Bidirectional conversation type home tumble identification system based on remote control of Internet of Things

Abstract

The invention relates to the technical field of smart home, and discloses a two-way call type home tumble recognition system based on remote control of the Internet of Things, which comprises a tumble recognition analysis module, a home equipment connection state acquisition module, a home equipment risk assessment module and a home equipment control module, the tumble recognition module comprises a tumble recognition judgment unit and a tumble risk assessment unit. According to the system, the falling condition of a user is comprehensively analyzed by reading a falling area of the user and analyzing and calculating to obtain an area weight coefficient, so that whether falling early warning needs to be carried out or not is judged, meanwhile, the system can give out emergency early warning during early warning, visual and auditory warning is carried out by controlling lamplight and loudspeaker equipment in a house, and the user experience is improved. The system can automatically cut off the circuit of the intelligent cooking equipment and close the gas valve of the internet of things, so that secondary damage caused by falling is prevented, and the intelligent household equipment is controlled in a linkage manner after the falling condition of the user is identified.

Description

Technical Field

[0001] The present invention relates to the technical field of smart home, and specifically provides a two-way call type home fall recognition system based on Internet of Things remote control. Background Art

[0002] Smart home is a platform based on a residence, which integrates facilities related to home life by using comprehensive wiring technology, network communication technology, security prevention technology, automatic control technology and audio-video technology to build an efficient management system for residential facilities and family daily affairs, improve the safety, convenience, comfort and artistry of the home, and achieve an environmentally friendly and energy-saving living environment. However, currently, when facing the situation of a home fall, smart home cannot intelligently judge the user's fall situation and perform corresponding control according to the user's fall situation. Summary of the Invention

[0003] Aiming at the deficiencies of the prior art, the present invention provides a two-way call type home fall recognition system based on Internet of Things remote control, which has the advantages of recognizing user falls and controlling smart home devices for intelligent control, etc., and solves the above technical problems.

[0004] To achieve the above object, the present invention provides the following technical solution: A two-way call type home fall recognition system based on Internet of Things remote control, including a fall recognition and analysis module, a home device connection status acquisition module, a home device risk assessment module and a home device control module; The fall recognition module analysis includes a fall recognition judgment unit and a fall risk assessment unit. The fall recognition judgment unit is used to recognize the user's state and judge whether the user has fallen. After judging that the user has fallen, the user's fall time is recorded. The fall risk analysis unit includes a fall area recognition subunit and a fall risk assessment subunit. The fall area recognition subunit is used to read the area where the user has fallen and analyze and calculate to obtain an area weight coefficient. The fall risk assessment subunit calculates a fall risk coefficient based on the user's fall time and the area weight coefficient; The home device connection status acquisition module is used to acquire the connection status of several different home smart devices and analyze to obtain the stability of the home smart devices; The home device risk assessment module judges the safety state of the device based on the stability of the home smart device; The home device control module includes a voice call unit, a user control unit, and an emergency control unit. The voice call unit is used to handle the communication between the user and the contacts set by the user or emergency warnings. The user control unit is used to provide a control command input port for the user to control the home intelligent devices. The emergency control unit executes an emergency control strategy based on the stability of the home intelligent devices and the fall risk coefficient.

[0005] As a preferred technical solution of the present invention, the fall recognition and judgment unit is used to recognize the user's state and judge whether the user has fallen. The methods include a wearable gyroscope and a camera device equipped with a fall recognition algorithm. The fall recognition algorithm realizes the recognition of the user's state through YOLOv5, including standing, falling, and moving.

[0006] As a preferred technical solution of the present invention, the specific expression for the fall recognition and judgment unit to record the user's fall time after judging that the user has fallen is as follows: ; Where represents the fall time, represents the current moment, represents the moment when the fall recognition and judgment unit recognizes the fall. If the fall recognition and judgment unit recognizes that the user's state has changed to standing, the call to the fall area recognition sub-unit will be terminated.

[0007] As a preferred technical solution of the present invention, the fall area recognition sub-unit is used to read the area where the user has fallen and analyze and calculate to obtain the area weight coefficient The specific steps are as follows: Step A1: Obtain the floor of the user's fall area in the user's home environment. If there is only one floor, execute Step A2; if there are multiple floors, execute Step A3; Step A2: Obtain the straight-line distance from the user's fall area to the door of the user's home environment, and set this straight-line distance as the first-layer distance , and then obtain the number of doorways passed from the first-layer entrance to the user's fall area in the user's home environment , and calculate to obtain the area weight coefficient The specific expression is as follows: ; Where represents the area weight coefficient, represents the number of doorways passed from the entrance to the user's fall area in the user's home environment, represents the first-layer distance; Step A3: Obtain the straight-line distance from the first-layer entrance to the stairs, and set it as the first-layer distance , obtain the The number of doorways passed from the floor entrance to the user's fall area in the user's home environment and calculate the regional weight coefficient The specific expression of which is as follows: ; Wherein, represents the natural constant, represents the distance of the first layer, represents the number of doorways passed from the floor entrance to the user's fall area in the user's home environment, represents the floor where the user falls.

[0008] As a preferred technical solution of the present invention, the specific expression of the fall risk coefficient calculated by the fall risk assessment subunit based on the user's fall time and the regional weight coefficient is as follows: ; Wherein, and respectively represent weight coefficients whose sum is 1, represents the regional weight coefficient, represents the fall time, represents the fall risk coefficient.

[0009] As a preferred technical solution of the present invention, the steps for the home device connection status acquisition module to collect the connection status of several different home intelligent devices and analyze the stability of the home intelligent devices are as follows: Step B1: Obtain the connection failure rate of the th home device; Step B2: Obtain the damage failure rate of the th home device; Step B3: Calculate the stability of the th home device.

[0010] As a preferred technical solution of the present invention, the specific expression of obtaining the connection failure rate of the th home device in Step B1 is as follows: ; Wherein, represents the connection failure rate of the th home device, represents the number of days of use of the th home device, represents the number of disconnection times of the th home device; In Step B2, obtaining the The failure rate of a home device The specific expression is as follows: ; Wherein, represents the failure rate of the th home device, represents the number of days of use of the th home device, represents the number of repairs of the th home device.

[0011] As a preferred technical solution of the present invention, the specific expression for calculating the stability of the th home device in step B3 is as follows: ; ; Wherein, represents the stability of the th home device, represents the failure rate of the th home device, represents the connection failure rate of the th home device.

[0012] As a preferred technical solution of the present invention, the specific steps for the home device risk assessment module to judge the safety status of the device based on the stability of the home intelligent device are as follows: When the stability of the th home device is lower than the stability threshold set by the user , the home device risk assessment module issues a replacement warning. When the stability of the th home device is not lower than the stability threshold set by the user , no warning is issued.

[0013] As a preferred technical solution of the present invention, the specific steps for the emergency control unit to execute the emergency control strategy based on the stability of the home intelligent device and the fall risk coefficient are as follows: Step C1: When the fall risk coefficient exceeds the set fall risk threshold , step C2 is executed. When the fall risk coefficient exceeds the set fall risk threshold , step C3 is executed; Step C2: Send a voice communication request to the contact set by the user through the voice call unit, and the contact set by the user inquires about the fall status. If the voice communication request is not connected, step C2 is terminated and step C1 is recursively executed until the contact set by the user connects to the voice communication request or step C3 is called; Step C3: Send an emergency warning to the contacts set by the user through the voice call unit, read the top n devices with stable lights and speakers that can be controlled among all home devices, and perform flashing and audible warnings at the same frequency. At the same time, cut off the circuit of the intelligent cooking device and close the Internet of Things gas valve until the fall recognition and judgment unit can no longer recognize the fall state.

[0014] Compared with the prior art, the present invention provides a two-way call type home fall recognition system based on Internet of Things remote control, which has the following beneficial effects: The present invention reads the area where the user falls, analyzes and calculates the area weight coefficient, and comprehensively analyzes the user's fall situation to determine whether a fall warning is needed. At the same time, when warning, the system will also issue an emergency warning, and visually and auditorily warn by controlling the lights and speakers in the home, increasing the success rate of the alarm. The system will automatically cut off the circuit of the intelligent cooking device and close the Internet of Things gas valve to prevent secondary injuries caused by falls, thus realizing the linkage control of smart home devices after recognizing the user's fall situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the system framework of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0017] Please refer to Figure 1 , a two-way call type home fall recognition system based on Internet of Things remote control, including a fall recognition and analysis module, a home device connection status acquisition module, a home device risk assessment module, and a home device control module; The fall recognition module analysis includes a fall recognition and judgment unit and a fall risk assessment unit. The fall recognition and judgment unit is used to recognize the user's state and judge whether the user has fallen. After judging that the user has fallen, the fall time of the user is recorded. The fall risk analysis unit includes a fall area recognition sub-unit and a fall risk assessment sub-unit. The fall area recognition sub-unit is used to read the area where the user falls and analyze and calculate the area weight coefficient. The fall risk assessment sub-unit calculates the fall risk coefficient based on the user's fall time and the area weight coefficient; The fall recognition and judgment unit uses a wearable gyroscope and a camera device equipped with a fall recognition algorithm to identify the user's state and determine whether the user has fallen. The fall recognition algorithm uses YOLOv5 to identify the user's state, including standing, falling, and moving.

[0018] The specific expression for the fall recognition and judgment unit to record the user's fall time after determining that the user has fallen is as follows: ; Among them, represents the fall time, represents the current moment, represents the moment when the fall recognition and judgment unit recognizes the fall. If the fall recognition and judgment unit recognizes that the user's state has changed to standing, the fall area recognition subunit will be terminated from being called; The fall area recognition subunit is used to read the area where the user has fallen and analyze and calculate the area weight coefficient The specific steps are as follows: Step A1: Obtain the floor of the user's fall area in the user's home environment. If there is only one floor, execute Step A2; if there are multiple floors, execute Step A3; Step A2: Obtain the straight-line distance from the user's fall area to the door in the user's home environment, and set this straight-line distance as the first-floor distance , and then obtain the number of doors passed from the first-floor entrance to the user's fall area in the user's home environment , and calculate the area weight coefficient The specific expression is as follows: ; Among them, represents the area weight coefficient, represents the number of doors passed from the entrance to the user's fall area in the user's home environment, represents the first-floor distance; Step A3: Obtain the straight-line distance from the first-floor entrance to the stairs, and set it as the first-floor distance , obtain the number of doors passed from the entrance on the th floor to the user's fall area in the user's home environment The specific expression for calculating the area weight coefficient ; Among them, represents the natural constant, represents the first-floor distance, represents the th floor, Indicates the floor where the user falls. By considering the difficulty of rescue at different floors, comprehensive analysis is achieved. The number of door passes from the entrance on the th floor to the area where the user falls in the user's home environment can be obtained by storing fixed values in the identification devices in each different area. When the identification device recognizes it, it is automatically input . If it is recognized in multiple areas, it means that the human body is in the junction area of multiple devices. In this case, the smallest one is taken; The home device connection status acquisition module is used to acquire the connection status of several different home intelligent devices and analyze the stability of the home intelligent devices. The specific steps are as follows: Step B1: Obtain the connection failure rate of the th home device ; In step B1, the specific expression for obtaining the connection failure rate of the th home device is as follows: ; Among them, represents the connection failure rate of the th home device, represents the number of days of use of the th home device, represents the number of disconnection times of the th home device; Step B2: Obtain the damage failure rate of the th home device ; In step B2, the specific expression for obtaining the damage failure rate of the th home device is as follows: ; Among them, represents the damage failure rate of the th home device, represents the number of days of use of the th home device, represents the number of repair times of the th home device; Step B3: Calculate the stability of the th home device .

[0019] In step B3, the specific expression for calculating the stability of the th home device is as follows: ; Among them, represents the stability of the th home device, Indicates the failure rate of the th home device, Indicates the connection failure rate of the th home device; The specific expression for the fall risk assessment subunit to calculate the fall risk coefficient based on the user's fall time and area weight coefficient is as follows: ; Where, and respectively represent the weight coefficients that sum to 1, represents the area weight coefficient, represents the fall time, represents the fall risk coefficient; The home device risk assessment module determines the safety status of the device based on the stability of the home intelligent device, can monitor the stability of the home device in real time, and immediately issue a replacement warning when the detected stability is lower than the set threshold. This helps to detect and solve problems in a timely manner, avoid potential safety risks, and through preventive maintenance, it is possible to avoid emergency repairs or replacements caused by sudden device failures, and in the long run, it can save the user the costs of maintenance and replacement; The specific steps for the home device risk assessment module to determine the safety status of the device based on the stability of the home intelligent device are as follows: When the stability of the th home device is lower than the stability threshold set by the user , then the home device risk assessment module issues a replacement warning. When the stability of the th home device is not lower than the stability threshold set by the user , no warning is issued; The home device control module includes a voice call unit, a user control unit, and an emergency control unit. The voice call unit is used to handle the communication or emergency warning between the user and the contacts set by the user. The user control unit is used to provide a control command input port for the user to control the home intelligent device. The emergency control unit executes the emergency control strategy based on the stability of the home intelligent device and the fall risk coefficient, and can immediately activate the voice call unit to send a communication request to the preset contacts and inquire about the fall status. This real-time response mechanism can quickly obtain external help and reduce the serious consequences that may be caused by a fall; The specific steps for the emergency control unit to execute the emergency control strategy based on the stability of the home intelligent device and the fall risk coefficient are as follows: Step C1: When the fall risk coefficient exceeds the set fall risk threshold , execute Step C2. When the fall risk coefficient Exceed the set fall risk threshold Execute step C3; Step C2: Send a voice communication request to the contact set by the user through the voice call unit, and the contact set by the user asks about the fall status. If the voice communication request is not connected, terminate step C2 and recursively execute step C1 until the contact set by the user connects to the voice communication request or step C3 is called. Even when the voice communication request is not connected, continue to try to contact the preset contact until successful or other emergency measures are triggered; Step C3: Send an emergency warning to the contact set by the user through the voice call unit, and read the top n devices with stable lights and speaker devices that can be controlled among all home devices for synchronous flashing and speaker warning at the same frequency. At the same time, cut off the circuit of the intelligent cooking device and close the Internet of Things gas valve until the fall recognition and judgment unit cannot recognize the fall status. At the same time, it can be preset by the user whether to associate with the intelligent door lock. When the emergency warning is triggered, the intelligent door lock is synchronously opened to keep the door open for subsequent rescue. Embodiment

[0020] In this embodiment, the area where the user falls is on the second floor of the user's home. For other parameters, refer to Table 1 below: Table 1 ; Calculate the area weight coefficient , calculate and obtain Exceed the set fall risk threshold , send an emergency warning to the contact set by the user through the voice call unit, and read the top n devices with stable lights and speaker devices that can be controlled among all home devices for synchronous flashing and speaker warning at the same frequency. At the same time, cut off the circuit of the intelligent cooking device and close the Internet of Things gas valve; In this embodiment, some home devices are shown in Table 2: ; At this time The corresponding device is lower than the warning value. At this time, send a replacement warning to the home device risk assessment module; In the above embodiment, the setting of the threshold value is for the convenience of comparison. Regarding the size of the threshold value, it depends on the amount of sample data and the base quantity set by those skilled in the art for each set of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values, it can be determined by those skilled in the art based on each sample data and multiple rounds of experimental processes, and the calculated data has been processed to remove the dimension; Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A two-way communication home fall recognition system based on remote control of the Internet of Things, characterized by: It includes a fall recognition and analysis module, a home device connection status acquisition module, a home device risk assessment module, and a home device control module; The fall identification module analysis includes a fall identification and judgment unit and a fall risk assessment unit. The fall identification and judgment unit is used to identify the user status and judge whether the user falls. After judging that the user falls, the user's fall time is recorded. The fall risk analysis unit includes a fall area identification subunit and a fall risk assessment subunit. The fall area identification subunit is used to read the area where the user falls and analyze and calculate to obtain the area weight coefficient. The fall risk assessment subunit calculates the fall risk coefficient based on the user's fall time and the area weight coefficient. The home device connection status collection module is used to collect the connection status of several different home smart devices and analyze the stability of the home smart devices; The home device risk assessment module determines the safety status of the device based on the stability of the home smart device; The home device control module includes a voice call unit, a user control unit and an emergency control unit. The voice call unit is used to handle communication or emergency warnings between a user and a contact person set by the user. The user control unit is used to provide a control command input port for the user to control the home smart device. The emergency control unit executes an emergency control strategy based on the stability and fall risk factor of the home smart device.

2. According to claim 1, a two-way communication home fall recognition system based on remote control of the Internet of Things is characterized by: The fall recognition and judgment unit is used to identify the user state and determine whether the user falls, including a wearable gyroscope and a camera device equipped with a fall recognition algorithm, and the fall recognition algorithm realizes user state recognition through YOLOv5, including standing, falling and moving.

3. According to claim 2, a two-way communication home fall recognition system based on remote control of the Internet of Things is characterized by: The specific expression of the fall recognition and judgment unit recording the user's fall time after judging that the user has fallen is as follows: ; in, Indicates the time of fall, Indicates the current moment, It indicates the moment when the fall recognition and judgment unit recognizes a fall. If the fall recognition and judgment unit recognizes that the user's state changes to standing, the call of the fall area recognition subunit is terminated.

4. According to claim 3, a two-way communication home fall recognition system based on remote control of the Internet of Things is characterized by: The fall area identification subunit is used to read the area where the user falls and analyze and calculate the area weight coefficient The specific steps are as follows: Step A1: Obtain the floor of the user's home environment in the area where the user falls. If there is only one floor, execute step A2; if there are multiple floors, execute step A3; Step A2: Get the straight-line distance from the user's falling area to the door of the user's home environment, and set the straight-line distance as the first-layer distance , and then obtain the number of doors passed from the first-floor entrance to the user's home environment where the user fell , and calculate the regional weight coefficient The specific expression is as follows: ; in, represents the regional weight coefficient, Indicates the number of doors passed from the entrance to the area where the user falls in the user's home environment. Indicates the first layer distance; Step A3: Get the straight-line distance from the first-floor entrance to the stairs and set it as the first-floor distance , get the Number of doors passed from the floor entrance to the user's home environment where the user fell , and calculate the regional weight coefficient The specific expression is as follows: ; in, represents a natural constant, represents the first layer distance, Indicates The number of doors passed from the floor entrance to the user's home environment where the user fell, Indicates the floor the user fell.

5. According to claim 4, a two-way communication home fall recognition system based on remote control of the Internet of Things is characterized by: The specific expression of the fall risk coefficient calculated by the fall risk assessment subunit based on the user's fall time and area weight coefficient is as follows: ; in, and They represent weight coefficients that sum to 1, represents the regional weight coefficient, Indicates the time of fall, Represents the fall risk factor.

6. A two-way communication home fall recognition system based on remote control of the Internet of Things according to claim 5, characterized in that: The steps of the home device connection status acquisition module for acquiring the connection status of several different home smart devices and analyzing the stability of the home smart devices are as follows: Step B1: Get the Connection failure rate of home devices ; Step B2: Get the The failure rate of household equipment ; Step B3: Calculate the Stability of home devices .

7. A two-way communication home fall recognition system based on IoT remote control according to claim 6, characterized in that: In step B1, the Connection failure rate of home devices The specific expression is as follows: ； in, Indicates Connection failure rate of home devices, Indicates The number of days that home devices are used, Indicates Number of disconnections of home devices; In step B2, the first The failure rate of household equipment The specific expression is as follows: ; in, Indicates The failure rate of household equipment Indicates The number of days that home devices are used, Indicates Number of home equipment repairs.

8. The two-way communication home fall recognition system based on remote control of the Internet of Things according to claim 7 is characterized by: In step B3, the calculation Stability of home devices The specific expression is as follows: ; in, Indicates The stability of home equipment Indicates The failure rate of household equipment Indicates The connection failure rate of each home device.

9. A two-way communication home fall recognition system based on remote control of the Internet of Things according to claim 8, characterized in that: The specific steps of the home device risk assessment module for judging the safety status of the device based on the stability of the home smart device are: Stability of home devices Below user-defined stability threshold When the home equipment risk assessment module issues a replacement warning, Stability of home devices Not less than the stability threshold set by the user No warning is given when 10. A two-way communication home fall recognition system based on remote control of the Internet of Things according to claim 9, characterized in that: The specific steps of the emergency control unit executing the emergency control strategy based on the stability and fall risk coefficient of the home smart device are as follows: Step C1: When the fall risk factor Exceeding the set fall risk threshold Step C2 is executed when the fall risk factor Exceeding the set fall risk threshold When , execute step C3; Step C2: sending a voice communication request to the contact set by the user through the voice call unit, and the contact set by the user inquires about the fall status. If the voice communication request is not connected, terminate step C2 and recursively execute step C1 until the contact set by the user connects the voice communication request or step C3 is called; Step C3: Send an emergency warning to the contacts set by the user through the voice call unit, read the stability of the lights and speaker devices that can be controlled in all home devices, and give a flashing and loudspeaker warning at the same frequency for the top n devices. At the same time, cut off the circuit of the smart cooking device and close the IoT gas valve until the fall recognition and judgment unit can no longer recognize the fall state.

Images