CN107860076B - Multi-user dynamic temperature regulation central air conditioning system and method based on artificial intelligence - Google Patents

Abstract

The multi-user dynamic temperature-regulating central air-conditioning system based on artificial intelligence obtains temperature curve models which accord with different age groups, different professions, different departments and sexes through an information retrieval unit according to conditions that the sexes, the age groups, the professions and the working departments are used as retrieval temperature curve models, and then carries out weighted average on the temperature curve models of the different age groups, the different professions, the different departments and the sexes retrieved by the retrieval unit according to the personal information conditions of all office workers in an office area to obtain an optimal temperature curve model; the temperature controller controls the water flow or air quantity of the fan coil according to the current optimal temperature curve model, so that the office area temperature in different time periods in one day can be optimally adjusted through a large amount of data, and the comfort level of the office environment temperature is improved; the invention also provides a multi-user dynamic temperature adjustment central air-conditioning method based on artificial intelligence.

Description

Multi-user dynamic temperature regulation central air conditioning system and method based on artificial intelligence

technical field

The invention relates to the field of central air conditioners, in particular to a multi-user dynamic temperature regulation central air conditioner system and method based on artificial intelligence.

Background technique

A 2015 survey of 129 U.S. office workers found that 42 percent thought their building was too hot, and 56 percent thought it was too cold. We can now adjust the office to any temperature at will, but we cannot agree on a specific temperature.

Setting the right room temperature can improve job satisfaction and productivity at work and collaboration. Improperly set temperatures can lead to inefficient employees, obesity, and increased rates of metabolic disorders such as diabetes.

In workplaces around the world, people are often debating the temperature set in the office area. The relevant data shows that about 2% of the working time in the UK office is wasted on the debate related to the temperature of the air conditioner, and the economic waste caused by it every year. More than £13 billion, Australia's economic losses as a result amounted to $6.2 billion.

In fact, ambient temperature can not only affect work efficiency, but also change the way of thinking. Warmer environments are better for creative thinking, while cooler environments can help people focus more on repetitive and monotonous tasks; when ambient temperatures exceed 27 degrees Celsius (80.6 degrees Fahrenheit), our math ability declines.

Ambient temperature has a direct impact on collaboration, with people more likely to feel good about others in a warmer room and cold in a cold room.

Industry insiders have devised a set of criteria to calculate the number of employees who are dissatisfied at each temperature, known as the Predicted Percentage of Dissatisfied ("PPD"). To calculate PPD, most property managers use a standard formula from the 1960s that takes into account factors such as the clothing of the building occupants and the metabolic rate (the rate at which we generate heat), which is based on a body weight of 70kg of 40-year-old men. The optimal office temperature is roughly between 22 and 24 degrees Celsius (71.6 and 75.2 degrees Fahrenheit).

Everyone's metabolic rate is different at different times of the day, so the perception of temperature at different times of the day is also different. Women's metabolic rate is much slower than men's, and the appropriate office temperature is 3 higher than that of men. Celsius (5.4 degrees Fahrenheit), however, the metabolic rate currently used when controlling office temperature is based on a 40-year-old male weighing 70kg and therefore does not apply in today's co-working environment.

There are many office workers in each office area of the public office space, and each individual in each office area has different perceptions of temperature at different times of the day. However, there is often only one in each office area. The temperature regulator, after setting the temperature, the temperature in the office area is basically unchanged throughout the day, and cannot be adjusted according to the metabolic rate of the human body, and the setting temperature is relatively rigid. At the same time, who exercises control over the temperature in each zone has been controversial, and we often hear co-workers complaining and arguing about temperature settings, raising a range of topics about co-worker empathy and empathy.

At present, the temperature of the office air conditioner is generally around 20~24 degrees, which is acceptable to most people when they first go to work. After a few hours, within two hours before lunch and get off work, the energy consumption in the body More, many people will feel colder, especially during the lunch break after lunch. At low temperatures, when there is hunger, the body will use most of its energy to maintain body temperature, and our work efficiency will be seriously affected.

The invention fully considers the gender, age, metabolism, occupation and work department of the office staff, obtains temperature curve models of different age groups, different occupations, different departments and genders through a large amount of data, and performs weighting by the proportion of personnel in the office area. Fusion to obtain the optimal temperature curve model.

Fan coil units are ideal end products for central air conditioners. Fan coil units are widely used in hotels, office buildings, hospitals, commercial and residential, scientific research institutions and other places. Working principle: relying on the forced action of the fan, the air passes through the coil, and the air in the room where the unit is continuously recirculated, so that the air is cooled (heated) after passing through the cold water (hot water) coil, and the indoor temperature is lowered or raised. , to meet people's comfort requirements.

Control method: The STC series thermostat automatically controls the opening and closing of the STV series electric two/three-way valve according to the comparison and calculation of the set temperature and the actual detected temperature; it directly controls the three-speed conversion and start-stop of the fan, so as to pass the control system. The water flow or air volume achieves the purpose of constant temperature.

Adjustment method: Generally, it is air volume adjustment (adjusting the input voltage of the one-way capacitor speed regulating motor), and water volume adjustment is also used.

SUMMARY OF THE INVENTION

Aiming at the above-mentioned defects in the prior art, one problem to be solved by the present invention is that the present invention inputs the personal information of all persons in the office area into the information retrieval unit, and the information retrieval unit is based on gender, age, occupation and work. Department is used as a condition for retrieving the temperature curve model, through the information retrieval unit to obtain temperature curve models that match different age groups, different occupations, different departments and genders, and then according to the personal information of all office personnel in the office area, the retrieval unit retrieves the obtained temperature curve models. The temperature curve models of different age groups, different occupations, different departments and genders are weighted and averaged to obtain the optimal temperature curve model; the thermostat controls the water flow or air volume of the fan coil according to the current optimal temperature curve model, so as to pass a large number of The most suitable adjustment to the temperature of the office area at different time periods of the day can improve the comfort of the office environment temperature and reduce the debate among office personnel on the set temperature of the office area.

The present invention is realized by adopting the following technical solutions. The artificial intelligence-based multi-user dynamic temperature regulation central air-conditioning system designed for this purpose includes: a personal set temperature acquisition unit, a personal set temperature processing unit, a temperature curve model library, and an information retrieval unit , artificial intelligence unit, update unit and thermostat.

Personal information includes: name, gender, age group, occupation and work sector.

Personally set temperature collection unit: collect the temperature set by the individual at different time periods of the day, and transmit the temperature set by the individual to the server through wired or wireless transmission.

The temperature collection unit for personal settings can be wearable devices such as wristbands and watches, or mobile phones, tablets, and computers.

Personally set temperature processing unit: The server averages the temperature set by the individual at different time periods every day to obtain a personal temperature curve model.

Temperature curve model library: The server classifies and averages various stored personal temperature curve models according to gender, age group, occupation and work department, and obtains temperature curve models for different age groups, different occupations, different work departments and genders .

Information retrieval unit: According to one or more combinations of gender, age group, work sector and occupation as the conditions for retrieving the temperature curve model, the temperature curve model that meets the conditions is obtained through the retrieval unit.

Artificial intelligence unit: intelligently simulate the temperature curve models corresponding to emerging occupations that do not exist in the temperature curve model library, and obtain the temperature curve models corresponding to the most relevant occupations by extracting the characteristics of emerging occupations. Then, the temperature curve models corresponding to the occupations with the greatest correlation are fused to obtain the temperature curve models corresponding to emerging occupations.

Update unit: The personal setting temperature collection unit continuously collects the temperature set by the individual at different time periods of the day, and transmits the collected temperature to the server. The data is updated, and then averaged is processed to obtain the updated personal temperature curve model; the server reclassifies and averages the updated various personal temperature curve models according to gender, age, occupation and work sector, and the updated personal temperature curve model is obtained. The temperature curve model of different age groups, different occupations, different work sectors and genders.

The temperature set by the individual at different time periods of the day is collected through the personal setting temperature collection unit, and then the temperature data set by the individual is transmitted to the server. The server averages the temperature set by the individual at different time periods every day to obtain the personal temperature curve. Then, the individual temperature curve models are classified and averaged according to gender, age group, occupation and work sector to obtain temperature curve models of different age groups, different occupations, different departments and genders.

Obtain the qualified temperature curve model through the information retrieval unit.

First, input the personal information of everyone in the office area into the information retrieval unit. The information retrieval unit uses gender, age group, occupation and work department as the conditions for retrieving the temperature curve model, and obtains information that matches different age groups, different The temperature curve models of occupations, different departments and genders, and then according to the personal information of all office personnel in the office area, the temperature curve models of different age groups, different occupations, different departments and genders retrieved by the retrieval unit are weighted and averaged to obtain Optimal temperature profile model.

The thermostat controls the water flow or air volume of the fan coil unit according to the current optimal temperature curve model, so as to adjust the temperature of the office area covered by the fan coil unit in a timely manner, so as to supply on-demand and reasonably allocated energy for efficient use state.

The optimal temperature curve model is:

。

.

The artificial intelligence-based multi-user dynamic temperature regulation central air-conditioning method designed for this purpose: the temperature set by the individual at different time periods of the day is collected through the personal setting temperature collection unit, and the temperature data set by the individual is transmitted to the server. The average value of the temperature set by the individual at different time periods every day is obtained to obtain a personal temperature curve model, and then each individual temperature curve model is classified and averaged according to gender, age group, occupation and work sector, and different age groups, different temperature curve models are obtained. Models of temperature profiles for occupation, different sectors and gender.

Input the personal information of everyone in the office area into the information retrieval unit. The information retrieval unit uses gender, age group, occupation and work department as the conditions for retrieving the temperature curve model, and obtains information that matches different age groups, different occupations, The temperature curve models of different departments and genders, and then according to the personal information of all office personnel in the office area, the temperature curve models of different age groups, different occupations, different departments and genders retrieved by the retrieval unit are weighted and averaged to obtain the optimal temperature curve model.

The thermostat controls the water flow or air volume of the fan coil unit according to the current optimal temperature curve model, so as to adjust the temperature of the office area covered by the fan coil unit in a timely manner, so as to supply on-demand and reasonably allocated energy for efficient use state.

The optimal temperature curve model is:

。

.

Description of drawings

FIG. 1 is a schematic diagram of the system of the present invention.

Figure 2 shows the steps of establishing temperature curve models for different age groups, different occupations, different departments and genders.

FIG. 3 shows the steps of obtaining the optimal temperature curve model that meets the conditions through the information retrieval unit.

Figure 4 shows some employee information of a start-up technology company.

Figure 5 shows the temperature curve model corresponding to male software engineers aged 20-30 in the R&D department.

Figure 6 shows the temperature curve model corresponding to female software engineers aged 20-30 in the R&D department.

Figure 7 shows the optimal temperature curve model corresponding to 10 software engineers in the R&D department between the ages of 20 and 30 in the same office area.

In Figure 1, 1 is a wearable device such as a wristband, a watch, or a mobile phone or tablet, 2 is a computer, 3 is a server, 4 is a thermostat, and 5 is a fan coil unit.

Detailed ways

The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

first embodiment

Figure 2 shows the steps of establishing temperature curve models for different age groups, different occupations, different departments and genders.

Step S11: Collect the temperature set by the individual at different time periods in a day through the personal setting temperature collection unit, and transmit the temperature data set by the individual to the server.

Step S12: The server performs an average value process on the temperature set by the individual at different time periods every day to obtain a personal temperature curve model.

Step S13: The server classifies and averages the individual temperature curve models according to gender, age group, occupation and work department, and obtains temperature curve models for different age groups, different occupations, different departments and genders.

Second Embodiment

As shown in Figure 3, the step of obtaining the optimal temperature curve model that meets the conditions through the information retrieval unit.

Step S21: Input the personal information of everyone in the office area into the information retrieval unit.

Step S22: The information retrieval unit obtains temperature curve models in accordance with different age groups, different occupations, different departments and genders through the information retrieval unit according to the conditions for retrieving the temperature curve model according to gender, age group, occupation and work sector.

Step S23: The server performs a weighted average of the temperature curve models of different age groups, different occupations, different departments and genders retrieved by the retrieval unit according to the personal information of all office personnel in the office area to obtain the optimal temperature curve model.

Step S24: The temperature controller controls the water flow or air volume of the fan coil unit according to the current optimal temperature curve model, so as to adjust the temperature of the office area covered by the fan coil unit in time.

The optimal temperature curve model is:

。

.

Third Embodiment

As shown in Figure 4, some employee information of a start-up technology company.

If there are 6 male software engineers in the R&D department in the age group of 20-30, 4 female software engineers in the R&D department, in the age group of 20-30; the age group in the R&D department is 20-30 years old The weight of male software engineers between the ages of 30 is: 6/10=60%, and the weight of female software engineers in the R&D department between the ages of 20 and 30 is: 4/10=40%.

As shown in Figure 5, the temperature curve model corresponding to male software engineers in the R&D department between the ages of 20 and 30. The temperature curve model corresponding to male software engineers in the R&D department between the ages of 20 and 30 is obtained by averaging all the individual temperature curve models in the temperature curve model library that match the work department, occupation, age and gender.

As shown in Figure 6, the temperature curve model corresponding to female software engineers in the R&D department between the ages of 20 and 30. The temperature curve models corresponding to female software engineers in the R&D department between the ages of 20 and 30 are obtained by averaging all personal temperature curve models in the temperature curve model library that match the work sector, occupation, age group and gender.

As shown in Figure 7, through the weighted average of the temperature curve models corresponding to 10 software engineers in the R&D department who are between the ages of 20 and 30 in the office area, 10 software engineers in the R&D department who are between the ages of 20 and 30 are obtained. The optimal temperature curve model corresponding to the engineer.

The thermostat controls the water flow or air volume of the fan coil unit according to the current optimal temperature curve model, so as to make the most suitable adjustment to the temperature of the office area at different times of the day through a large amount of data, reducing the number of settings for the office area by the office staff. The temperature debate improves the office environment and work efficiency of the office staff, increases the flexibility and adaptability of the system, and makes it more humane.

Each office area can use the above method to set the optimal temperature curve model of each office area, so that each office area is independent of each other.

The above are only preferred embodiments of the present invention, and are not intended to limit the scope of implementation of the present invention; all equivalent changes and modifications made according to the present invention are covered by the scope of the claims of the present invention.

Claims (5)

1. The utility model provides a multi-user developments central air conditioning system that adjusts temperature based on artificial intelligence which characterized in that, multi-user developments central air conditioning system that adjusts temperature based on artificial intelligence includes: the system comprises an individual set temperature acquisition unit, an individual set temperature processing unit, a temperature curve model library, an information retrieval unit, an artificial intelligence unit, an updating unit and a temperature controller;

the personal information includes: name, gender, age group, occupation, and work department;

personal setting temperature acquisition unit: collecting the temperatures set by an individual at different time periods in one day, and transmitting the temperatures set by the individual to a server in a wired transmission or wireless transmission mode;

individual setting temperature processing unit: the server performs mean value processing on the temperatures set by the individual in different time periods every day to obtain an individual temperature curve model;

temperature curve model library: the server classifies and averages various stored personal temperature curve models according to gender, age groups, occupation and working departments to obtain temperature curve models of different age groups, different occupations, different working departments and genders;

an information retrieval unit: obtaining a temperature curve model meeting the conditions through a retrieval unit according to one or more combinations of gender, age group, work department and occupation as the conditions for retrieving the temperature curve model;

an artificial intelligence unit: intelligently simulating temperature curve models corresponding to emerging careers which do not exist in a temperature curve model library, extracting the characteristics of the emerging careers to obtain temperature curve models corresponding to the careers with the maximum correlation, and then fusing the temperature curve models corresponding to the careers with the maximum correlation to obtain temperature curve models corresponding to the emerging careers;

an update unit: the personal set temperature acquisition unit continuously acquires the temperatures set by the person in different time periods in one day and transmits the acquired temperatures to the server, and the server updates the data of the temperatures set by the person in different time periods every other time period and then performs mean value processing to obtain an updated personal temperature curve model; the server classifies and averages the updated various personal temperature curve models again according to the gender, the age group, the occupation and the working department to obtain updated temperature curve models of different age groups, different occupations, different working departments and the gender;

the optimal temperature curve model is as follows:

；

the personal setting temperature acquisition unit is a bracelet, a watch, a mobile phone or a computer;

the temperature controller controls the water flow or air volume of the fan coil according to the current optimal temperature curve model, and timely adjusts the temperature of an office area covered by the fan coil;

establishing temperature curve models of different age groups, different occupations, different departments and genders:

firstly, acquiring the temperature set by an individual at different time periods in one day through an individual setting temperature acquisition unit, and transmitting the temperature data set by the individual to a server;

then, the server performs mean value processing on the temperatures set by the individual in different time periods every day to obtain an individual temperature curve model;

finally, the server classifies and averages the individual temperature curve models according to gender, age group, occupation and working department to obtain temperature curve models of different age groups, different occupations, different departments and genders;

the method comprises the following steps of obtaining an optimal temperature curve model meeting conditions through an information retrieval unit:

firstly, inputting personal information of all persons in an office area into an information retrieval unit;

then, the information retrieval unit obtains temperature curve models which accord with different age groups, different professions, different departments and sexes through the information retrieval unit according to the conditions that the sexes, the age groups, the professions and the working departments serve as retrieval temperature curve models;

then, the server averages the temperature curve models of different age groups, different professions, different departments and genders, which are obtained by the retrieval unit, according to the personal information conditions of all office workers in the office area to obtain an optimal temperature curve model;

and finally, the temperature controller controls the water flow or the air volume of the fan coil according to the current optimal temperature curve model, so that the temperature of the office area covered by the fan coil is adjusted in time.

2. The central air-conditioning method of a central air-conditioning system according to claim 1, wherein: according to conditions that gender, age group, occupation and working departments are used as retrieval temperature curve models, a multi-user dynamic temperature adjustment central air-conditioning method based on artificial intelligence obtains temperature curve models which accord with different age groups, different occupations, different departments and genders through an information retrieval unit, and then averages the temperature curve models of different age groups, different occupations, different departments and genders retrieved by the retrieval unit according to personal information conditions of all office staff in an office area to obtain an optimal temperature curve model; the temperature controller controls the water flow or air volume of the fan coil according to the current optimal temperature curve model, so that the office area temperature in different time periods in one day can be optimally adjusted through a large amount of data;

the optimal temperature curve model is as follows:

。

3. the central air-conditioning method of a central air-conditioning system according to claim 1,

establishing temperature curve models of different age groups, different occupations, different departments and genders:

firstly, acquiring the temperature set by an individual at different time periods in one day through an individual setting temperature acquisition unit, and transmitting the temperature data set by the individual to a server;

then, the server performs mean value processing on the temperatures set by the individual in different time periods every day to obtain an individual temperature curve model;

and finally, the server classifies and averages the individual temperature curve models according to the gender, the age group, the occupation and the working department to obtain the temperature curve models of different age groups, different occupations, different departments and genders.

4. The central air-conditioning method of a central air-conditioning system according to claim 1,

the method comprises the following steps of obtaining an optimal temperature curve model meeting conditions through an information retrieval unit:

firstly, inputting personal information of all persons in an office area into an information retrieval unit;

then, the information retrieval unit obtains temperature curve models which accord with different age groups, different professions, different departments and sexes through the information retrieval unit according to the conditions that the sexes, the age groups, the professions and the working departments serve as retrieval temperature curve models;

then, the server averages the temperature curve models of different age groups, different professions, different departments and genders, which are obtained by the retrieval unit, according to the personal information conditions of all office workers in the office area to obtain an optimal temperature curve model;

and finally, the temperature controller controls the water flow or the air volume of the fan coil according to the current optimal temperature curve model, so that the temperature of the office area covered by the fan coil is adjusted in time.

5. The central air-conditioning method of a central air-conditioning system according to claim 1, wherein: the personal set temperature acquisition unit continuously acquires the temperatures set by the person in different time periods in one day and transmits the acquired temperatures to the server, and the server updates the data of the temperatures set by the person in different time periods every other time period and then performs mean value processing to obtain an updated personal temperature curve model; and the server classifies and averages the updated various personal temperature curve models again according to the gender, the age group, the occupation and the working department to obtain the updated temperature curve models of different age groups, different occupations, different working departments and the gender.

Images