601 results about "Comfort levels" patented technology

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

The embodiment of the invention provides an energy-saving optimization system for heating, ventilating and air conditioning of an indoor ski field. The energy-saving optimization system comprises a multi-source sensing layer, an edge computing layer, a cloud decision-making layer and an equipment execution layer. The multi-source sensing layer is used for collecting multi-source data such as weather, passenger flow, temperature and humidity and equipment state; the edge calculation layer carries out fusion processing on the data and generates a load prediction result through a load prediction mechanism; the cloud decision-making layer generates an optimization control instruction based on a multi-agent deep reinforcement learning and model prediction control optimization strategy; and the equipment execution layer receives and executes the instruction and feeds back the equipment state. Through a multi-layer collaborative optimization architecture, accurate load prediction and equipment intelligent collaborative control are realized, five-stage stepped optimization and a dynamic priority mechanism are adopted, the energy efficiency of the system is remarkably improved, the energy consumption is reduced while the environmental comfort is ensured, and the economical efficiency and the stability of system operation are effectively improved.

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 is suitable for the technical field of automobile intelligent control, and provides an air conditioner seat collaborative cooling control method based on a neural network, which comprises the following steps of: constructing a human body-environment comfortable temperature original index model by collecting a large amount of human body and environment temperature distribution data in advance; on the basis, data acquisition and model comparison are carried out on the real-time human body temperature, the environment temperature and the temperature in a passenger compartment before the passenger gets on the bus, so that the heat comfort in the bus is pre-adjusted most reasonably before the passenger gets on the bus, and a method for cooperatively controlling ventilation and heating of an air conditioner and a seat is utilized; the two are combined to improve the thermal comfort of the passenger and the passenger compartment. And meanwhile, real-time sensing data is quickly processed when a passenger feels uncomfortable in temperature during riding and adjustment is carried out, the body temperature of the passenger and the ambient temperature of a passenger compartment are recorded and are input into a model for correction, so that the body comfort requirement of the passenger is met in a more personalized manner, and the comfort of the passenger in the vehicle running process is improved.

The invention discloses an air conditioner control method and system, electronic equipment and a storage medium, and relates to the field of air conditioner control. The method comprises the following steps: determining an energy-saving award coefficient and a comfort award coefficient according to a current time period and a current season; constructing an energy-saving award function according to the energy-saving award coefficient, constructing a comfort award function according to the comfort award coefficient, and constructing an instant award function according to the energy-saving award function, the comfort award function and a punishment mechanism; state data and action data of operation of the air conditioner are obtained, the state data comprise the indoor temperature, the outdoor temperature and the temperature, the mode and the air speed set by a user, and the action data comprise air speed adjustment, mode adjustment and temperature adjustment; and the optimal action of the next state is determined according to the state data, the action data and the instant reward function, and the operation parameters of the air conditioner are adjusted according to the optimal action. By implementing the technical scheme provided by the invention, a more efficient and environment-friendly air conditioner control method is provided.

The embodiment of the invention discloses a self-adaptive air conditioner heating control method and system based on multi-source perception.The method comprises the steps that multi-source environment data such as indoor environment data, outdoor environment data and air conditioner operation data are collected in real time, and active adjustment behaviors and environment state data of a user are combined; a personalized comfort model is established and continuously updated through a machine learning algorithm, and a dynamic target comfort temperature interval is output to reflect comfort temperature preferences of a user in different environments; the multi-source environment data and the target comfortable temperature interval serve as input, maximization of user comfort, minimization of energy consumption and reduction of compressor starting and stopping times serve as targets, rolling optimization calculation is conducted through an optimization algorithm, and an air conditioner control instruction set containing a dynamic target temperature set value, a compressor operation instruction and a fan rotating speed instruction is dynamically generated; and executing an instruction set, monitoring an effect and user feedback, and feeding data back to the model establishment and optimization calculation step to realize self-adaptive control.

The invention relates to the technical field of smart home, and discloses an AI-based fan intelligent temperature regulation control system, which comprises a multi-dimensional data acquisition module for acquiring environment temperature, humidity, air quality, illumination intensity and human body state data; the data fusion and preprocessing module is used for carrying out denoising, standardization and time synchronization on the multi-dimensional data and fusing the multi-source data; the AI decision and control module is used for generating a speed regulation and mode control instruction of the fan based on the human body comfort evaluation model and an AI algorithm; and the feedback optimization and execution module is used for executing the control instruction. Through a multi-dimensional data perception and fusion technology, comprehensive monitoring of environment temperature and humidity, air quality and a human body state is realized. The AI intelligent regulation and control algorithm is combined, the fan speed and mode are dynamically adjusted, and the user comfort and energy consumption are balanced; through edge calculation and cloud optimization, real-time response and continuous adaptive optimization of the system are ensured, and the accuracy and stability of the system are improved.

The invention relates to the technical field of smart home, and discloses an electric blanket system capable of adjusting calorific value by self-adaption to environment temperature, comprising a sleep sensing module used for collecting physiological signal data of a user; the state recognition module is used for recognizing the current sleep state of the user; the temperature target generation module is used for determining a corresponding target temperature value according to the current sleep state; the control calculation module is used for calculating a control instruction of each heating area; the multi-area heating execution module is used for performing heating control on the plurality of independent heating areas; and the temperature acquisition and feedback module is used for acquiring the real-time temperature of each heating area and feeding back the temperature to the control calculation module. Through linkage of the AI housekeeper and the external electronic bracelet, adaptive adjustment of the intelligent temperature control system is realized, a temperature control strategy is dynamically optimized according to real-time temperature data, user behaviors and environmental changes, limitation of a traditional static scheme is avoided, personalized temperature adjustment is provided, and flexibility and comfort are improved.

The invention discloses a temperature control method and system based on a time sequence-residual module cascade algorithm, and belongs to the field of heating and ventilation design and automatic control design. The method comprises the following steps: acquiring environmental data in real time by using a sensor system, and generating a data set suitable for model training and prediction through data preprocessing and feature extraction; a deep learning model is awarded, wherein a time sequence-residual module cascade model is adopted for temperature prediction; the network structure captures the long-term trend of a time sequence by using the LSTM, the Res residual module extracts local fluctuation features by using a convolutional layer, and the local fluctuation features and the Res residual module realize cooperation of a time sequence dimension and a space dimension through feature parameter jump connection remodeling, so that the capability of predicting the future temperature change trend is remarkably improved, and the prediction efficiency is improved. The indoor temperature can be adjusted in real time to maintain comfortable environmental conditions. According to the intelligent indoor temperature prediction method, the comfort degree of the indoor environment is improved, the energy consumption is remarkably reduced, the remarkable energy-saving effect is achieved, and the positive promotion effect on environment protection is achieved.

The invention provides an air conditioner and a control method and device thereof, a storage medium and a computer program product, and the method comprises the following steps: detecting whether a person is in a room or not, and detecting whether a pet exists in the room or not when it is detected that no person is in the room; if it is detected that the pet exists, the air conditioner is controlled to be switched to a preset mode; collecting an image of the pet; determining whether the pet has a preset behavior or not according to the collected image of the pet; if it is determined that the pet has the preset behavior, an air conditioner and / or an air purifier in the air conditioning system are / is controlled; and / or, acquiring hair humidity detection data of the pet; according to the acquired hair humidity detection data of the pet, judging the dry and wet state of the hair of the pet; and controlling an air conditioner and / or a dehumidifier and / or a humidifier in the air conditioning system according to the judged dry and wet state of the hair of the pet. According to the scheme provided by the invention, the comfort level of the pet in indoor life can be improved.

The invention relates to a method and a system for optimizing indoor thermal comfort of a building based on machine learning, and the method for optimizing the indoor thermal comfort of the building based on machine learning is used for maintaining the indoor thermal comfort of the building in cooperation with indoor temperature control equipment of the building. Comprising the following steps: S1, establishing a BIM three-dimensional information model of a building indoor structure; s2, acquiring indoor environment data of the building by using a sensor, and constructing a digital twin platform in combination with the BIM three-dimensional information model; s3, preprocessing the acquired indoor environment data by using a digital twin platform; according to the method, the indoor environment data of the building is analyzed and predicted by the machine learning technology after being preprocessed, the indoor future environment conditions of the building are accurately predicted, the adjustment data of the indoor temperature control equipment of the building in the future time period are obtained, and therefore the purpose of rapidly and accurately adjusting the thermal comfort degree in each time period is achieved.

The invention discloses an intelligent temperature control energy-saving system and method based on personnel position detection and prediction. The system monitors indoor personnel distribution and temperature and humidity in real time through the human body and environment sensing module; the behavior prediction module utilizes an LSTM deep learning model to analyze the historical moving track of the user and predict the next target room and the arrival time of the user in combination with the environment context; the environment regulation and control module starts equipment such as an air conditioner in the target room in advance to adjust to a comfortable state; and the energy efficiency optimization module is used for implementing energy-saving control on the unmanned room. According to the method, the crossing from passive reaction to active prediction is realized, and the energy utilization efficiency of the home environment is remarkably improved on the premise of ensuring the comfort.

The invention relates to an intelligent mattress water temperature control method and system based on artificial intelligence. Body temperature data and environment temperature data of a user are collected in real time through a plurality of sensors in a mattress. According to the collected data, the current comfortable temperature interval of the user is calculated through a preset comfortable temperature model. And an initial water temperature regulation control strategy is generated in combination with the calculated comfortable temperature interval and historical sleep data of the user, and the strategy is used for controlling a temperature control unit in a water circulation system in the mattress. In the water temperature adjusting process, the system continuously monitors the body temperature change, the environment temperature change, the sleep state and the mattress surface temperature of the user and records generated sleep data. Through the pre-trained neural network model, the personalized temperature control strategy is generated, and finally the strategy is applied to the temperature control unit in the water circulation system, so that accurate water temperature adjustment based on the actual sleep state and the temperature requirement of the user is realized, and the sleep comfort of the user and the intelligent level of water temperature control are improved.

The invention relates to the crossing field of biothermodynamics and dynamic environment control, and discloses a space thermal microclimate multi-target regulation and control method, device and system, a medium and a product. The method comprises the following steps: acquiring physiological parameters (including effective dressing thermal resistance and local sweat gland density of posture correction) of a passenger, environment space-time parameters and light environment parameters through a biological characteristic sensor, an environment sensor and an optical sensor; constructing a dynamic human body thermal comfort model library, and adopting a feature coding-parameter decoding mechanism to match a target thermal comfort model; generating a hierarchical regulation strategy based on the difference between the local comfortable temperature and humidity interval and the real-time thermal environment sensing parameter; and the refrigerant circulation system, the fluid circulation system and the optical radiation system are cooperatively controlled to realize local microclimate regulation and control. According to the method, the problems of inaccurate thermal comfort modeling and low multi-system cooperation efficiency in a transient environment are solved, the energy efficiency ratio is improved, and the comfort of passengers in a cabin is remarkably improved.

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.

The invention provides an air conditioner control method and device, an air conditioner and a storage medium. The air conditioner control method comprises the steps that the current state of the air conditioner is obtained; determining a current comfort level according to the current state; constructing a potential state combination based on the current state; determining comfort corresponding to each potential state according to the potential state combination; and determining a target state according to the current comfort level and the comfort level corresponding to each potential state, and operating according to the operating parameters corresponding to the target state. According to the method, the current comfort level and the comfort level corresponding to each potential state in the potential state combination are determined according to the current state of the air conditioner, so that the air conditioner is controlled according to the comfort levels of the potential states and the current comfort level, and the indoor comfort level is adjusted more accurately.

The invention discloses a self-adaptive adjusting method and device for a vehicle seat, equipment and a medium. The method comprises the steps that first temperature data detected by a temperature sensor in a vehicle and first humidity data detected by a humidity sensor in the vehicle are obtained; detecting first physiological feature data of a passenger of the target seat; inputting the first temperature data, the first humidity data and the first physiological feature data into a trained comfort level identification model, and predicting the comfort level category and the key index category of the passenger through the comfort level identification model; if it is determined that the comfort level category is uncomfortable, a to-be-adjusted assembly is determined from the heating assembly and the ventilation assembly according to the key index category; and controlling the to-be-adjusted assembly to adjust the temperature or humidity of the target seat. Adjustment of heating and ventilation of the vehicle seat can be automatically achieved, and the riding experience is improved. The method can be widely applied to the technical field of vehicles.

A device located within a user environment may be used to measure one or more environmental conditions within the user environment. For example, the sensor device may measure the temperature, humidity, light intensity, color temperature, and / or the like. The sensor device may periodically measure the environmental conditions, and may periodically transmit the values of the measured environmental conditions to a computing device. A mobile device associated with a user may receive the measured values from the sensor device when the mobile device is within range of the sensor device, and may present a survey to the user that includes one or more questions that prompt the user to report their comfort level with respect to the measured environmental conditions. The mobile device and / or another computing device may build a profile for the location and / or the user based on the values and the user's reported comfort levels.

The invention provides an intelligent closestool temperature adjusting method, a server, a medium and a program product, and relates to the technical field of intelligent control. The method comprises the steps that the initial skin temperature when a user makes contact with a seat ring and the indoor environment temperature are collected, a temperature change curve is established to determine the skin temperature sensing condition and the optimal temperature adjusting time, the two are combined to calculate the temperature sensitivity coefficient, and the target temperature is determined according to the temperature sensitivity coefficient and heated to the preset weight temperature within the optimal time. The skin temperature rising condition is detected to determine the optimal temperature, and heating is continued if the skin temperature does not rise. The corresponding relation between the optimal temperature and the use time period, the environment temperature and the sensitivity coefficient is stored in a database, when the same user is detected next time, the heating parameter is called according to the current environment temperature to adjust the temperature, and by implementing the method, the heating temperature is automatically adjusted according to the individual difference and the environment temperature, and the comfort level and the energy saving performance are improved.

The invention discloses an intelligent analysis method for a sleep-aiding scheme driven by intelligent perception, and relates to the technical field related to data processing.The method comprises the steps that pressure sensing data and temperature sensing data of sleep of a user are sensed and collected through a sensor array arranged in sleep equipment in advance; performing integrated comfort analysis to obtain pressure comfort information and temperature comfort information of the user; performing screening and body position change analysis on the first user body position information sequence and the second user body position information sequence to obtain a body position change frequency; analyzing and calculating the sleep-aiding comfort level of the sleep-aiding scheme to obtain the sleep-aiding comfort level as an analysis result of the sleep-aiding scheme. The technical problems that in the prior art, it is difficult to comprehensively perceive and analyze the sleep state of the user to reflect the comfort level of the user, dynamic optimization based on body position changes is lacked, and consequently the scientificity and individuation of the sleep scheme of the user are insufficient are solved, and the technical effect of improving the analysis scientificity and individuation adaptation capacity of the sleep scheme is achieved.

The invention is suitable for the technical field of air conditioners, and provides an air conditioner intelligent regulation and control method which comprises the steps that outdoor environment data, indoor environment data and personnel state data are collected in real time, all the data are fused, and a comprehensive data set is generated; constructing a dynamic temperature gradient field based on the comprehensive data set; dividing functional areas, and calculating an influence relation matrix in combination with the dynamic temperature gradient field; taking the influence relation matrix as a core constraint condition, and adopting a multi-objective optimization algorithm to obtain an air conditioner regulation and control parameter set; and on the basis of the air conditioner regulation and control parameter set, the output parameters of all the air conditioner single bodies are gradually adjusted through a switching mechanism, dynamic global optimization of the air conditioner system on multiple targets such as energy saving, comfort and equipment service life is achieved, and the problems that regulation and control are lagged, energy consumption is too high, the comfort degree is not uniform, and equipment loss is large are effectively solved.

The invention provides an air conditioner control method and device and an air conditioner. The control method comprises the steps that a signal for controlling the air conditioner to execute a direct blowing prevention mode is received, and the positions of indoor personnel in the indoor environment are obtained; according to the positions of the indoor people, all air outlet areas are divided into direct blowing prevention areas and normal air outlet areas, and the direct blowing prevention areas correspond to the positions of the indoor people; and the air outlet direction of the direct blowing prevention area is controlled to avoid the indoor personnel to achieve direct blowing prevention, and the air outlet state of the normal air outlet area is controlled according to the refrigeration requirement or the heating requirement of the air conditioner. According to the control method and device of the air conditioner and the air conditioner, it is guaranteed that the refrigerating effect and the heating effect of the air conditioner are not affected while the direct blowing prevention requirement of a user is met, that is, the direct blowing prevention requirement and the heating / cooling requirement of the user are met at the same time, the use experience of the user is greatly improved, and the indoor comfort level is guaranteed.

The invention discloses an air conditioner air outlet control method and device based on environmental parameters. The method comprises the steps that an environmental parameter set corresponding to a target area is determined; the environment parameter set corresponding to the target area comprises external environment parameters corresponding to the target area and indoor environment parameters of the target area; according to the environment parameter set corresponding to the target area, an external environment influence coefficient corresponding to the target area is analyzed, and the external environment influence coefficient is used for representing the influence relation between the external environment parameters and the indoor environment parameters; according to the environment parameter set corresponding to the target area and the external environment influence coefficient, air outlet control parameters corresponding to a target air conditioner of the target area are generated; and according to the air outlet control parameters corresponding to the target air conditioner, the target air conditioner is controlled to execute air outlet operation corresponding to the air outlet control parameters. Therefore, the air conditioner air-out control flexibility can be improved, the air conditioner air-out control accuracy is improved, and the environment comfort level can be improved.

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 provides a vehicle comfort control method and device and a storage medium. Firstly, the target air outlet temperature of an air conditioner is determined; according to the human body comfort model, the radiation temperature when the fireplace or the seat is not started for heating is calculated, the thermal comfort evaluation index is calculated, the thermal comfort evaluation index is in the human body thermal comfort interval by adjusting the air conditioner outlet air temperature, and under the condition that the human body thermal comfort interval is maintained, the thermal comfort evaluation index is obtained. The corrected in-vehicle target head temperature after fireplace heating or seat heating is started is calculated based on the influence of heating of different gears of an in-vehicle fireplace or / and seats on the comfort degree of the human body, then the corrected air conditioner target air outlet temperature is determined, and the mapping relation between the different gears of the in-vehicle fireplace or seats and the corrected air conditioner target air outlet temperature is established. And the comfort level of the vehicle is controlled. Through cooperative control of the air conditioner and the fireplace or the seat, energy consumption of the air conditioner is reduced, and meanwhile the body surface temperature can be rapidly increased through fireplace heating or seat heating.

The invention discloses a central air conditioner control system which comprises at least one outdoor unit and at least one indoor unit in communication connection with the outdoor units through communication buses. The controllers can communicate with one another and are respectively connected with the communication bus; the temperature and humidity sensor is used for collecting indoor temperature data and humidity data; wherein the controller is used for storing current regional information, weather information and equipment operation records; the controller is also used for establishing a thermal comfort evaluation / recommendation model and an intelligent prediction schedule model by using a machine learning algorithm; the controller is further used for forming recommended control parameters according to the set requirements of the user and sending the recommended control parameters to the outdoor unit or the indoor unit. According to the invention, based on the information of the area where the user is located, the weather information, the indoor environment information and the user information, a machine learning algorithm is utilized to establish a thermal comfort evaluation recommendation model and an intelligent prediction schedule model, the models are combined to form a recommendation control strategy according to a scene set by the user, and optimal control parameters are provided for the user. And in cooperation with the energy-saving effect of the central air conditioning equipment, the purpose of efficient and energy-saving operation is achieved on the premise that the comfort level of a user is met.

The invention provides a sheep body temperature monitoring device and a heat stress management method, and the method comprises the steps: obtaining a real-time body temperature signal based on the sheep body temperature monitoring device, obtaining real-time environment information based on an environment collection device, building a temperature compensation model according to the real-time body temperature signal and the environment information, and obtaining a real-time temperature change curve, the method comprises the following steps: acquiring a real-time temperature change curve, acquiring signal characteristics according to the real-time temperature change curve, comparing the signal characteristics with a preset reference value, calculating a real-time temperature change rate, constructing a heat stress evaluation model according to the signal characteristics and the temperature change rate, judging the heat stress state of a tested individual, and implementing heat management measures according to the heat stress state. The environment comfort level of animals in a farm can be improved, high-temperature stress generation and energy waste can be reduced, animal welfare guarantee can be provided for individual sheep in a high-temperature environment, and heat stress events can be effectively prevented and managed.

The invention relates to the technical field of energy-saving control, and discloses a self-adaptive energy-saving control method and system for building heating and ventilation equipment based on digital twinning. The method comprises the steps of collecting temperature and humidity in a building, heating and ventilation equipment operation, external environment and personnel flow data, extracting energy consumption fluctuation characteristics and performing coupling analysis on the energy consumption fluctuation characteristics and equipment operation data. A distributed lag regression model is constructed in combination with external environment data, the environment influence weight and trend are calculated, and a high-dynamic region is identified through fuzzy reasoning. Energy consumption is predicted based on high-dynamic area data, a waste value is calculated, equipment operation parameters are optimized, and a target power sequence is generated through population iteration. An adjusting instruction is generated through analysis and deployed to a control system, thermal sensation feedback and instantaneous power data are collected, comfort evaluation is conducted, and the adjusting instruction is updated for optimization control. According to the method, dynamic balance of energy conservation and comfort can be realized.

To provide a presentation method enabling a user of an air conditioner to understand from what kind of viewpoint a preset temperature to be set in the air conditioner is determined.SOLUTION: A presentation method comprises a presentation step where a computer presents a first matrix in which a first axis is set as a preset temperature of an air conditioner and a second axis is set as an outside air temperature. The presentation step presents the first matrix in a mode showing the preset temperature to be set on the air conditioner and determined on the basis of a parameter related to comfort of a user of the air conditioner and the change of the parameter.SELECTED DRAWING: Figure 13