911results about "Control inputs involving users/components" patented technology

The invention relates to the technical field of air-cooled air conditioner control, in particular to an air-cooled air conditioner control method and system based on deep learning, and the method comprises the following steps: obtaining sensor readings of indoor temperature, outdoor temperature and humidity and Wi-Fi channel state information, judging the position number and the activity state of personnel, calculating the position distribution of the personnel in combination with a time window, and calculating the position distribution of the personnel. And integrating to obtain a multi-dimensional environment and load state vector. According to the method, indoor and outdoor temperature, humidity, Wi-Fi channel state information and personnel position distribution and activity states are integrated through a multi-dimensional environment and load state vector, the personnel density change trend is dynamically calculated through a time window, the comprehensiveness and real-time performance of environment perception are enhanced, and high-dimensional data support is provided for control decision making. And a basic comfort degree deviation index is constructed based on the temperature deviation value and the humidity deviation value, and a multi-target performance index set is generated in combination with the wind speed value, the compressor start-stop frequency and the energy consumption power.

The invention discloses a health-care sojourn environment air quality monitoring and purifying method and system based on the Internet of Things, and the method comprises the steps: dividing a dynamic microenvironment region, deploying a multi-mode sensing terminal, collecting indexes, and uploading the indexes to a cloud end; establishing a personalized dynamic standard according to the human body biological rhythm characteristics; generating an initial evaluation value through an environment-health coupling evaluation model, and judging whether the initial evaluation value deviates from a standard or not through a dynamic threshold deviation detection model; if so, predicting an air quality trend by using a space-time multi-dimensional trend deduction model, and generating a target evaluation value; and inputting the regional space purification model to generate a purification strategy, and linking the purification equipment to realize precise targeted purification. According to the method, the limitation of traditional fixed indexes is broken through, the upgrading from environmental monitoring to health response is realized, the health risk can be accurately evaluated, the trend can be predicted, the purification parameters are dynamically adjusted, a monitoring, analysis, prediction and purification closed loop is formed, the air quality regulation and control accuracy and energy efficiency are improved, and an efficient scheme is provided for healthy and nourishment of sojourn.

A method for controlling a dehumidifier is provided. The dehumidifier may include a dehumidifying module having a compressor, a condenser, an expansion valve, an evaporator, and a fan module. The method may include determining by an occupancy sensor whether an occupant is present in an indoor space in which the dehumidifier is located; operating the compressor at a low speed when the occupancy sensor determines that an occupant is present in the indoor space; operating the compressor at a constant or high speed when the occupancy sensor determines that there are no occupants in the indoor space; and stopping operation of the compressor when an indoor humidity reaches a target humidity.

The invention relates to the technical field of control, and discloses an oxygen supply dynamic regulation and control method, system and device for a plateau district and computer equipment, and the method comprises the steps: carrying out the first-stage oxygen supply for an indoor room through a first oxygen supply operation corresponding to a first oxygen supply flow under the condition that there is no person in the indoor room; after the indoor real-time oxygen content reaches the target oxygen volume fraction, if people move in the indoor room and the indoor room is in a ventilation state, second-stage oxygen supply is carried out on the indoor room through second oxygen supply operation corresponding to second oxygen supply flow, so that the indoor real-time oxygen content is kept stable at the target oxygen volume fraction; and the second oxygen supply flow is corrected by using the number of indoor people, the indoor activity type and the indoor real-time carbon dioxide content which are monitored in real time, and the difference value between the indoor real-time oxygen content and the target oxygen volume fraction is kept within the target threshold value range. Finally, the oxygen supply regulation and control method for dynamically controlling the indoor oxygen supply flow of the plateau area based on the environment parameter data monitored in real time is achieved.

The invention relates to the technical field of constructional engineering, and discloses an intelligent ventilation and purification method and system for constructional engineering, and the method comprises the steps: 1, determining the concentration of pollutants in a building based on real-time air quality data, and calculating the required ventilation quantity meeting a preset standard; secondly, the fresh air introduction proportion is adjusted according to the indoor and outdoor temperature and humidity difference value so as to optimize energy consumption and thermal comfort balance; 3, according to the personnel distribution density, the local area air supply intensity is set, and the air circulation uniformity is ensured; fourthly, the system operation mode is regulated and controlled based on the working state of the air purification equipment, so that energy consumption is reduced, and the service life of the equipment is prolonged; the fresh air introduction proportion is intelligently adjusted by comparing indoor and outdoor temperature and humidity differences. For example, when the outdoor temperature and humidity are close to the indoor comfortable interval, the fresh air volume is increased to utilize natural cold and heat sources; when the outdoor environment is extreme, the fresh air volume is reduced, the heat recovery device is started, the air conditioner load is reduced, and energy waste is reduced.

The invention relates to the technical field of air conditioning system control, and discloses an airport terminal air conditioning system control method, device and equipment. According to the invention, by combining the number of passengers in any target area in the nth sub-areas of the check-in hall, the security check area and the waiting hall in the preset time period and the load demand parameters of the air conditioning system in the target area in the preset time period, the change of the passenger flow volume in the airport station building can be flexibly adapted; and the regulation and control mode of the corresponding air conditioning system is correspondingly adapted, so that the air conditioning system of the target area is precisely regulated and controlled, and finally the energy consumption of the air conditioning system of the airport terminal is saved.

The invention relates to the technical field of ventilation regulation and control, in particular to an air conditioner door and window joint control method and system, and the method comprises the steps: information collection: constructing a multi-source data collection layer, and obtaining the following data in real time: meteorological early warning data, user operation logs, a regional climate feature library, and a user historical use region; behavior feature extraction: processing user operation logs and thermodynamic diagram data by adopting a space-time convolutional neural network to generate a three-dimensional demand map; dynamic regulation and control calculation: extracting an external window SHGC value and a wall heat conductivity coefficient based on a building BIM model, and calculating an optimal opening threshold value of a door and a window in combination with real-time meteorological data; performing cooperative control: adopting a multi-target particle swarm optimization algorithm, and generating a control instruction set under the targets of energy consumption and comfort; and an instruction is issued to the air conditioner and the electric door and window actuator. The system comprises an information acquisition module, a behavior characteristic acquisition module, a dynamic regulation and control calculation module and a cooperative control execution module. The method has the effect of reducing energy waste.

The invention provides a heating ventilation air conditioner control method, system and device based on dynamic heat load prediction and a storage medium. The method comprises the following steps: acquiring indoor individual physiological data, environmental parameters and regional personnel distribution data in real time; determining a real-time individual metabolic rate equivalent based on the individual physiological data and the environmental parameters; aggregating the individual metabolic rate equivalents according to the regional personnel distribution data, determining the total heat load and the total heat load change rate of each indoor region, and decomposing the total heat load into a sensible heat load and a latent heat load; and on the basis of the sensible heat load, the latent heat load and the total heat load change rate, air supply temperature, air supply amount and humidity control instructions of the heating ventilation air conditioning system for feed-forward adjustment are generated. According to the technical scheme, dynamic thermal load prediction based on individual physiological data and environmental parameters can be achieved, the indoor total thermal load is quantified in real time, and the feedforward adjustment control instruction of the heating ventilation air conditioning system is generated.

The invention relates to the field of intelligent control systems, and particularly discloses a water chilling unit operation control method based on artificial intelligence, which comprises the following steps: S1, data acquisition: respectively acquiring operation parameters of each water chilling unit, a chilled water pump, a cooling water pump and a cooling tower in an air conditioning system in real time by utilizing a plurality of sensors, outdoor meteorological parameters and environment parameters of all rooms are collected at the same time; s2, load prediction: establishing a load prediction model by using a neural network according to the collected historical outdoor meteorological parameters, the environment parameters of each room and the corresponding air conditioner load data, and predicting the air conditioner load of the building; s3, performance parameter determination: establishing a performance attenuation model of the water chilling unit, and correcting the COP to obtain real-time dynamic performance parameters of the unit; s4, control strategy generation: optimizing the energy consumption of the water system to obtain an optimal operation strategy of the water system; and S5, controlling execution. By the adoption of the technical scheme, the optimal energy efficiency can be achieved, accurate matching of supply and demand of the cooling capacity can be achieved, and user experience is improved.

The invention discloses an intelligent constant-humidity control FFU integrated system and a dust-free workshop application method thereof, and relates to the technical field of workshop application, and the method comprises an environment sensing unit which is used for collecting internal and external environment parameters and equipment operation states of a workshop in real time; the prediction unit is used for training and generating a model with a time sequence prediction capability by fusing historical production data and real-time environment fluctuation characteristics so as to output a temperature and humidity change trend and a key adjustment time window of each partition of the workshop in a future time period; the decision-making unit is used for dynamically selecting a target operation strategy from a process priority mode, an energy-saving mode and an emergency mode based on real-time production process requirements, an environment sensitivity threshold value and an energy consumption constraint condition; the parameter optimization unit is used for performing wind field parameter adjustment on the FFU unit under the target operation strategy, and minimizing system energy consumption while maintaining uniform distribution of temperature and humidity; adjustment comprises fan rotating speed gradient configuration, air outlet angle cooperative control and airflow circulation path optimization.

The invention provides a conference room environment regulation and control method and system, a medium and a product. In the method, an environment regulation and control system firstly determines a target temperature according to an external environment temperature, and then carries out temperature regulation and control in advance in combination with reservation time. When the conference is carried out, the environment regulation and control system carries out targeted monitoring on the temperature of different areas by dividing the air outlet area and the non-air outlet area in the conference room, and it is ensured that the temperature imbalance phenomenon is found in time. When the regional temperature difference between the air outlet region and the non-air outlet region reaches a temperature difference threshold value, the environment regulation and control system determines the regulation sequence according to the number of people in the region and the regional temperature difference, and it is ensured that resources are preferentially used for the region with the larger influence. And finally, the environment regulation and control system calculates the air volume and the air direction by combining the space parameters of the to-be-regulated area and regulates and controls the air volume and the air direction in sequence, so that the temperature of each area synergistically approaches a target value. According to the method, the temperature difference of different positions of the conference room is effectively relieved, and the balance and comfort of the whole environment are improved.

A ventilation system including a ventilator; and an outdoor unit, wherein the ventilator includes a housing including a first intake, a second intake, a first outlet and a second outlet, a plurality of dampers to change flow paths of air flowing through the housing, first and second air blowers, a heat exchanger in the housing, and a processor to control the dampers and first and second air blowers to form a first flow path in which outside air flows through the heat exchanger, or form a second flow path in which room air flows through the heat exchanger, to thereby form a flow path in the ventilator, while air flows through the flow path, control the outdoor unit to form frost on the heat exchanger, and control the outdoor unit to stop operating based on a preset frosting termination condition so that the frost melts to clean the heat exchanger.

The invention discloses an air conditioner intelligent regulation and control method and device based on a comfort model. The method comprises the steps that firstly, the indoor environment temperature and the human body temperature are collected in real time through a sensor module; then, an environment comfort model to be used in a temperature interval corresponding to the indoor environment temperature is determined, and meanwhile, a human body comfort model to be used in a temperature interval corresponding to the human body temperature is determined; inputting the indoor environment temperature into a to-be-used environment comfort degree model to obtain an indoor environment comfort degree value, and inputting the indoor environment temperature and the human body temperature into a to-be-used human body comfort degree model to obtain a human body comfort degree value; and air conditioner control parameters are determined based on the indoor environment comfort level value and the human body comfort level value. The air conditioner can be controlled according to changes of the indoor environment and changes of the human body temperature of the user, and therefore the experience comfort of the user is improved.

The invention discloses a personalized comfortable air conditioning system based on AI visual identification, and belongs to the technical field of air conditioners, and the personalized comfortable air conditioning system comprises a data acquisition module used for acquiring multi-modal real-time data of a user according to AI vision; the data processing module is used for processing the multi-modal real-time data of the user and determining multi-modal fusion data of the user; the analysis and prediction module is used for constructing a personalized comfortable air conditioner demand prediction model to analyze the multi-modal fusion data of the user and determining a personalized comfortable air conditioner demand prediction result; and the comfort regulation and control module is used for dynamically adjusting air conditioner operation parameters to meet the requirement of a user for air conditioner comfort experience. The problem that in the prior art, personalized and comfortable air conditioner adjusting experience cannot be provided for a user based on AI visual recognition, and the use feeling of the user is low is solved. Personalized and comfortable air conditioner adjusting experience can be provided for the user on the basis of AI visual recognition, the use feeling of the user is improved, and the user requirement can be well met.

The embodiment of the invention provides a control method and system of an air conditioner control system and a storage medium, and belongs to the field of air conditioner control. The method comprises the following steps: receiving first detection data of a passive infrared sensor, second detection data of a visual sensor and third detection data of a multi-path detection sensor; determining the temperature confidence of the target object according to the first detection data; determining the attitude confidence of the target object according to the second detection data; according to the third detection data, the air supply path interference confidence coefficient of the target object is determined; performing confidence coefficient weighting processing according to the temperature confidence coefficient, the attitude confidence coefficient and the air supply path interference confidence coefficient to obtain a target object confidence coefficient; when the confidence coefficient of the target object is smaller than or equal to a preset first confidence coefficient threshold value, the visual sensor and the multi-path detection sensor are controlled to enter a dormant state; otherwise, the air conditioner power parameters and / or the air supply path are / is adjusted. According to the embodiment of the invention, energy consumption and use experience can be considered.

The invention relates to the technical field of air purification, in particular to a negative oxygen ion dynamic air purification strategy and system.The negative oxygen ion dynamic air purification strategy comprises the following steps that on the basis of linkage of particulate matter concentration and multiple environmental parameters, influences of airflow, pressure, temperature and humidity and personnel flow on particulate matter distribution are analyzed, and formaldehyde and harmful gas parameter fluctuation trends are combined; pollution changes and equipment response grades are judged, the release path, frequency and power of the negative oxygen ion generator are adjusted, and ion release adjustment parameters are output. Data such as multi-element particulate matter concentration, airflow state, environmental pressure, temperature and humidity, personnel flow and the like cooperatively participate in monitoring and judgment, particulate matter grading characteristics are linked in real time through environmental dynamic factors, fluctuation trends of multiple pollutants in air are jointly calculated, high-risk change stages are actively recognized, purification response grades are dynamically output, and the purification effect is improved. The ion release direction and power are adjusted in an automatic linkage mode, the purification response changes along with space pollution hot spots, and diversified pollution distribution scenes are effectively covered.

The invention discloses a sleep control method for an intelligent air conditioner, a medium, equipment and the intelligent air conditioner, and relates to the technical field of air conditioners. The method comprises the following steps: acquiring indoor environment temperature detected by a temperature sensor, indoor environment brightness detected by a photosensitive sensor, an indoor personnel detection result of a radar and an indoor sound data acquisition result of a voice sensor; when the intelligent air conditioner is not in the sleep mode, whether the intelligent air conditioner is controlled to enter the sleep mode or not is judged according to at least one of the indoor environment brightness and the indoor sound data collection result; and when the intelligent air conditioner is in the sleep mode, sleep control is conducted on the intelligent air conditioner according to at least one of the indoor environment temperature, the indoor environment brightness, the indoor person detection result and the indoor sound data collection result. Therefore, sleep control over the intelligent air conditioner can be achieved.

The invention discloses a heating, ventilation and chilled water cooperative control method and system based on a double-branch deep and shallow feature fusion neural network, and the method comprises the steps: obtaining and preprocessing the historical operation data of a heating, ventilation and chilled water system, and forming standardized training data; a double-branch deep and shallow feature fusion neural network model is trained based on the standardized training data, and the model realizes equipment collaborative prediction through a cold water host load prediction branch and a freezing pump frequency prediction branch in combination with a deep and shallow feature fusion mechanism; acquiring environmental parameters in real time, inputting the environmental parameters into the trained model, and outputting a cold water host load predicted value and a freezing pump frequency predicted value; and correcting the predicted value based on a physical constraint correction algorithm, and outputting an optimization control instruction. The technical problem of poor control reliability caused by insufficient equipment collaboration, insufficient feature extraction and lack of physical constraints in the prior art is solved.

Systems and methods for executing an IAQ analysis of a building. One system includes a controller including memory and one or more processors configured to obtain IAQ data from one or more sensors within the building, wherein the IAQ data is associated with at least one of a plurality of environment species, obtain BAS data, identify one or more unknown parameters from the IAQ data and BAS data of two or more of the plurality of environment species, estimate the one or more unknown parameters based on inputting the IAQ data and the BAS data into an optimization model, and wherein the optimization model analyzes predicted concentrations of the plurality of environment species subject to the two or more of the plurality of environment species evolving according to a single-species concentration model, and provide the estimated one or more unknown parameters to one or more predictive models.

Disclosed in the present invention is a heat recovery ventilator, comprising a frame, a housing, a heat exchange rotor, a central shaft, a plurality of shaft seals, an outer rotor motor, and a motor support; the housing is mounted on the frame, the heat exchange rotor is rotatably mounted in the housing, the heat exchange rotor is fixed to an outer rotor motor housing by means of an inner fixing support, two ends of the central shaft are fixedly mounted on the frame, and the plurality of shaft seals are connected between the housing and the heat exchange rotor. The outer rotor motor is mounted in the middle of the inner cavity of the heat exchange rotor by means of the motor support, and a shaft of the outer rotor motor is fixedly connected to the central shaft. In the present invention, since the outer rotor motor provides rotating power for the heat exchange rotor, the structure is simple, and since an outer cylinder and an inner cylinder in the heat exchange rotor are conical cylinders, when the heat exchange rotor rotates, the centrifugal forces acting on dewdrops attached to the inner cylinder and the outer cylinder are different, the dewdrops concentrate in the axial direction under the action of the centrifugal forces and are transferred to a cold air passage at the shaft seals for evaporation, the flow velocity of the dewdrops is higher, and the heat exchange effect is better.

The invention relates to an air conditioner control method and device, an air conditioner and a computer readable medium. The method comprises the steps that the environment temperature of the space where a target air conditioner is located is obtained; under the condition that the environment temperature meets the starting condition of the target air conditioner, whether a target object exists in the space where the target air conditioner is located or not is detected based on the through-wall prevention strategy; and under the condition that the target object exists in the space where the target air conditioner is located, the target air conditioner is controlled to start running. Whether the target object is located in the space where the air conditioner is located or not is accurately recognized through the through-wall prevention strategy, outdoor Bluetooth signal interference is avoided, energy waste caused by unnecessary startup is avoided, the through-wall false triggering probability is remarkably reduced, the air conditioner control accuracy and energy saving performance are improved, and the air conditioner control cost is reduced. The technical problem of outdoor false triggering caused by Bluetooth signal wall penetration is solved.

The invention discloses an energy output power adjusting method based on artificial intelligence and big data. The method comprises the following steps of collecting environment data and personnel flow information in a space in real time; generating a people flow model through big data analysis and a machine learning algorithm; the operation state and the output power of the energy equipment are automatically adjusted according to the people flow model and the environment data, and precise environment control and energy saving are achieved. According to the invention, environment data is collected in real time through the data acquisition module, and an optimal energy adjustment strategy is generated by using big data analysis and a machine learning algorithm. The system has self-learning and self-adaptive capabilities, and can automatically optimize an adjustment strategy according to environmental changes and user habits, so that energy consumption is remarkably reduced, and user experience is improved.

The invention discloses a thermal environment and air quality self-adjusting intelligent emergency rescue cabin and method, and relates to the technical field of emergency rescue. The core of the method is that firstly, heat loss characteristics of the rescue cabin are learned through a simulated environment, and a standard loss rate is established; then, a target temperature interval is set, and based on comparison between the temperature loss rate monitored in real time and a standard value, hierarchical temperature control modes such as dormancy, low-power-consumption maintenance or dynamic balance are dynamically selected. Furthermore, by integrating vital sign monitoring, the target temperature can be dynamically adjusted according to parameters such as the core body temperature, blood oxygen and blood pressure of a patient, medical intervention modes such as active cooling and shock rewarming are started, and safe rewarming is achieved in the shock rewarming mode in the mode that a core area is heated through directional radiation. The system is also internally provided with a multi-rule priority arbitration mechanism. The cabin body comprises a sensor, an air conditioner, vital sign monitoring equipment and a directional heating plate. Unification of energy conservation, temperature stabilization and precise medical intervention is achieved, and the intelligent level and the safety guarantee capacity of emergency rescue are remarkably improved.

The invention relates to the technical field of heating ventilation air conditioner control and energy conservation, and discloses an energy-saving self-adaptive control method and system for a heating ventilation air conditioner. The method comprises the following steps: acquiring power consumption data and environment data in a building to obtain initial activity state distribution; air conditioner related energy consumption characteristics are separated according to the activity state distribution; identifying a specific activity state in combination with a user behavior database; determining a target cooling capacity output range according to the activity type and the personnel density; if the range exceeds the current setting, recalculating the operation parameters in combination with the external climate data, and generating an adjustment instruction; dynamic adjustment is executed, the comfort degree is monitored, and operation feedback is obtained; and according to the feedback continuous optimization operation strategy, energy consumption optimization is realized. According to the method, air conditioner operation can be dynamically adjusted according to the real-time activity state and the external environment, and energy consumption is effectively reduced while the comfort level is guaranteed.

An environment control device includes a control unit usable to control an environment adjustment portion that controls a thermal environment of a space. The control unit estimates a sensation indicating comfort or discomfort of a target person based on sensation information about the target person in the space. The control unit determines, based on an appearance frequency of each sensation corresponding to a thermal index value as a value of thermal index, a range of the thermal index value indicating comfort or discomfort as a sensation region. The control unit sets a target value of the thermal index in the space based on the sensation region. The control unit determines a duration of comfort or discomfort sensation. The control unit determines the sensation region by excluding the thermal index value where the duration of the comfort or discomfort sensation is shorter than a predetermined time.

The invention relates to an indoor air lake purification system and method based on layered detection and intelligent airflow control. Comprising a layered detection system used for monitoring air quality parameters, temperature and humidity at different heights in real time; the intelligent control system is used for calculating density difference and pressure difference distribution of indoor air based on the data of the layered detection system and generating a control instruction according to a thermodynamic model; the airflow adjusting system is used for actively adjusting and controlling the flowing state and density distribution of indoor air; the thermodynamic driving module forms a vertical temperature difference of 3-10 DEG C and a horizontal pressure difference of 5-20 Pa by adjusting the air inlet temperature and pressure, and the natural convection effect of air is enhanced. From the perspective of the system, directional removal of pollutants is realized, the purification efficiency is remarkably improved, the energy consumption is greatly reduced, pipeline-free low-cost installation is realized, and the working modes are dynamically switched according to the activity range of personnel and seasonal change so as to create a comfortable and healthy living environment.

A method, controller and computer program product for operating an industrial air cleaning system (1) arranged within a facility (100), perimeters (P1-n) being defined within the facility (100). Operating the industrial air cleaning system comprises a propagation assessment sequence (A) and a preemptive action sequence (B). The propagation assessment sequence (A) comprises detecting an actionable instance of an industrial activity (X) within the facility (100); and identifying impacted perimeters (PI1-m) estimated as impacted by the actionable instance. The preemptive action sequence (B) comprises identifying a subset (S10) of air cleaning devices (101-n) associated with the impacted perimeters (PI1-m); determining setpoint parameters of the subset (S10) of air cleaning devices (101-n) based on data representative of the actionable instance and indoor air quality target values; and controlling the subset (S10) of air cleaning devices (101-n) in accordance with the setpoint parameters.

Systems and methods for executing an IAQ analysis of a building. One system includes a controller including memory and one or more processors configured to obtain IAQ data from one or more sensors within the building, wherein the IAQ data is associated with at least one of a plurality of environment species, obtain BAS data, identify one or more unknown parameters from the IAQ data and BAS data of two or more of the plurality of environment species, estimate the one or more unknown parameters based on inputting the IAQ data and the BAS data into an optimization model, and wherein the optimization model analyzes predicted concentrations of the plurality of environment species subject to the two or more of the plurality of environment species evolving according to a single-species concentration model, and provide the estimated one or more unknown parameters to one or more predictive models.

An HVAC control system having a cloud-based optimization engine in communication with a local building hub that interfaces with the building HVAC system and room units. The cloud-based optimization engine implements an optimal and predictive control strategy to integrate occupancy prediction, weather forecasting, and modeling of indoor infection risk, indoor air quality, and building energy consumptions. The control strategy includes a model-based predictive control and a model-free reinforcement learning approach. The control strategy considers outdoor weather (both thermal and air quality) conditions, indoor occupancy and requirements for IAQ and infectious risk reduction to decide whether outdoor air should be introduced and how much fresh air will be introduced into the space. Communications with the building hub allow the local HVAC unit to be driven according to the optimization plan. Individual room sensing units can provide local sensor data to the cloud-based optimization engine.

The evaluation method of thermoregulatory function is characterized by comprising: a process of acquiring an autonomic nerve index of a subject; a process of acquiring a sweating index of the subject; and an evaluation process of evaluating a thermoregulatory function of the subject using the autonomic nerve index of the subject and the sweating index of the subject. Preferably, the autonomic nerve index comprises at least one of a heartbeat variation index and a pulse variation index, and the sweating index comprises at least one of a skin conductance and a sweating amount.