Intelligent terminal online control system and method based on personnel identification and location tracking

Abstract

The present application relates to the technical field of intelligent terminal online control, in particular to an intelligent terminal online control system and method based on personnel identification and location tracking. The system comprises a number updating unit, an indoor division unit, a walking path statistical analysis unit, a control triggering unit, a lamp selection unit and a lamp opening control unit. The number updating unit is used to establish an online number statistics library and collect door lock identification data at the same time, and update the online number of the online number statistics library according to the door lock identification data. According to the personnel location and walking direction, the system realizes intelligent light control by combining indoor area division and lamp lighting range. The lamps are turned on in advance before the personnel enter the relevant area, and the lamps are automatically turned off when the personnel leave and no other personnel activity occurs within a period of time. This not only avoids energy waste, but also prolongs the service life of the lamps.

Description

Technical Field

[0001] This invention relates to the field of online control technology for smart terminals, and more specifically, to an online control system and method for smart terminals based on personnel identification and location tracking. Background Technology

[0002] In the field of integrating smart building and IoT technologies, we are committed to achieving intelligent management of building equipment and efficient monitoring of personnel activities through various means.

[0003] Currently, existing lighting and electrical appliance control methods, whether timed control or simple sensor control, cannot accurately match the actual activity trajectory of people. Timed control will cause energy waste when people's actual work and rest do not match the preset time. Sensor control can only be triggered when people enter the sensing range, and cannot predict people's needs in advance. As a result, in some scenarios, such as when people quickly move from one room to another, the lights in the target room cannot be turned on in time. Therefore, a smart terminal online control system and method based on personnel recognition and location tracking is proposed. Summary of the Invention

[0004] The purpose of this invention is to provide an online control system and method for intelligent terminals based on personnel identification and location tracking, so as to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, one of the objectives of this invention is to provide an intelligent terminal online control system based on personnel identification and location tracking, including a personnel update unit, an indoor division unit, a walking path statistical analysis unit, a control trigger unit, a lamp selection unit, and a lamp activation control unit. The number of people update unit is used to establish an online number of people statistics database, and at the same time collect door lock recognition data, and update the number of online people in the online number of people statistics database according to the door lock recognition data; The indoor division unit is used to collect historical video data, and at the same time extract and analyze the internal building data, lighting installation location data and lighting range of the house, and divide the house into indoor areas based on the data obtained from the analysis. The walking path statistical analysis unit is used to extract the walking path of people based on historical video data and door lock recognition data, obtain the walking path of each person after the door lock is unlocked, and then perform probability statistical analysis on the walking path in combination with time nodes. The control triggering unit is used to establish a lighting control terminal based on the indoor division unit and the walking path statistical analysis unit, and then combine the lighting control terminal with the online people statistics database to set up a control triggering mechanism; The lighting selection unit is used to extract the walking path by combining the personnel identification data of the door lock identification data with the real time when the lighting control terminal is triggered, and then obtain the relevant indoor area based on the extracted walking path, and select the lighting fixture by combining the relevant indoor area. The lighting control unit is used to track the location of people based on real-time video data. At the same time, it sets a distance threshold based on the lighting brightness of the relevant indoor area where the person is located. Then, it selects other relevant indoor areas based on the direction of the person's movement and compares them with the distance threshold. Based on the comparison results, it controls the lighting of other relevant indoor areas in advance.

[0006] As a further improvement to this technical solution, the number of people update unit establishes an online number of people statistics database in the smart lock through Internet of Things technology, and at the same time collects the door lock identification data of the smart lock, and updates the online number of people in the online number of people statistics database according to the door lock identification data.

[0007] As a further improvement to this technical solution, the indoor partitioning unit establishes a data transmission connection through Internet of Things technology and indoor monitoring devices, and obtains indoor historical video data and real-time video data by extracting historical data and real-time data from the monitoring devices.

[0008] As a further improvement to this technical solution, the indoor division unit includes a data extraction and analysis module and an indoor area division module; The data extraction and analysis module is used to analyze the interior building data and lighting installation location of the room based on historical video data, thereby establishing an interior three-dimensional model based on the interior building data, filling the corresponding lighting installation location in the three-dimensional building model, and then extracting the lighting range of each lighting fixture and the time proportion of different lighting ranges by combining historical video data, and then taking the lighting range with the highest time proportion as the lighting range represented by that lighting fixture. The indoor area division module is used to divide the interior of the house into multiple indoor areas based on internal building data, lighting installation locations, and lighting range.

[0009] As a further improvement to this technical solution, the walking path statistical analysis unit includes a walking path extraction module and a walking statistics module; The walking path extraction module is used to extract the walking path of people based on historical video data and door lock recognition data, and to obtain the walking path of each person after the door lock is unlocked. The walking statistics module is used to obtain the unlocking time of each walking path, and then perform probability statistical analysis on all walking paths in combination with the unlocking time to obtain the probability of each person passing through each walking path at different times.

[0010] As a further improvement to this technical solution, the control triggering unit includes a terminal establishment module and a power-on triggering module; The terminal establishment module is used to establish a lighting control terminal based on all the data collected from the indoor division unit and the walking path statistical analysis unit. At the same time, the lighting control terminal controls the internal electrical equipment of the entire house through the Internet of Things. The power-on trigger module is used to combine the lighting control terminal with the online people statistics database to set up a control trigger mechanism; When the online user statistics database shows that the number of online users is 0, the lighting control terminal will cut off the power to all internal electrical equipment. When the number of online users is updated in the online user statistics database and is not zero, the mechanism is triggered. First, the lights in the entrance hall are turned on, and at the same time, a signal is sent to the light selection unit to perform lighting control operation. After the lighting control operation is triggered, if a person manually turns off the lights, the subsequent automatic lighting control operation will stop until the number of online users reaches 0.

[0011] As a further improvement to this technical solution, the lamp selection unit includes a path extraction module and a lamp selection module; The path extraction module is used to extract the latest personnel identification data acquired by the smart door lock, and extract the walking path based on the personnel identification data and real-time time to obtain the walking path of the person who unlocked the door with a corresponding probability of passing. The lighting selection module is used to filter relevant indoor areas by combining all indoor areas with the walking path obtained by the path extraction module, obtain the relevant indoor areas involved in the walking path, and then select lighting fixtures in the relevant indoor areas to obtain the lighting range of each relevant indoor area that can achieve the coverage effect.

[0012] As a further improvement to this technical solution, the lamp activation control unit includes a walking analysis module, a distance threshold setting module, and a distance comparison module; The walking analysis module is used to track the location of people based on real-time video data and to predict and analyze the walking direction of people based on the acquired personnel location tracking data. The distance threshold setting module is used to obtain the relevant indoor area where the person is located based on the personnel location tracking data, and then set the distance threshold based on the current lighting brightness of the relevant indoor area. The brighter the light fixture, the shorter the distance to the threshold. The lower the brightness of the light fixture, the longer the distance from the threshold. The distance comparison module is used to extract other relevant indoor areas based on the walking direction obtained by the walking analysis module. Then, it selects the other relevant indoor areas with the highest probability of passing and compares them with a distance threshold. When the distance between the person and other relevant indoor areas is less than the distance threshold, it controls the lights in the other relevant indoor areas to be turned on. Conversely, when the distance between the person and other relevant indoor areas is greater than the distance threshold, it continues to monitor.

[0013] The second objective of this invention is to provide an online control method for intelligent terminals based on personnel identification and location tracking, including the online control system for intelligent terminals based on personnel identification and location tracking described in any one of the above-mentioned methods, comprising the following steps: S1. Establish an online people statistics database and collect door lock recognition data. Update the online people statistics database based on the door lock recognition data. Then, extract and analyze the internal building data, lighting installation location data, and lighting range of the building. Divide the building into indoor areas based on the data obtained from the analysis. S2. Extract people's walking paths based on historical video data and door lock recognition data, perform probability statistical analysis on the walking paths in conjunction with time nodes, establish a lighting control terminal, and then set up a control trigger mechanism by combining the lighting control terminal with the online people statistics database. S3. When the lighting control terminal is triggered, the personnel identification data of the door lock identification data is combined with the real time to extract the walking path, and the relevant indoor areas are combined to select lighting fixtures. S4. Set a distance threshold based on the brightness of the lights in the relevant indoor area where the person is located. Then, select other relevant indoor areas based on the direction the person is walking and compare them with the distance threshold. Based on the comparison results, control the lights in other relevant indoor areas to turn on in advance.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. An intelligent terminal online control system and method based on personnel identification and location tracking. By combining the personnel's location and walking direction with the indoor area division and lighting range of the lamps, the system realizes intelligent lighting control. The lamps are turned on in advance before personnel enter the relevant area, and automatically turned off when personnel leave and there is no other personnel activity for a period of time. This not only avoids energy waste, but also extends the service life of the lamps.

[0015] 2. An online control system and method for intelligent terminals based on personnel identification and location tracking. For people who frequently come and go, the system can provide convenience in advance according to their past walking paths and habits. After people return home and open the smart door lock, the system can automatically turn on the lights in the entrance hall and indoor areas to create a comfortable living environment. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall structure of the present invention.

[0017] The meanings of the labels in the diagram are as follows: 10. Number of people update unit; 20. Indoor division unit; 30. Walking path statistical analysis unit; 40. Control trigger unit; 50. Lighting selection unit; 60. Lighting control unit. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, one of the objectives of this invention is to provide an intelligent terminal online control system based on personnel identification and location tracking, including a personnel update unit 10, an indoor division unit 20, a walking path statistical analysis unit 30, a control trigger unit 40, a lamp selection unit 50, and a lamp activation control unit 60. The number of people update unit 10 is used to establish an online number of people statistics database, and at the same time collect door lock recognition data, and update the number of online people in the online number of people statistics database based on the door lock recognition data; The people update unit 10 establishes an online people statistics database in the smart lock through Internet of Things technology, and collects the door lock identification data of the smart lock, and updates the online people in the online people statistics database according to the door lock identification data.

[0020] By embedding a module with data storage and processing capabilities into the smart lock system, an online people statistics database is established. This database accurately collects lock recognition data, including key information such as the identification of successfully identified persons and the recognition time. Then, through the built-in IoT communication chip (Wi-Fi), a data transmission link is established between the smart lock and the backend server, ensuring that the lock recognition data can be uploaded to the server in real time for updating the online people statistics database.

[0021] The indoor division unit 20 is used to collect historical video data, and at the same time, extract and analyze the internal building data, lighting installation location data and lighting range of the building, and divide the building into indoor areas based on the data obtained from the analysis. The indoor partition unit 20 establishes a data transmission connection through IoT technology and indoor monitoring devices. By extracting historical and real-time data from the monitoring devices, it obtains historical and real-time video data of the indoor environment.

[0022] Select indoor monitoring devices, such as high-definition cameras and smart video sensors, and connect them to the Internet of Things. The backend server sends data extraction instructions to the monitoring devices at regular intervals, and the monitoring devices extract historical data and real-time data according to the instructions.

[0023] Indoor partitioning unit 20 includes a data extraction and analysis module and an indoor area partitioning module; The data extraction and analysis module is used to analyze the interior building data and lighting fixture installation locations based on historical video data. This allows for the creation of a 3D interior model based on the building data, and the lighting fixture installation locations are then filled into the 3D model. Next, the module combines historical video data to extract the illumination range of each lighting fixture and the time percentage of different illumination ranges. The illumination range with the highest time percentage is then used as the illumination range represented by that lighting fixture. The specific steps are as follows: Indoor building data and lighting installation location extraction: Image frames are extracted from historical video data at a specific frame rate. The extracted image frames are then converted to grayscale to convert color images into grayscale images. The Canny edge detection algorithm is used to extract the contour features of the indoor building. For the extraction of lighting installation locations, a deep learning model based on object detection is used. After training, historical video data is input into the model. Indoor 3D Model Building: Based on the extracted indoor building outline features, a 3D reconstruction algorithm is used to build an indoor 3D model. Then, the position of the lamps is transformed into the 3D model space according to the corresponding 3D coordinate mapping rules. This mapping process requires converting the coordinates of the lamps in the 2D video image into the actual coordinates in the 3D model according to the coordinate system and scale relationship used when building the model, so that the lamps can be visualized in the 3D building model with the correct position and posture. Lighting range extraction and time proportion calculation: From historical video data, one frame is extracted every ten minutes during the lighting period. The luminous area of ​​each light fixture in each frame is segmented. Then, the lighting range area of ​​each light fixture at different time points is calculated, and the change of the lighting range area of ​​each light fixture over time is statistically analyzed. The time proportion of different lighting ranges is calculated using the following formula: Among them, S lamp (t) represents the area of ​​the illumination range, A lamp (t) represents the set of pixels in the illuminated area, where t represents different time points; Among them, P range T represents the time percentage of the illumination range. occur T is the cumulative time that a certain area of ​​a certain lighting fixture appears to be illuminated. tatalThe total observation time is used to determine the relative importance of each lighting range within the entire observation period by calculating the time percentage. This allows us to identify the most representative lighting range and then select the lighting range with the highest time percentage as the representative lighting range for that luminaire.

[0024] The indoor zone division module is used to divide the interior of a building into multiple indoor zones based on internal building data, lighting fixture installation locations, and lighting range. Using building wall data, a scan-line algorithm is used to identify enclosed spaces. Starting from one side of the space (such as the far left), the scan proceeds along a certain direction (such as horizontally to the right). When a wall is encountered, the state change is recorded. When the starting wall is encountered, a new area is started for recording, and when the ending wall is encountered, the current area is closed for recording. In this way, a preliminary area is identified based on the wall division.

[0025] The walking path statistical analysis unit 30 is used to extract the walking path of people based on historical video data and door lock recognition data, obtain the walking path of each person after the door lock is unlocked, and then perform probability statistical analysis on the walking path in combination with time nodes. The walking path statistical analysis unit 30 includes a walking path extraction module and a walking statistics module; The walking path extraction module is used to extract people's walking paths based on historical video data and door lock recognition data, and to obtain the walking path of each person after the door lock is unlocked; The walking statistics module is used to obtain the unlocking time of each walking path, and then perform probability statistical analysis on all walking paths together with the unlocking time to obtain the probability of each person passing through each walking path at different times. The specific steps are as follows: Personnel initial location positioning: When a door lock unlocking event is detected, the location of the door lock is used as the starting point of the walking path; Personnel walking path tracking: Starting from the path origin, the personnel position changes are tracked along the video frame time sequence, the displacement vector is accumulated frame by frame to construct the personnel walking path sequence, and then the trajectory of the personnel from unlocking to subsequent activities is completely recorded by continuously updating the path nodes.

[0026] Path probability statistical analysis based on unlocking time: We collected walking paths and corresponding unlocking times for all individuals over a six-month period to construct a path-time dataset. Assuming a total of N walking path samples, for each walking path and its unlocking time, we divided the data into time intervals, for example, one hour per interval. We then counted the number of times each path appeared within each time interval. The formula for calculating the probability of each individual traversing each walking path at different times is as follows: Among them, P ijTo represent the probability of each person traversing each walking path at different times, n ij The number of times a walking path appears within a time interval, k is an index variable used to iterate through all walking paths, N is the total number of walking path samples, and n kj This represents the number of times the k-th walking path appears within the time interval.

[0027] The control triggering unit 40 is used to establish a lighting control terminal based on the indoor division unit 20 and the walking path statistical analysis unit 30, and then combine the lighting control terminal with the online people statistics database to set up a control triggering mechanism. The control triggering unit 40 includes a terminal establishment module and a power-on triggering module; The terminal establishment module is used to establish a lighting control terminal based on all the data collected from the indoor division unit 20 and the walking path statistical analysis unit 30. At the same time, the lighting control terminal controls the electrical equipment inside the entire house through the Internet of Things.

[0028] The power-on trigger module is used to combine the lighting control terminal with the online people statistics database to set up the control trigger mechanism; When the online user statistics database shows that the number of online users is 0, the lighting control terminal will cut off the power to all internal electrical equipment. When the number of online users is updated in the online user statistics database and is not zero, the mechanism is triggered. First, the lights in the entrance hall are turned on, and at the same time, a signal is sent to the light selection unit 50 to perform lighting control operation. Turn on the entryway light to provide basic illumination for people entering.

[0029] After the lighting control operation is triggered, if a person manually turns off the lights, the subsequent automatic lighting control operation will stop until the number of online users reaches 0.

[0030] The lighting selection unit 50 is used to extract the walking path by combining the personnel identification data of the door lock identification data with the real time when the lighting control terminal is triggered, and then obtain the relevant indoor area based on the extracted walking path, and select the lighting fixture by combining the relevant indoor area. The lighting fixture selection unit 50 includes a path extraction module and a lighting fixture selection module; The path extraction module is used to extract the latest personnel identification data acquired by the smart door lock. Based on the personnel identification data and real-time time, the walking path is extracted to obtain the walking path of the person who unlocked the door with a corresponding probability of passing. The system queries previously collected data on the probability of different individuals traversing various walking paths within different time intervals. Based on the current real-time time interval, it finds the corresponding probability dataset and matches it to identify the walking paths with a probability of passage for the person who unlocked the door. In other words, it obtains the walking paths that meet the conditions and their corresponding paths. These paths and their probabilities can reflect the walking routes that the person is most likely to choose at the current time, providing a basis for subsequent lighting control.

[0031] The lighting selection module is used to filter relevant indoor areas by combining all indoor areas with the walking path obtained by the path extraction module, and then select lighting fixtures in the relevant indoor areas to obtain the lighting range that can achieve the desired coverage effect in each relevant indoor area. The specific steps are as follows: Relevant indoor area filtering: The walking path consists of a series of continuous coordinate points, P j For each location point on the path, P j = (x j y j Meanwhile, let one side of the polygon be from point (x) s1 y s1 ) to (x s2 y s2 The coordinates of the intersection point of ray r and the edge are (x... int y int ); When ray r is parallel to the side (i.e., y) s1 =y s2 And y s1 ≠y j If there is no intersection, then the equation of the line is as follows: When y int =y j When the time is right, the formula can be calculated as follows: When x int ≥x j If the edge intersects the ray, then the edge intersects the ray. If the number of intersection points is odd, then point P j Within the polygon, i.e., the area involved in the walking path, all points of the walking path are traversed, and the numbers of all indoor areas hit by the path points are recorded to form a set of related indoor areas.

[0032] Lighting Fixture Selection: For each area in the relevant set of indoor areas, traverse all lighting fixtures. Using a ray-mapping method similar to that used for point and polygon determination, for each vertex of the area, determine whether it is within the lighting range polygon of the lighting fixture. If all vertices of the area are within the lighting range polygon of the lighting fixture, then the lighting fixture can cover the area. Record the lighting fixture numbers that meet the condition in the lighting fixture list of the corresponding area.

[0033] The lighting control unit 60 is used to track the location of people based on real-time video data. At the same time, it sets a distance threshold based on the lighting brightness of the relevant indoor area where the person is located. Then, it selects other relevant indoor areas based on the direction of the person's movement and compares them with the distance threshold. Based on the comparison results, it controls the lighting of other relevant indoor areas in advance.

[0034] The lighting control unit 60 includes a walking analysis module, a distance threshold setting module, and a distance comparison module; The walking analysis module is used to track the location of people based on real-time video data and to predict and analyze the walking direction of people based on the acquired personnel location tracking data; The Kalman filter algorithm is introduced to optimize the tracking of personnel positions. Then, based on the continuous position information of the tracked personnel, the displacement vector of personnel at adjacent time moments is calculated. Personnel walking displacement vector data within a certain time window (such as the past 5 seconds or the 10-second personnel update unit) are collected to form a direction angle sequence. By analyzing the data of this sequence, the changing trend of personnel walking direction is analyzed. Then, short-term prediction is made based on the trend. Assuming that the current trend continues, the walking direction of personnel in the near future is predicted.

[0035] The distance threshold setting module is used to obtain the relevant indoor area where a person is located based on the person's location tracking data, and then set the distance threshold based on the current brightness of the lights in the relevant indoor area. The brighter the light fixture, the shorter the distance to the threshold. The lower the brightness of the light fixture, the longer the distance to the threshold, as shown in the formula below: Where D is the distance threshold, B is the lamp brightness, and k is a constant that can be adjusted according to the actual scenario and requirements. The distance comparison module is used to extract other relevant indoor areas based on the walking direction obtained by the walking analysis module. Then, it selects the other relevant indoor areas with the highest probability of passing and compares them with a distance threshold. When the distance between the person and other relevant indoor areas is less than the distance threshold, the lights in the other relevant indoor areas are turned on. Conversely, when the distance between the person and other relevant indoor areas is greater than the distance threshold, monitoring continues. The formula is as follows: Where, x person and y person Let x be the coordinates of the current location of the person. center and y center For the geometric center coordinates of other related indoor areas; If d < D, a control signal is triggered to send an on command to the lights in other relevant indoor areas, thus achieving advance lighting. If d≥D, then continue monitoring the personnel's location and direction of movement, and wait for the next distance calculation and comparison.

[0036] The second objective of this invention is to provide an online control method for intelligent terminals based on personnel identification and location tracking, including any one of the above-mentioned online control systems for intelligent terminals based on personnel identification and location tracking, comprising the following steps: S1. Establish an online people statistics database and collect door lock recognition data. Update the online people statistics database based on the door lock recognition data. Then, extract and analyze the internal building data, lighting installation location data, and lighting range of the building. Divide the building into indoor areas based on the data obtained from the analysis. S2. Extract people's walking paths based on historical video data and door lock recognition data, perform probability statistical analysis on the walking paths in conjunction with time nodes, establish a lighting control terminal, and then set up a control trigger mechanism by combining the lighting control terminal with the online people statistics database. S3. When the lighting control terminal is triggered, the personnel identification data of the door lock identification data is combined with the real time to extract the walking path, and the relevant indoor areas are combined to select lighting fixtures. S4. Set a distance threshold based on the brightness of the lights in the relevant indoor area where the person is located. Then, select other relevant indoor areas based on the direction the person is walking and compare them with the distance threshold. Based on the comparison results, control the lights in other relevant indoor areas to turn on in advance.

[0037] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent terminal online control system based on personnel identification and location tracking, characterized in that: It includes a people update unit (10), an indoor division unit (20), a walking path statistical analysis unit (30), a control trigger unit (40), a lamp selection unit (50), and a lamp activation control unit (60). The number of people update unit (10) is used to establish an online number of people statistics database, and at the same time collect door lock identification data, and update the number of online people in the online number of people statistics database according to the door lock identification data; The indoor division unit (20) is used to collect historical video data, and at the same time extract and analyze the internal building data, lamp installation location data and lamp lighting range of the house, and divide the house into indoor areas based on the data obtained from the analysis; The walking path statistical analysis unit (30) is used to extract the walking path of personnel based on historical video data and door lock recognition data, obtain the walking path of each person after the door lock is unlocked, and then perform probability statistical analysis on the walking path in combination with time nodes. The control triggering unit (40) is used to establish a lighting control terminal based on the indoor division unit (20) and the walking path statistical analysis unit (30), and then combine the lighting control terminal with the online people statistics database to set up a control triggering mechanism; The lamp selection unit (50) is used to extract the walking path by combining the personnel identification data of the door lock identification data with the real time when the lighting control terminal is triggered, and then obtain the relevant indoor area according to the extracted walking path, and select lamps by combining the relevant indoor area; The lighting control unit (60) is used to track the location of personnel based on real-time video data, and set a distance threshold based on the lighting brightness of the relevant indoor area where the personnel are located. Then, it selects other relevant indoor areas based on the direction of the personnel's walking and compares them with the distance threshold. Based on the comparison results, it controls the lighting of other relevant indoor areas in advance.

2. The intelligent terminal online control system based on personnel identification and location tracking according to claim 1, characterized in that: The number of people update unit (10) establishes an online number of people statistics database in the smart lock through Internet of Things technology, and collects the door lock identification data of the smart lock, and updates the online number of people in the online number of people statistics database according to the door lock identification data.

3. The intelligent terminal online control system based on personnel identification and location tracking according to claim 1, characterized in that: The indoor partitioning unit (20) establishes a data transmission connection through Internet of Things technology and indoor monitoring devices, and obtains indoor historical video data and real-time video data by extracting historical data and real-time data from the monitoring devices.

4. The intelligent terminal online control system based on personnel identification and location tracking according to claim 1, characterized in that: The indoor division unit (20) includes a data extraction and analysis module and an indoor area division module; The data extraction and analysis module is used to analyze the interior building data and lighting installation location of the room based on historical video data, thereby establishing an interior three-dimensional model based on the interior building data, filling the corresponding lighting installation location in the three-dimensional building model, and then extracting the lighting range of each lighting fixture and the time proportion of different lighting ranges by combining historical video data, and then taking the lighting range with the highest time proportion as the lighting range represented by that lighting fixture. The indoor area division module is used to divide the interior of the house into multiple indoor areas based on internal building data, lighting installation locations, and lighting range.

5. The intelligent terminal online control system based on personnel identification and location tracking according to claim 1, characterized in that: The walking path statistical analysis unit (30) includes a walking path extraction module and a walking statistics module; The walking path extraction module is used to extract the walking path of people based on historical video data and door lock recognition data, and to obtain the walking path of each person after the door lock is unlocked. The walking statistics module is used to obtain the unlocking time of each walking path, and then perform probability statistical analysis on all walking paths in combination with the unlocking time to obtain the probability of each person passing through each walking path at different times.

6. The intelligent terminal online control system based on personnel identification and location tracking according to claim 1, characterized in that: The control triggering unit (40) includes a terminal establishment module and a power-on triggering module; The terminal establishment module is used to establish a lighting control terminal based on all the data collected from the indoor division unit (20) and the walking path statistical analysis unit (30). At the same time, the lighting control terminal controls the internal electrical equipment of the entire house through the Internet of Things. The power-on trigger module is used to combine the lighting control terminal with the online people statistics database to set up a control trigger mechanism; When the online user statistics database shows that the number of online users is 0, the lighting control terminal will cut off the power to all internal electrical equipment. When the number of online users is updated in the online user statistics database and is not zero, the mechanism is triggered. First, the lights in the entrance hall are turned on, and at the same time, a signal is sent to the light selection unit (50) to perform lighting control operation. After the lighting control operation is triggered, if a person manually turns off the lights, the subsequent automatic lighting control operation will stop until the number of online users reaches 0.

7. The intelligent terminal online control system based on personnel identification and location tracking according to claim 1, characterized in that: The lamp selection unit (50) includes a path extraction module and a lamp selection module; The path extraction module is used to extract the latest personnel identification data acquired by the smart door lock, and extract the walking path based on the personnel identification data and real-time time to obtain the walking path of the person who unlocked the door with a corresponding probability of passing. The lighting selection module is used to filter relevant indoor areas by combining all indoor areas with the walking path obtained by the path extraction module, obtain the relevant indoor areas involved in the walking path, and then select lighting fixtures in the relevant indoor areas to obtain the lighting range of each relevant indoor area that can achieve the coverage effect.

8. The intelligent terminal online control system based on personnel identification and location tracking according to claim 1, characterized in that: The lighting control unit (60) includes a walking analysis module, a distance threshold setting module, and a distance comparison module; The walking analysis module is used to track the location of people based on real-time video data and to predict and analyze the walking direction of people based on the acquired personnel location tracking data. The distance threshold setting module is used to obtain the relevant indoor area where the person is located based on the personnel location tracking data, and then set the distance threshold based on the current lighting brightness of the relevant indoor area. The brighter the light fixture, the shorter the distance to the threshold. The lower the brightness of the light fixture, the longer the distance from the threshold. The distance comparison module is used to extract other relevant indoor areas based on the walking direction obtained by the walking analysis module. Then, it selects the other relevant indoor areas with the highest probability of passing and compares them with a distance threshold. When the distance between the person and other relevant indoor areas is less than the distance threshold, it controls the lights in the other relevant indoor areas to be turned on. Conversely, when the distance between the person and other relevant indoor areas is greater than the distance threshold, it continues to monitor.

9. A method for implementing online control of intelligent terminals based on personnel identification and location tracking, comprising the online control system for intelligent terminals based on personnel identification and location tracking as described in any one of claims 1-8, characterized in that: The steps include the following: S1. Establish an online people statistics database and collect door lock recognition data. Update the online people statistics database based on the door lock recognition data. Then, extract and analyze the internal building data, lighting installation location data, and lighting range of the building. Divide the building into indoor areas based on the data obtained from the analysis. S2. Extract people's walking paths based on historical video data and door lock recognition data, perform probability statistical analysis on the walking paths in conjunction with time nodes, establish a lighting control terminal, and then set up a control trigger mechanism by combining the lighting control terminal with the online people statistics database. S3. When the lighting control terminal is triggered, the personnel identification data of the door lock identification data is combined with the real time to extract the walking path, and the relevant indoor areas are combined to select lighting fixtures. S4. Set a distance threshold based on the brightness of the lights in the relevant indoor area where the person is located. Then, select other relevant indoor areas based on the direction the person is walking and compare them with the distance threshold. Based on the comparison results, control the lights in other relevant indoor areas to turn on in advance.

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