A fall detection floor and method

Abstract

The invention relates to a fall detection floor, comprising: a power supply module, a sensor input module, a microcontroller module, a heating module, a network transmission module and an Internet of Things platform. The invention has the following beneficial effects: the fall detection floor is based on an STM32 chip; the heating module is designed to heat and dry water droplets on the surface of the floor; the semiconductor refrigeration sheet in the heating module is used for heating; the thermal conductive pad in the heating module makes full use of heat conduction to make the water on the sole of the pedestrian evaporate quickly, with high thermal efficiency and shortening the drying time of the sole; a gravity sensor is used to detect the sudden change of gravity when the pedestrian passes by, and whether a fall event occurs is determined based on whether normal gravity is restored; a strain resistor is added to determine whether the shape of the force-bearing area is consistent with the contour of the human body, thereby improving the accuracy of judging the fall event; the fall detection floor has a simple structure, and the installation method is suspended laying, which is easy to install and maintain; the Internet of Things platform is convenient for users to debug the temperature condition of the floor.

Description

Technical Field

[0001] The present invention relates to the field of human fall detection on the floor, and in particular comprises a fall detection floor and a method. Background Art

[0002] Traditional indoor wooden floors have high requirements for the use environment. They are prone to expansion, deformation, mildew, and insect in a humid environment, and are prone to shrinkage, deformation, and cracking in a dry environment. Finished or semi-finished products are generally formed by a coating process to form a smooth paint layer on the surface to protect the wooden floor and increase the service life and beauty of the wooden floor. However, since the paint surface of the traditional wooden floor is relatively smooth, it is easy for people to slip when walking on it, especially when the floor surface is wet, a water film is easily formed on its smooth surface, making it even more slippery.

[0003] Since there are no floor products that can dry water stains on shoe soles in the market, it is particularly important to propose a fall detection floor and method. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a fall detection floor and method.

[0005] The fall detection floor comprises: a power supply module, a sensor input module, a microcontroller module, a heating module, a network transmission module and an Internet of Things platform; the heating module comprises a thermal pad, a heating port and a semiconductor cooling sheet; the thermal pad is arranged on the surface layer of the floor, the heating port is arranged in the floor cavity below the thermal pad, and the semiconductor cooling sheet is placed in the heating port; the microcontroller module is connected to the Internet of Things platform through the network transmission module;

[0006] The power supply module includes a linear adjustable power supply and an external switching power supply; the external switching power supply supplies power to the heating module, and the linear adjustable power supply supplies power to the remaining modules;

[0007] The sensor input module includes a raindrop sensor, a temperature sensor and a gravity sensor; the raindrop sensor, the temperature sensor and the gravity sensor are all arranged on the surface layer of the floor;

[0008] The main controller of the microcontroller module is a single chip microcomputer; the input of the single chip microcomputer is gravity data collected by the gravity sensor, temperature data collected by the temperature sensor and rainfall data collected by the raindrop sensor.

[0009] Preferably, a plurality of columns of strain resistors are installed at the mechanical layer below the thermally conductive pad; a microprocessor controller is provided to collect analog signals of the strain resistors, and the microprocessor controller is connected to a main controller of the microcontroller module via an IIC serial connection.

[0010] Preferably, the linear adjustable power supply outputs a voltage of 3.3V to supply power to the microcontroller module.

[0011] Preferably, the single chip microcomputer is STM32F103C8T6; the linear adjustable power supply is LM317; and the temperature sensor is DS18B20.

[0012] Preferably, the network transmission module is ESP8266.

[0013] Preferably, the gravity sensor is HX711.

[0014] The working method of the fall detection floor specifically includes the following steps:

[0015] S1, the microcontroller module's single chip microcomputer starts working and initializes the peripherals;

[0016] S2, the single chip microcomputer obtains the gravity sensor data, the temperature sensor data and the raindrop sensor data;

[0017] S3, the MCU sends a command to the network transmission module, and the network transmission module receives the command and sends an MQTT connection request to the IoT platform; if the MQTT connection request is successful, the MCU uploads the JSON data to the IoT platform through the network transmission module; if the MQTT connection request is not successful, the network transmission module sends the MQTT connection request to the IoT platform again until it is successful;

[0018] S4. If the gravity sensor detects that a pedestrian is passing by and the raindrop sensor detects rainfall data, the heating module starts to heat the floor;

[0019] S5. If the gravity sensor detects a sudden change in gravity while a pedestrian is passing by, the impact force of the fall is obtained according to F=mv / t and an approximate value is taken; if the approximate value of the impact force is greater than the set threshold, it is determined whether normal gravity is restored after a fixed time; if normal gravity is restored, it is determined as a fall event; F is force, m is the mass of the object, and v is the velocity;

[0020] S6. If it is determined that a fall event occurs, an alarm message is sent; otherwise, no alarm message is sent, and the process returns to step S4.

[0021] Another working method of a fall detection floor comprises the following steps:

[0022] S1, the microcontroller module's single chip microcomputer starts working and initializes the peripherals;

[0023] S2, the single chip microcomputer obtains the gravity sensor data, the temperature sensor data and the raindrop sensor data;

[0024] S3, the MCU sends a command to the network transmission module, and the network transmission module receives the command and sends an MQTT connection request to the IoT platform; if the MQTT connection request is successful, the MCU uploads the JSON data to the IoT platform through the network transmission module; if the MQTT connection request is not successful, the network transmission module sends the MQTT connection request to the IoT platform again until it is successful;

[0025] S4. If the gravity sensor detects that a pedestrian is passing by and the raindrop sensor detects rainfall data, the heating module starts to heat the floor;

[0026] S5. Fall detection:

[0027] S5.1. Detecting a sudden change in gravity. If the gravity sensor detects a sudden change in gravity while detecting a pedestrian passing by, the impact force of the fall is obtained according to F=mv / t and an approximate value is taken; F is the force, m is the mass of the object, and v is the velocity;

[0028] S5.2, if the approximate value of the impact force is greater than the set threshold, determine whether normal gravity is restored after a fixed time; if normal gravity is restored, it is determined as a fall event and step S5.3 is executed; otherwise, it is not a fall event;

[0029] S5.3, the microprocessor controller obtains the force area according to the position of the strain resistance response data, and if the obtained force area is greater than the set value, the force area data is uploaded to the Internet of Things platform;

[0030] S5.4. The IoT platform generates coordinate locations for the gravity sensing positions of each force-bearing area data; Python3 is used to convert the coordinate data into a binary image;

[0031] S5.5. Use opencv and imutils to determine whether the binary image is a human body contour image;

[0032] S5.6, if the binary image is determined to be a human body contour image in S5.5, then it is determined that a fall event occurs;

[0033] S6. If it is determined that a fall event occurs, an alarm message is sent; otherwise, no alarm message is sent, and the process returns to step S4.

[0034] Preferably, the Internet of Things platform in step S3 is OneNet platform; and the alarm message in step S5 is sent by a trigger of OneNet.

[0035] The beneficial effects of the present invention are: the fall detection floor is based on the stm32 chip; the heating module is designed to heat and dry water droplets on the surface of the floor; the semiconductor refrigeration sheet in the heating module is used for heating; the thermal conductive pad in the heating module makes full use of heat conduction to make the moisture on the soles of pedestrians evaporate quickly, with high thermal efficiency and shortened drying time of the soles; a gravity sensor is used to detect the sudden change of gravity when pedestrians pass by, and whether a fall event occurs is judged based on whether normal gravity is restored; a strain resistor is added to judge whether the shape of the force-bearing area conforms to the contour of the human body, thereby improving the accuracy of judging a fall event; the fall detection floor has a simple structure, and the installation method is suspended laying, which is easy to install and maintain; the Internet of Things platform facilitates users to debug the temperature condition of the floor. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Hardware block diagram for fall detection floor;

[0037] Figure 2 This is the operation flow chart of each module of the fall detection floor;

[0038] Figure 3 This is the model diagram for force area detection;

[0039] Figure 4 Floor model diagram for fall detection;

[0040] Figure 5 This is the minimum system diagram for STM32F103C8T6;

[0041] Figure 6 This is the schematic diagram of the power module;

[0042] Figure 7 Provide the wiring diagram for the network module circuit;

[0043] Figure 8 This is the MOSFET driving circuit diagram;

[0044] Fig. 9 This is the schematic diagram of ds18b20;

[0045] Fig.10 This is the circuit schematic diagram of the HX711 module;

[0046] Fig.11 The wiring diagram for the HX711 circuit;

[0047] Fig.12 This is the schematic diagram of the raindrop sensor circuit;

[0048] Fig.13 Wiring diagram for raindrop sensor circuit;

[0049] Fig.14 Display graph for IoT;

[0050] Fig.15 This is the actual circuit schematic.

[0051] Description of the reference numerals: strain resistor 1, heating port 2, thermal conductive pad 3. DETAILED DESCRIPTION

[0052] The present invention is further described below in conjunction with embodiments. The description of the following embodiments is only used to help understand the present invention. It should be noted that for ordinary persons in the art, without departing from the principle of the present invention, the present invention can also be modified in some ways, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

[0053] The fall detection floor of the present invention uses STM32F103C8T6 as the core unit to collect temperature, pressure and other data, and then transmits it to a third-party network platform (OneNet) through the esp8266 module using the MQTT protocol, so that users can observe their own data. A heating module is added, which can enable this product to turn on the heating function to heat the floor surface when pedestrians pass by after judging the temperature and rainfall conditions of the weather, and send emails to associated accounts for reminders in specific fall events (currently only for some fall situations).

[0054] The hardware block diagram of the fall detection floor is as follows Figure 1 As shown, it includes: a power supply module, a sensor input module, a microcontroller module, a heating module, a network transmission module and an Internet of Things platform; the heating module includes a thermal pad 3, a heating port 2 and a semiconductor cooling plate; the thermal pad 3 is arranged on the surface of the floor, the heating port 2 is arranged in the floor cavity below the thermal pad 3, and the semiconductor cooling plate is placed in the heating port 2; the heating module uses the semiconductor cooling plate to heat and dry the floor, because of the shackles of its own hardware (constant power), it can avoid harmful events caused by excessive heating during the heating process. The network transmission module is bidirectionally connected to the microcontroller module and the Internet of Things platform;

[0055] The power supply module includes an LM317 linear adjustable power supply and an external switching power supply; the external switching power supply supplies power to the heating module, and the linear adjustable power supply supplies power to the remaining modules;

[0056] The sensor input module includes a raindrop sensor, a temperature sensor and a gravity sensor; the raindrop sensor, the temperature sensor and the gravity sensor are all arranged on the surface layer of the floor; the temperature sensor is mounted on multiple controllers of the microcontroller module;

[0057] The main controller of the microcontroller module is an STM32F103C8T6 single-chip microcomputer, and is manufactured using ESP8266, ds18b20, HX711, and H-bridge. The basic power supply circuit of the microcontroller module is powered by an external switching power supply, and the secondary single-chip microcomputer of the microcontroller module is powered by an LM317 linear adjustable power supply packaged as TO252; the input of the STM32F103C8T6 single-chip microcomputer is gravity data collected by a gravity sensor, temperature data collected by a temperature sensor, and rainfall data collected by a raindrop sensor.

[0058] Network transmission module: Use ESP8266 and its built-in AT firmware to implement the MQTT function of connecting to the Internet of Things.

[0059] Internet of Things Platform: Select the OneNet platform and use the MQTT protocol to connect. Then use its own product application functions to set up the interface, so that data can be observed more intuitively and exported.

[0060] STM32F103C8T6 minimum system diagram Figure 5 As shown, the principle is to collect the surface data of the floor through the sensors (temperature, pressure, etc.) on the surface of the floor and transmit it to the main controller, and then rely on the main controller (STM32F103C8T6) to analyze the change law of the collected data, adjust the scanning cycle, and set the proportional coefficient to adjust the duty cycle of PWM to control the MOS tube drive circuit to control the temperature of the semiconductor refrigeration plate on the surface of the floor.

[0061] The basic power supply circuit of the control unit power supply circuit can provide 12V DC power supply through the switching circuit. The 3.3V of the secondary microcontroller power supply circuit is modulated by two resistors using the linear adjustable chip LM317 packaged as TO252. The calculation formula is Vo=1.25(1+R2 / R1). Therefore, according to the formula, R1 and R2 select resistors 3k and 5k packaged as 0805 to obtain a voltage of 3.33V to power the STM32F103C8T6 with a maximum voltage of 3.7V. According to the LM317 data sheet, the LM317 can provide a maximum current support of 1.5A (some different models can provide a current close to 3A), which is sufficient according to the maximum current of 100MA of the control circuit part of the STM32F103C8T6 and the maximum normal working current of 200MA of the esp8266. The power module schematic diagram is as follows Figure 6 shown.

[0062] Network module circuit wiring diagram Figure 7As shown, the network communication module uses ESP8266, which is a low-power 32-bit microcontroller (MCU). The main frequency supports 80MHZ and 160MHZ. ESP8266 follows the standard IEEE802.11 b / g / n protocol, and can fully use the TCP / IP protocol stack for network data interaction, supports USART for communication, and supports AT commands to operate its network functions. In this design, its pin physical interface is PA9 and PA10, and the interface function is a serial port (usart1).

[0063] MOSFET drive circuit such as Figure 8 As shown, this time MOSFET (commonly known as MOS tube) is used to control the semiconductor cooling film, because the conduction of the MOS tube requires a voltage of about 10 to 20 volts between the G pole (gate) and the S stage (source) to cause the MOS tube to be fully turned on. According to this circuit characteristic of the MOS tube, this time IR2101 is used as the pre-stage driver of the MOS tube, and a BOOST boost circuit is formed through the diode and capacitor in the front half to fully turn on the MOS tube. What's more, IR2101 itself is a half-bridge driver, and two IR2101s and MOS tubes can form an H-bridge drive circuit to heat and cool the semiconductor cooling film. In this design, the pin physical interface is PA0, PB9, PA1, and PB8.

[0064] The ds18b20 digital temperature sensor is used, with an accuracy of ±0.5 degrees Celsius, a limit detection temperature range of -55℃~125℃, and a response time of 750ms. The single bus protocol (1-wire) can be used to mount multiple controllers. In this design, its pin physical interface is at PA11. The ds18b20 circuit diagram is shown below: Fig. 9 shown.

[0065] HX711 (a 24-bit high-precision electronic scale A / D conversion module) is used, with an output data rate of 10HZ and 80HZ, low power consumption (power consumption 1.6MA), and the extreme detection gravity range changes according to the change of the properties of the strain gauge material. This time, 4 gravity sensors with a material weight resistance of 20KG are selected. In this design, the pin physical interface is PA7, PA6, PB1, PB0, PB10, PB11, PB13, and PB14. The HX711 module circuit schematic and circuit wiring diagram are as follows Fig.10 , Fig.11 shown.

[0066] The raindrop sensor is a module that is compatible with analog and digital outputs. It is also known as a rain sensor or a rainfall sensor. In modern life, it can detect weather conditions in certain areas to determine whether it is raining or how heavy the rain is. The threshold of the rain sensor switch can be controlled by adjusting the rear adjustable resistor, or the analog quantity can be directly collected to determine the amount of rain. It is a very simple and convenient test module. In this design, its pin physical interface is at PA5. The circuit schematic diagram and circuit wiring diagram of the raindrop sensor module are as follows: Fig.12 , 13 shown.

[0067] MQTT connects to the IoT platform: MQTT is a lightweight network communication protocol with a wide range of applications. It is used in most unreliable environments and is very common in IoT applications. It connects to the MQTT IoT platform through the network assistant.

[0068] Actual effect of fall detection floor:

[0069] The temperature and gravity parameters transmitted from the floor are displayed on the web page through the network tools provided by the Internet of Things platform. According to F=mv / t (F is force, m is the mass of the object, v is the speed, and v speed is 1s), the impact force of the falling object is obtained and an approximate value is taken to determine whether the normal gravity is restored after 1 second. If it is restored, it is judged as a fall event alarm, otherwise no alarm is given; the anti-slip effect is as follows: Fig.14 shown.

[0070] On this basis, the strain resistor 1 is installed at the mechanical layer below the thermal pad 3, which can measure the force on the cross-sectional area, and then the accuracy of detecting falls based on the sudden change of gravity can be more accurately measured. The influence of jumping and movement can be eliminated, and the approximate force area can be judged according to the position of the reaction data of the strain resistor 1 (the principle of the resistance screen can improve the accuracy according to the number), and small area touches can be eliminated. The Internet of Things technology is used to upload the touch area to the server, so that each gravity sensing position formed generates a coordinate location, and python3 is used to convert the coordinate data into a binary image. Opencv (open source computer vision library) and imutils (image processing software) are used to determine whether it is a human body contour map. After judging it as a human body contour map, the sudden change value taken by the gravity sensor is added to determine that a fall event has occurred, and an alarm message is sent (the camera software can be used to improve the screening accuracy). A second microprocessor controller is required to collect the analog signal of the strain gauge, and then use the IIC serial protocol to establish a connection with the main control microcontroller. The IIC serial analog signal pins are PB6 and PB7. Strain resistor 1 is installed as follows Figure 3 shown.

[0071] Email alarm is sent by selecting the trigger of OneNet. According to the result of email, the autocad drawing is drawn and the cad model is drawn. The floor model is as follows Figure 4 shown.

[0072] The actual schematic and circuit diagram are as follows Fig.15 After the initial idea is formulated, the product hardware and software are produced and debugged. After the debugging is completed, it will be assembled into a model, and a large public place will be sought for consultation. The product will be placed in it at a specific time, the site will be surveyed, and field experiments and debugging will be carried out.

[0073] This new type of fall detection floor is composed of a network module, an Internet of Things platform, a semiconductor cooling module, a MOS tube drive circuit module, a sensor detection module, and a microcontroller module. The installation method is suspended laying, which is easy to install and maintain. The final Internet of Things platform is also very suitable for users to collect their own data and facilitate the adjustment of the temperature of the floor. In software adaptation.

[0074] After the hardware is made, a small model is made. We seek to negotiate with large public places with high traffic, put this product in at a specific time, and conduct on-site inspections. The designed floor will have pedestrian detection, heating and drying, raindrop detection, etc., and add over-temperature protection, which further improves the safety of the tool.

Claims

1. A method for detecting a fall on a floor, characterized in that: include: A power supply module, a sensor input module, a microcontroller module, a heating module, a network transmission module and an Internet of Things platform; the heating module comprises a thermally conductive pad (3), a heating port (2) and a semiconductor cooling plate; the thermally conductive pad (3) is arranged on the surface layer of the floor, the heating port (2) is arranged in a floor cavity below the thermally conductive pad (3), and the semiconductor cooling plate is placed in the heating port (2); The microcontroller module is connected to the Internet of Things platform via a network transmission module; The power supply module includes a linear adjustable power supply and an external switching power supply; the external switching power supply supplies power to the heating module, and the linear adjustable power supply supplies power to the remaining modules; The sensor input module includes a raindrop sensor, a temperature sensor and a gravity sensor; the raindrop sensor, the temperature sensor and the gravity sensor are all arranged on the surface layer of the floor; The main controller of the microcontroller module is a single chip microcomputer; the input of the single chip microcomputer is gravity data collected by the gravity sensor, temperature data collected by the temperature sensor and rainfall data collected by the raindrop sensor; specifically, the following steps are included: S1, the microcontroller module's single chip microcomputer starts working and initializes the peripherals; S2, the single chip microcomputer obtains the gravity sensor data, the temperature sensor data and the raindrop sensor data; S3, the MCU sends a command to the network transmission module, and the network transmission module receives the command and sends an MQTT connection request to the IoT platform; if the MQTT connection request is successful, the MCU uploads the JSON data to the IoT platform through the network transmission module; if the MQTT connection request is not successful, the network transmission module sends the MQTT connection request to the IoT platform again until it is successful; S4. If the gravity sensor detects that a pedestrian is passing by and the raindrop sensor detects rainfall data, the heating module starts to heat the floor; S5. If the gravity sensor detects a sudden change in gravity while a pedestrian is passing by, the impact force of the fall is calculated according to F=mv / t and an approximate value is taken; If the approximate impact force value is greater than the set threshold, it is determined whether normal gravity is restored after a fixed time; If normal gravity is restored, it is judged as a fall event; F is the force, m is the mass of the object, and v is the velocity; S6. If it is determined that a fall event occurs, an alarm message is sent; otherwise, no alarm message is sent, and the process returns to step S4.

2. A method for detecting a fall on a floor, characterized in that: include: A power supply module, a sensor input module, a microcontroller module, a heating module, a network transmission module and an Internet of Things platform; the heating module comprises a thermally conductive pad (3), a heating port (2) and a semiconductor cooling plate; the thermally conductive pad (3) is arranged on the surface layer of the floor, the heating port (2) is arranged in a floor cavity below the thermally conductive pad (3), and the semiconductor cooling plate is placed in the heating port (2); The microcontroller module is connected to the Internet of Things platform via a network transmission module; The power supply module includes a linear adjustable power supply and an external switching power supply; the external switching power supply supplies power to the heating module, and the linear adjustable power supply supplies power to the remaining modules; The sensor input module includes a raindrop sensor, a temperature sensor and a gravity sensor; the raindrop sensor, the temperature sensor and the gravity sensor are all arranged on the surface layer of the floor; The main controller of the microcontroller module is a single chip microcomputer; the input of the single chip microcomputer is gravity data collected by the gravity sensor, temperature data collected by the temperature sensor and rainfall data collected by the raindrop sensor; A plurality of rows of strain resistors (1) are also installed at the mechanical layer below the thermally conductive pad (3); a microprocessor controller is provided to collect analog signals of the strain resistors (1); the microprocessor controller is connected to a main controller of the microcontroller module via an IIC serial connection; the specific steps include: S1, the microcontroller module's single chip microcomputer starts working and initializes the peripherals; S2, the single chip microcomputer obtains the gravity sensor data, the temperature sensor data and the raindrop sensor data; S3, the MCU sends a command to the network transmission module, and the network transmission module receives the command and sends an MQTT connection request to the IoT platform; if the MQTT connection request is successful, the MCU uploads the JSON data to the IoT platform through the network transmission module; if the MQTT connection request is not successful, the network transmission module sends the MQTT connection request to the IoT platform again until it is successful; S4. If the gravity sensor detects that a pedestrian is passing by and the raindrop sensor detects rainfall data, the heating module starts to heat the floor; S5. Fall detection: S5.

1. Detecting a sudden change in gravity. If the gravity sensor detects a sudden change in gravity while detecting a pedestrian passing by, the impact force of the fall is obtained according to F=mv / t and an approximate value is taken; F is the force, m is the mass of the object, and v is the velocity; S5.2, if the approximate impact force value is greater than the set threshold, determine whether normal gravity is restored after a fixed time; If normal gravity is restored, it is determined as a fall event and step S5.3 is executed; otherwise, it is not a fall event; S5.3, the microprocessor controller obtains the force area according to the position of the strain resistance response data, and if the obtained force area is greater than the set value, the force area data is uploaded to the Internet of Things platform; S5.

4. The IoT platform generates coordinate locations for the gravity sensing positions of each force-bearing area data; Python3 is used to convert the coordinate data into a binary image; S5.

5. Use opencv and imutils to determine whether the binary image is a human body contour image; S5.6, if the binary image is determined to be a human body contour image in S5.5, then it is determined that a fall event occurs; S6. If it is determined that a fall event occurs, an alarm message is sent; otherwise, no alarm message is sent, and the process returns to step S4.

3. The working method of the fall detection floor according to claim 2, characterized in that: The Internet of Things platform described in step S3 is selected as the OneNet platform; the alarm message described in step S5 is sent by the trigger of OneNet.

4. The working method of the fall detection floor according to claim 2, characterized in that: The linear adjustable power supply outputs a voltage of 3.3V to supply power to the microcontroller module.

5. The working method of the fall detection floor according to claim 2, characterized in that: The single chip microcomputer is STM32F103C8T6; the linear adjustable power supply is LM317; and the temperature sensor is DS18B20.

6. The working method of the fall detection floor according to claim 2, characterized in that: The network transmission module is ESP8266.

7. The working method of the fall detection floor according to claim 2, characterized in that: The gravity sensor is HX711.

Images