated PMV value. O .

5. The portable Wi-Fi thermal comfort sensing device according to claim 4, characterized in that, The environmental sensor array also includes a carbon dioxide sensor for measuring the ambient CO2 concentration.

6. The portable Wi-Fi thermal comfort sensing device according to claim 5, characterized in that, The black sphere thermometer includes a hollow sphere with a high emissivity coating on its surface and a temperature probe placed at the center of the sphere.

7. The portable Wi-Fi thermal comfort sensing device according to claim 6, characterized in that, When the air velocity var ≤ 1 m / s, the formula for calculating the average radiation temperature tr is: ； When the air velocity var > 1 m / s, the formula for calculating the average radiation temperature tr is: ； in, ; is the diameter of the hollow sphere.

8. The portable Wi-Fi thermal comfort sensing device according to claim 7, characterized in that, The formula for calculating the predicted average vote PMV value is as follows: ； ； ； ； ； Among them, W represents the work done by the party at that time, which is generally zero in the office; Based on the above equation, tcl is obtained through iteration: ； ； ； ； ； ； ； in, for The initial value; The condition for the iteration to end is: .

9. The portable Wi-Fi thermal comfort sensing device according to claim 8, characterized in that, The formula for calculating the predicted percentage of dissatisfaction (PPD) is as follows: 。 10. The portable Wi-Fi thermal comfort sensing device according to claim 9, characterized in that, The operating temperature t O The calculation formula is: ； Where A is a variable.

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