Intelligent building integration management system based on Internet of Things

Abstract

The invention relates to the field of intelligent building integration management, in particular to an intelligent building integration management system based on the Internet of Things, which comprises an access control management module, a data acquisition module, an energy analysis module, a gas analysis module and an early warning processing module, through real-time monitoring of the gas sensor, potential safety hazards can be found in time, an alarm system can be automatically started, linkage with fire fighting equipment is achieved, the moderate response speed of gas is improved, the access control management module controls personnel to enter and exit according to intelligent recognition of all face information, and the system aims at achieving centralized management and remote monitoring of a building. The management efficiency is improved and the management cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent building integrated management, and in particular to an intelligent building integrated management system based on the Internet of Things. Background Art

[0002] With the increasing energy crisis and the continuous improvement of environmental awareness, the construction industry has higher and higher requirements for energy efficiency. Intelligent building integrated management system can achieve optimal energy management, reduce energy consumption and improve energy efficiency through intelligent control of various equipment in the building. For example, it can automatically adjust the light brightness according to the indoor light intensity and the air conditioning temperature according to the indoor temperature.

[0003] The demand for improving safety and comfort is also increasing. The intelligent building integrated management system can realize real-time monitoring and early warning of buildings by installing various sensors and monitoring equipment to improve the safety of buildings. At the same time, through the intelligent adjustment of environmental parameters, a more comfortable indoor environment can be provided for users. When gas is detected indoors, the ventilation device is automatically started to improve the management efficiency. For large buildings or building complexes, the traditional management method is inefficient and costly. The intelligent building integrated management system can realize centralized management and remote monitoring of buildings, improve management efficiency and reduce management costs. Summary of the invention

[0004] In order to solve the technical problems raised by the above background technology, the present invention provides an intelligent building integrated management system based on the Internet of Things.

[0005] The purpose of the present invention can be achieved through the following technical solutions: The present invention is an intelligent building integrated management system based on the Internet of Things, comprising an access control management module, a data acquisition module, an energy analysis module, a gas analysis module, an early warning processing module and a data center.

[0006] The access control management module uses intelligent facial recognition to control the entry and exit of personnel, implement authority management, ensure building safety and efficiently screen personnel. The specific acquisition process is as follows: The input end of the access control management module is connected to the output end of the data center. The property staff sends personal information to the data center. The property personal information includes name, position and facial contour information. The residents send personal information to the data center. The resident personal information includes name, real estate certificate and facial contour information. The data center receives the resident personal information and property personal information and divides them into resident information set and property information set, extracts the data of each resident in the data center, matches the actual resident data with the resident information set, and if successful, the resident information set is judged as qualified and stored, if unsuccessful, the resident information set is discarded, the property staff and residents capture facial images through the access control display, extract the facial contour image of the data center, and match the captured facial image with the facial contour information. If the match is successful, the access control display sends the door opening command to the access control terminal, the access control terminal receives the door opening command and unlocks the door head, obtains the people within the door head radius through the infrared sensor, and the door head is automatically closed if there is no flow of people within the sensing radius.

[0007] The data acquisition module collects data information of each building according to each sensor. The specific acquisition process is as follows: Install gas sensors in each building area, including basements, garages, kitchens, and machine rooms where harmful gases are generated. Use gas sensors to collect harmful gas data information in each building area in real time, and obtain gas parameters in each building area in real time; Install light sensors in each building area where people move around, collect light intensity data information of each building area in real time through the light sensors, and obtain light intensity parameters of each building area in real time; Install a pressure sensor on each drainage pipe, monitor the pressure data of each drainage pipe in real time through the pressure sensor, and obtain the pressure parameters of each drainage pipe; The output end of the data acquisition module is connected to the input end of the energy analysis module and the gas analysis module, and the light intensity parameters of each building area and the pressure parameters of the drainage pipe are sent to the energy analysis module, and the gas parameters of each building area are sent to the gas analysis module.

[0008] The energy analysis module analyzes the collected parameter information separately. The specific acquisition process is as follows: The output end of the energy analysis module is connected to the input end of the early warning processing module, and the pressure parameters of the drainage pipe are analyzed. The preset pressure monitoring time zone is set, and the pressure monitoring time zone is divided into several pressure monitoring time zones. The pressure values ​​of all collection times in the pressure time zone are obtained, and the average of each pressure value is calculated to obtain the pressure average value corresponding to the pressure monitoring time zone, marked as DF, and the pressure values ​​of all collection times are arranged in chronological order. The maximum pressure value and the minimum pressure value corresponding to the collection time are obtained, and the maximum pressure value is marked as KF. Then, the maximum pressure value is subtracted from the minimum pressure value to obtain the pressure difference value of the pressure monitoring time zone, marked as GF, and then the time point corresponding to the maximum pressure value and the time point corresponding to the minimum pressure value are obtained to obtain the minimum pressure time point and the maximum pressure time point. The minimum pressure time point and the minimum pressure time point are subtracted to obtain the pressure difference period, marked as HF, and the obtained pressure average value, maximum pressure value, pressure difference value and pressure difference period are calculated using the formula The pressure flow value GCB is obtained, where C1, C2, C3 and C4 are preset proportional coefficients, and their sizes are custom settings, with values ​​of 0.18, 0.45, 1.62 and 1.24 respectively. The preset pressure flow value range of the data center is extracted, and the preset pressure flow value range is compared with the actual pressure flow value. If the actual pressure flow value is greater than or less than the preset pressure flow value range, a pressure abnormality signal is generated and sent to the corresponding early warning processing module; The light intensity parameters are analyzed, the light intensity of each building area is monitored in real time, the real-time light intensity of each building area is obtained, the preset light intensity of the data center is extracted, and the real-time light intensity of each building area is compared with the preset light intensity. If the real-time light intensity of each building area is greater than the preset light intensity, a light signal is generated and sent to the corresponding early warning processing module.

[0009] The gas analysis module analyzes the gas parameter information of each area based on the gas parameter information sent by data acquisition. The specific acquisition process is as follows: The output end of the gas analysis module is connected to the input end of the early warning processing module to analyze the information of each gas parameter, obtain the gas parameters of each building area obtained by data collection, classify and detect the gas parameters of each building area at each monitoring time point, and obtain various types of gases in each building area at each monitoring time. The formaldehyde concentration of each building area at each monitoring time point is monitored by a formaldehyde detector to obtain the formaldehyde concentration value of each building area at each monitoring time point. The obtained formaldehyde concentration values ​​are averaged to obtain the formaldehyde average concentration value, marked as TP, and the methane at each monitoring time point in each building area is measured by a thermal conductivity gas analyzer. The concentration is monitored to obtain the methane concentration values ​​of each building area at each monitoring time point. The obtained methane concentration values ​​are averaged to obtain the average methane concentration value, marked as YT. The start monitoring time point of each methane concentration and each formaldehyde concentration is marked as the initial monitoring time point, and then the current system time point is cut off and marked as the end time point. The initial time point and the end time point are subtracted to obtain the gas monitoring time period corresponding to each methane concentration and each formaldehyde concentration, marked as TR and TE respectively. The obtained formaldehyde average concentration value, methane average concentration value, methane gas monitoring time and formaldehyde monitoring time period are calculated using the formula The gas harmful value is obtained, where F1, F2, F3 and F4 are preset proportional coefficients, and their sizes are custom settings, with values ​​of 0.26, 0.78, 0.96 and 1.45 respectively. i represents the number of each monitoring time point, i=1, 2, ..., m, and m is the maximum value of the number, that is, the total number of each monitoring time point, and the value is a positive integer. The preset gas harmful threshold of the data center is extracted, and the actual gas harmful value is compared with the preset gas harmful threshold. If the actual gas harmful value is greater than the preset gas harmful threshold, a diffusion signal is generated and sent to the early warning processing module.

[0010] The early warning processing module performs early warning processing on each signal received, and the specific acquisition method is as follows: The output end of the early warning processing module is connected to the input end of the data center. A pressure reducing valve and a booster pump are installed in the drainage pipe. When an abnormal pressure signal is received, the abnormal pressure signal is sent to the intelligent building control system. The intelligent building control system receives the abnormal pressure signal and obtains the current pressure state of the drainage pipe through the pressure sensor. If the current pressure state is greater than the preset pressure, the intelligent building control system generates a pressure reducing instruction and sends it to the pressure reducing valve. The pressure reducing valve dredges the current pipeline pressure. If the current pressure state is less than the preset pressure, the intelligent building control system generates a pressure increasing instruction and sends it to the booster pump. The booster pump increases the current pipeline drainage pressure.

[0011] The light signal is received and sent to the intelligent building control system. The intelligent building control system receives the light signal and divides the light brightness into five levels, including extremely dark light with a brightness range of 0-50 lux, dim light illumination range of 51-200lux, medium light illumination range of 201-500lux, bright light illumination range of 501-1000lux and extremely bright light illumination range of more than 1000lux. The light brightness is adjusted according to the different light illuminations obtained. The light brightness includes low brightness, medium-low brightness, medium brightness, medium-high brightness and high brightness. The light illumination is matched with the light brightness. The lower the light illumination, the higher the corresponding light brightness; the higher the light illumination, the lower the corresponding light brightness. When the current level of light illumination is in the extremely dim light illumination range, the flow of personnel activities within the radius is obtained through the microwave radar sensor. When it senses that there are personnel activities nearby, the microwave radar sensor generates an on signal and sends it to the lighting control system. The lighting control system receives the on signal and starts the lights in the corresponding area. If there are no personnel within the sensing radius of the microwave radar sensor, a shut-down signal is generated and sent to the lighting control system, and the lighting control system turns off the corresponding lights.

[0012] The diffusion signal is received and sent to the intelligent building control system. The intelligent building control system receives the diffusion signal, obtains the location information of the corresponding area through the positioning sensor, marks the corresponding area as an abnormal area, and obtains the positioning of each ventilation device within the radius with the abnormal area as the center point. The intelligent building control terminal generates a control instruction and sends it to each ventilation device. Each ventilation device receives the control instruction and ventilates the harmful gas in the abnormal area.

[0013] Compared with the prior art, the beneficial effects of the present invention are: improving energy efficiency, automatically adjusting the light brightness and switch status according to the data of the light sensor and the activities of the personnel, and avoiding unnecessary lighting waste. For example, the lights are automatically dimmed or turned off in areas with sufficient natural light, and the lights are automatically turned off when the personnel leave the room. The ventilation system is optimized, and through the real-time monitoring of the gas sensor, it can timely discover safety hazards, automatically start the alarm system, and link with the fire-fighting equipment to improve the response speed of gas medium, illegal intrusion detection, access control system and video surveillance system are combined to strictly control the entry and exit of personnel to prevent illegal intrusion. When an abnormal person enters or forcibly destroys the access control, the system immediately issues an alarm and notifies the security personnel. At the same time, the video surveillance system can record the on-site situation and provide evidence for subsequent investigations. The lighting equipment is automatically adjusted according to the indoor lighting environment parameters to provide users with a comfortable indoor environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present invention.

[0015] Figure 1 It is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0017] See also Figure 1 As shown, the present invention is an intelligent building integrated management system based on the Internet of Things, including an access control management module, a data acquisition module, an energy analysis module, a gas analysis module, an early warning processing module and a data center.

[0018] The access control management module uses intelligent facial recognition to control the entry and exit of personnel, implement authority management, ensure building safety and efficiently screen personnel. The specific acquisition process is as follows: The input end of the access control management module is connected to the output end of the data center. The property staff sends personal information to the data center. The property personal information includes name, position and facial contour information. The residents send personal information to the data center. The resident personal information includes name, real estate certificate and facial contour information. The data center receives the resident personal information and property personal information and divides them into resident information set and property information set, extracts the data of each resident in the data center, matches the actual resident data with the resident information set, and if successful, the resident information set is judged as qualified and stored, if unsuccessful, the resident information set is discarded, the property staff and residents capture facial images through the access control display, extract the facial contour image of the data center, and match the captured facial image with the facial contour information. If the match is successful, the access control display sends the door opening command to the access control terminal, the access control terminal receives the door opening command and unlocks the door head, obtains the people within the door head radius through the infrared sensor, and the door head is automatically closed if there is no flow of people within the sensing radius.

[0019] The data acquisition module collects data information of each building according to each sensor. The specific acquisition process is as follows: Install gas sensors in each building area, including basements, garages, kitchens, and machine rooms where harmful gases are generated. Use gas sensors to collect harmful gas data information in each building area in real time, and obtain gas parameters in each building area in real time; Install light sensors in each building area where people move around, collect light intensity data information of each building area in real time through the light sensors, and obtain light intensity parameters of each building area in real time; Install a pressure sensor on each drainage pipe, monitor the pressure data of each drainage pipe in real time through the pressure sensor, and obtain the pressure parameters of each drainage pipe; The output end of the data acquisition module is connected to the input end of the energy analysis module and the gas analysis module, and the light intensity parameters of each building area and the pressure parameters of the drainage pipe are sent to the energy analysis module, and the gas parameters of each building area are sent to the gas analysis module.

[0020] The energy analysis module analyzes the collected parameter information separately. The specific acquisition process is as follows: The output end of the energy analysis module is connected to the input end of the early warning processing module, and the pressure parameters of the drainage pipe are analyzed. The preset pressure monitoring time zone is set, and the pressure monitoring time zone is divided into several pressure monitoring time zones. The pressure values ​​of all collection times in the pressure time zone are obtained, and the average of each pressure value is calculated to obtain the pressure average value corresponding to the pressure monitoring time zone, marked as DF, and the pressure values ​​of all collection times are arranged in chronological order. The maximum pressure value and the minimum pressure value corresponding to the collection time are obtained, and the maximum pressure value is marked as KF. Then, the maximum pressure value is subtracted from the minimum pressure value to obtain the pressure difference value of the pressure monitoring time zone, marked as GF, and then the time point corresponding to the maximum pressure value and the time point corresponding to the minimum pressure value are obtained to obtain the minimum pressure time point and the maximum pressure time point. The minimum pressure time point and the minimum pressure time point are subtracted to obtain the pressure difference period, marked as HF, and the obtained pressure average value, maximum pressure value, pressure difference value and pressure difference period are calculated using the formula The pressure flow value GCB is obtained, where C1, C2, C3 and C4 are preset proportional coefficients, and their sizes are custom settings, with values ​​of 0.18, 0.45, 1.62 and 1.24 respectively. The preset pressure flow value range of the data center is extracted, and the preset pressure flow value range is compared with the actual pressure flow value. If the actual pressure flow value is greater than or less than the preset pressure flow value range, a pressure abnormality signal is generated and sent to the corresponding early warning processing module; The light intensity parameters are analyzed, the light intensity of each building area is monitored in real time, the real-time light intensity of each building area is obtained, the preset light intensity of the data center is extracted, and the real-time light intensity of each building area is compared with the preset light intensity. If the real-time light intensity of each building area is greater than the preset light intensity, a light signal is generated and sent to the corresponding early warning processing module.

[0021] The gas analysis module analyzes the gas parameter information of each area based on the gas parameter information sent by data acquisition. The specific acquisition process is as follows: The output end of the gas analysis module is connected to the input end of the early warning processing module to analyze the information of each gas parameter, obtain the gas parameters of each building area obtained by data collection, classify and detect the gas parameters of each building area at each monitoring time point, and obtain various types of gases in each building area at each monitoring time. The formaldehyde concentration of each building area at each monitoring time point is monitored by a formaldehyde detector to obtain the formaldehyde concentration value of each building area at each monitoring time point. The obtained formaldehyde concentration values ​​are averaged to obtain the formaldehyde average concentration value, marked as TP, and the methane at each monitoring time point in each building area is measured by a thermal conductivity gas analyzer. The concentration is monitored to obtain the methane concentration values ​​of each building area at each monitoring time point. The obtained methane concentration values ​​are averaged to obtain the average methane concentration value, marked as YT. The start monitoring time point of each methane concentration and each formaldehyde concentration is marked as the initial monitoring time point, and then the current system time point is cut off and marked as the end time point. The initial time point and the end time point are subtracted to obtain the gas monitoring time period corresponding to each methane concentration and each formaldehyde concentration, marked as TR and TE respectively. The obtained formaldehyde average concentration value, methane average concentration value, methane gas monitoring time and formaldehyde monitoring time period are calculated using the formula The gas harmful value is obtained, where F1, F2, F3 and F4 are preset proportional coefficients, and their sizes are custom settings, with values ​​of 0.26, 0.78, 0.96 and 1.45 respectively. i represents the number of each monitoring time point, i=1, 2, ..., m, and m is the maximum value of the number, that is, the total number of each monitoring time point, and the value is a positive integer. The preset gas harmful threshold of the data center is extracted, and the actual gas harmful value is compared with the preset gas harmful threshold. If the actual gas harmful value is greater than the preset gas harmful threshold, a diffusion signal is generated and sent to the early warning processing module.

[0022] The early warning processing module performs early warning processing on each signal received, and the specific acquisition method is as follows: The output end of the early warning processing module is connected to the input end of the data center. A pressure reducing valve and a booster pump are installed in the drainage pipe. When an abnormal pressure signal is received, the abnormal pressure signal is sent to the intelligent building control system. The intelligent building control system receives the abnormal pressure signal and obtains the current pressure state of the drainage pipe through the pressure sensor. If the current pressure state is greater than the preset pressure, the intelligent building control system generates a pressure reducing instruction and sends it to the pressure reducing valve. The pressure reducing valve dredges the current pipeline pressure. If the current pressure state is less than the preset pressure, the intelligent building control system generates a pressure increasing instruction and sends it to the booster pump. The booster pump increases the current pipeline drainage pressure.

[0023] The light signal is received and sent to the intelligent building control system. The intelligent building control system receives the light signal and divides the light brightness into five levels, including extremely dark light with a brightness range of 0-50 lux, dim light illumination range of 51-200lux, medium light illumination range of 201-500lux, bright light illumination range of 501-1000lux and extremely bright light illumination range of more than 1000lux. The light brightness is adjusted according to the different light illuminations obtained. The light brightness includes low brightness, medium-low brightness, medium brightness, medium-high brightness and high brightness. The light illumination is matched with the light brightness. The lower the light illumination, the higher the corresponding light brightness; the higher the light illumination, the lower the corresponding light brightness. When the current level of light illumination is in the extremely dim light illumination range, the flow of personnel activities within the radius is obtained through the microwave radar sensor. When it senses that there are personnel activities nearby, the microwave radar sensor generates an on signal and sends it to the lighting control system. The lighting control system receives the on signal and starts the lights in the corresponding area. If there are no personnel within the sensing radius of the microwave radar sensor, a shut-down signal is generated and sent to the lighting control system, and the lighting control system turns off the corresponding lights.

[0024] The diffusion signal is received and sent to the intelligent building control system. The intelligent building control system receives the diffusion signal, obtains the location information of the corresponding area through the positioning sensor, marks the corresponding area as an abnormal area, and obtains the positioning of each ventilation device within the radius with the abnormal area as the center point. The intelligent building control terminal generates a control instruction and sends it to each ventilation device. Each ventilation device receives the control instruction and ventilates the harmful gas in the abnormal area.

[0025] The above is an explanation of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, it will be readily appreciated by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined in the claims. It should be understood that the above is an explanation of the present invention and should not be considered as being limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. An integrated management system for intelligent buildings based on the Internet of Things, comprising an access control management module, a data acquisition module, an energy analysis module, an early warning processing module and a data center, characterized in that: Gas analysis module; The gas analysis module analyzes the gas parameter information of each area according to the gas parameter information sent by the data collection. The output end of the gas analysis module is connected to the input end of the early warning processing module to obtain the gas parameters of each building area obtained by data collection, and the gas parameters of each building area at each monitoring time point are classified and detected to obtain various types of gases in each building area at each monitoring time. The formaldehyde concentration of each building area at each monitoring time point is monitored by a formaldehyde detector to obtain the formaldehyde concentration value of each building area at each monitoring time point. The obtained formaldehyde concentration values ​​are averaged to obtain the formaldehyde average concentration value, marked as TP, and the thermal conductivity gas analyzer is used to monitor the formaldehyde concentration of each building area at each monitoring time point. The methane concentrations at each monitoring time point in the area are monitored, and the methane concentration values ​​at each monitoring time point in each building area are obtained. The obtained methane concentration values ​​are averaged to obtain the average methane concentration value, marked as YT. The start monitoring time point of each methane concentration and each formaldehyde concentration is marked as the initial monitoring time point, and then the current system time point is cut off and marked as the end time point. The initial time point and the end time point are subtracted to obtain the gas monitoring time period corresponding to each methane concentration and each formaldehyde concentration, marked as TR and TE respectively. The obtained formaldehyde average concentration value, methane average concentration value, methane gas monitoring time and formaldehyde monitoring time period are calculated using the formula The gas harmful value is obtained, where F1, F2, F3 and F4 are preset proportional coefficients, i represents the number of each monitoring time point, i=1, 2, ..., m, and the preset gas harmful threshold of the data center is extracted. The actual gas harmful value is compared with the preset gas harmful threshold. If the actual gas harmful value is greater than the preset gas harmful threshold, a diffusion signal is generated and sent to the early warning processing module.

2. According to claim 1, the intelligent building integrated management system based on the Internet of Things is characterized in that: The energy analysis module analyzes the collected parameter information separately. The specific process is as follows: The output end of the energy analysis module is connected to the input end of the early warning processing module, and the pressure parameters of the drainage pipe are analyzed. The preset pressure monitoring time zone is set, and the pressure monitoring time zone is divided into several pressure monitoring time zones. The pressure values ​​of all collection times in the pressure time zone are obtained, and the average of each pressure value is calculated to obtain the pressure average value corresponding to the pressure monitoring time zone, marked as DF, and the pressure values ​​of all collection times are arranged in chronological order. The maximum pressure value and the minimum pressure value corresponding to the collection time are obtained, and the maximum pressure value is marked as KF. Then, the maximum pressure value is subtracted from the minimum pressure value to obtain the pressure difference value of the pressure monitoring time zone, marked as GF, and then the time point corresponding to the maximum pressure value and the time point corresponding to the minimum pressure value are obtained to obtain the minimum pressure time point and the maximum pressure time point. The minimum pressure time point and the minimum pressure time point are subtracted to obtain the pressure difference period, marked as HF, and the obtained pressure average value, maximum pressure value, pressure difference value and pressure difference period are calculated using the formula Obtain the pressure flow value GCB, where C1, C2, C3 and C4 are preset proportional coefficients, extract the preset pressure flow value range of the data center, compare the preset pressure flow value range with the actual pressure flow value, and if the actual pressure flow value is greater than or less than the preset pressure flow value range, generate a pressure abnormality signal and send it to the corresponding early warning processing module; The light intensity parameters are analyzed, the light intensity of each building area is monitored in real time, the real-time light intensity of each building area is obtained, the preset light intensity of the data center is extracted, and the real-time light intensity of each building area is compared with the preset light intensity. If the real-time light intensity of each building area is greater than the preset light intensity, a light signal is generated and sent to the corresponding early warning processing module.

3. According to the IoT-based intelligent building integrated management system of claim 1, it is characterized in that: The early warning processing module performs early warning processing on each signal received, and the specific process is as follows: The output end of the early warning processing module is connected to the input end of the data center. A pressure reducing valve and a booster pump are installed in the drainage pipe. When an abnormal pressure signal is received, the abnormal pressure signal is sent to the intelligent building control system. The intelligent building control system receives the abnormal pressure signal and obtains the current pressure state of the drainage pipe through the pressure sensor. If the current pressure state is greater than the preset pressure, the intelligent building control system generates a pressure reducing instruction and sends it to the pressure reducing valve. The pressure reducing valve dredges the current pipeline pressure. If the current pressure state is less than the preset pressure, the intelligent building control system generates a pressure increasing instruction and sends it to the booster pump. The booster pump increases the current pipeline drainage pressure. After receiving the light signal, the light signal is sent to the intelligent building control system. After receiving the light signal, the intelligent building control system divides the light brightness into five levels, including extremely dark light brightness, dark light brightness, medium light brightness, bright light brightness and extremely bright light brightness. The light brightness is adjusted according to the different light brightnesses obtained. The light brightness includes low brightness, medium-low brightness, medium brightness, medium-high brightness and high brightness. The light brightness is matched with the light brightness to obtain each matching brightness level. When the light brightness obtains the current level in the extremely dark light brightness range, the flow of human activity within the radius is obtained through the microwave radar sensor. When human activity is sensed nearby, the microwave radar sensor generates an on signal and sends it to the lighting control system. The lighting control system receives the on signal and starts the lights in the corresponding area. If there are no people within the sensing radius of the microwave radar sensor, a shut-down signal is generated and sent to the lighting control system. The lighting control system shuts down the corresponding lights. The diffusion signal is received and sent to the intelligent building control system. The intelligent building control system receives the diffusion signal, obtains the location information of the corresponding area through the positioning sensor, marks the corresponding area as an abnormal area, and obtains the positioning of each ventilation device within the radius with the abnormal area as the center point. The intelligent building control terminal generates a control instruction and sends it to each ventilation device. Each ventilation device receives the control instruction and ventilates the harmful gas in the abnormal area.

4. According to claim 1, the intelligent building integrated management system based on the Internet of Things is characterized in that: The access control management module controls the entry and exit of personnel based on intelligent recognition of facial information. The specific process is as follows: The input end of the access control management module is connected to the output end of the data center. The property staff sends personal information to the data center. The property personal information includes name, position and facial contour information. The residents send personal information to the data center. The resident personal information includes name, real estate certificate and facial contour information. The data center receives the resident personal information and property personal information and divides them into resident information set and property information set, extracts the data of each resident in the data center, matches the actual resident data with the resident information set, and if successful, the resident information set is judged as qualified and stored, if unsuccessful, the resident information set is discarded, the property staff and residents capture facial images through the access control display, extract the facial contour image of the data center, and match the captured facial image with the facial contour information. If the match is successful, the access control display sends the door opening command to the access control terminal, the access control terminal receives the door opening command and unlocks the door head, obtains the people within the door head radius through the infrared sensor, and the door head is automatically closed if there is no flow of people within the sensing radius.

5. The intelligent building integrated management system based on the Internet of Things according to claim 1 is characterized in that: The data acquisition module collects data information of each building according to each sensor. The specific process is as follows: Gas sensors are installed in each building area, including basements, garages, kitchens, and machine rooms where harmful gases are generated. The harmful gas data information of each building area is collected in real time through the gas sensors, and the gas parameters of each building area are obtained in real time; light sensors are installed in each building area where people move, and the light intensity data information of each building area is collected in real time through the light sensors, and the light intensity parameters of each building area are obtained in real time; pressure sensors are installed on each drainage pipe, and the pressure data of each drainage pipe is monitored in real time through the pressure sensors, and the pressure parameters of each drainage pipe are obtained; The output end of the data acquisition module is connected to the input end of the energy analysis module and the gas analysis module, and the light intensity parameters of each building area and the pressure parameters of the drainage pipe are sent to the energy analysis module, and the gas parameters of each building area are sent to the gas analysis module.

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