CN220212910U - Human body fall detection device based on infrared array - Google Patents

Abstract

The utility model discloses a human body fall detection device based on an infrared array in the field of electronic information communication, which includes an infrared array sensor. The infrared array sensor is connected to a single-chip computer. The single-chip computer is connected to an Internet of Things module and a GSM module respectively. The infrared array sensor and the single-chip computer , the Internet of Things module and the GSM module are all connected to the power supply module; the microcontroller is used to collect the human body temperature data detected by the infrared array sensor and classify it to identify and judge the falling behavior. If a fall is recognized, the device connects to the IoT platform through the IoT module and can receive alarm information on the mobile APP. At the same time, it can also send alarm text messages to designated mobile phones via the GSM module to achieve dual alarm reminders.

Description

A human fall detection device based on infrared array

Technical field

The utility model relates to a human body fall detection device in the field of electronic information communication.

Background technique

Falls are a serious threat to the health of the elderly. Accurate detection of accidental falls in the elderly and timely rescue can minimize the risk of death and injury. In recent years, various technologies combined with machine learning and deep learning algorithms have been widely used in the field of fall detection. Currently, common fall detection systems or devices are roughly divided into three categories: wearable device-based, environmental sensor-based, and video sensor-based fall detection equipment. However, for current fall detection solutions, the wearing behavior of fall monitoring equipment is a bit cumbersome, and some people do not have the habit of wearing watches, jewelry, etc. Due to the demand for smaller size of wearable hardware, the battery life problem cannot be effectively improved. Especially when faced with usage scenarios by the elderly, the relatively poor memory of the elderly is also a major problem, and they will forget to charge and wear the device. Only wearing it enables it to perform its monitoring and alarm functions. Therefore, the user's memory and living habits problems will become a huge hidden danger for the system to be unable to perform its functions. The fall detection of visual recognition technology must include a camera as a component, which causes users to worry about privacy leaks. Due to the characteristics of the Internet of Things, the entire system has a high risk of privacy leaks, and the performance of the video processing and recognition system is affected. The requirements also make the price of this type of equipment relatively high.

Utility model content

The purpose of this utility model is to provide a human body fall detection device based on an infrared array to achieve a safe, low-cost, and threshold-free fall detection function.

In order to achieve the above purpose, the utility model provides a human body fall detection device based on an infrared array, including an infrared array sensor. The infrared array sensor is connected to a single-chip computer. The single-chip computer is connected to the Internet of Things module and the GSM module respectively. The infrared array sensor, single-chip computer, Both the IoT module and the GSM module are connected to the power supply module.

Compared with the existing technology, the beneficial effect of the present invention is that the single-chip microcomputer is used to collect the human body temperature data detected by the infrared array sensor and classify it to identify and judge the falling behavior. If a fall is recognized, the device connects to the IoT platform through the IoT module and can receive alarm information on the mobile APP. At the same time, it can also send alarm text messages to designated mobile phones via the GSM module to achieve dual alarm reminders.

As a further improvement of the present utility model, the microcontroller includes chip STM32, the infrared array sensor includes chip AMG8833, pin 2 of chip STM32 is connected to pin 93 of chip STM32, pin 3 of chip STM32 is connected to pin 92 of chip STM32, Pin 6 of the chip STM32 is connected to ground. Pins 13 and 9 of the chip STM32 are connected to the power supply module. Pin 10 of the chip STM32 is connected to pin 12 of the chip STM32 through resistor R4, capacitors C9 and C10. One end of capacitor C9 is connected to the ground. One end of capacitor C7 is connected to ground, and the other end of capacitor C7 is connected to pin 9 of chip STM32. Capacitor C7 is connected in parallel with capacitor C8.

In this way, the chip AMG8833 collects data three times per second. Each time the data format is an 8*8 temperature data array. AMG8833 transmits the data to the microcontroller chip STM32 in real time through the IIC interface. The chip STM32 performs calculations, feature extraction and data classification judgment on the data. .

As a further improvement of the present utility model, the Internet of Things module includes a chip ESP8266. Pins 1, 3, 4, 29 and 30 of the chip ESP8266 are connected to the power supply module. Pin 2 of the chip ESP8266 is connected to the antenna. Connected, the No. 7 pin of the chip ESP8266 is connected to the No. 11, No. 28, No. 50, No. 75 and No. 100 pins of the chip STM32 via the resistor R6. The No. 26 pin of the chip ESP8266 is connected to the No. 25 pin of the chip STM32. , pin 25 of the chip ESP8266 is connected to pin 26 of the chip STM32.

In this way, the STM32 microcontroller determines the fall behavior and sends alarm information to ESP8266 through serial port 1. ESP8266 uses the MQTT protocol to connect to the external network through the home network and router to transmit data to the Alibaba Cloud server. The alarm information can be received on the mobile APP. The process is accurate and fast, and can be timely Alert the caregiver to a fall by the caregiver.

As a further improvement of the present utility model, the GSM module includes a chip SIM900A. The J1.1 pin of the chip SIM900A is connected to the power supply module. The J1.2 pin of the chip SIM900A is connected to the J1.7 pin of the chip SIM900A and grounded. The chip SIM900A Pin J1.5 of the chip is connected to pin No. 68 of the chip STM32, and pin J1.6 of the chip SIM900A is connected to pin No. 69 of the chip STM32.

In this way, the STM32 microcontroller determines the fall behavior and sends alarm information to the SIM900A module through serial port 2. After receiving the alarm information, SIM900A sends an alarm text message to the mobile phone number set in the program. This can provide double insurance and remind caregivers in multiple ways.

As a further improvement of the present utility model, the power supply module includes a voltage stabilizing chip 1117A. Pins 1 and 3 of the voltage stabilizing chip 1117A are connected to pin 3 of the isolation switching power supply U8. Pin 4 of the isolation switching power supply U8 is grounded. Pins 1 and 2 of the switching power supply U8 are connected to pins 1 and 2 of the socket J1 respectively. Pin 1 of the voltage stabilizing chip 1117A is also connected to pin J1.1 of the chip SIM900A. The pins of the voltage stabilizing chip 1117A Capacitor C4 is connected between pins 1 and 4. Capacitor C4 is connected in parallel with capacitor C3. Capacitor C3 is connected in parallel with the light-emitting diodes and resistor R1 connected in series. Pin 4 of the voltage stabilizing chip 1117A is connected to pin 4 of the chip AMG8833 respectively. pins, pins 5, 13 and 9 are connected. Pin 4 of the voltage stabilizing chip 1117A is also connected to the parallel capacitor C11, capacitor/12 capacitor C13 and capacitor C14. Pin 4 of the voltage stabilizing chip 1117A is connected to Pins 1, 3, 4, 29 and 30 of the chip ESP8266 are connected.

Socket J1 is connected to the 220V AC power supply. The 220V AC power is converted into +5v power supply through the isolation switch power supply U8, and then the voltage stabilizing chip 1117A is used to provide a stable 3.3V voltage for each chip to ensure the normal use of the equipment.

Description of the drawings

Figure 1 is a schematic diagram of the basic composition of the present utility model.

Figure 2 is a schematic diagram of the overall equipment connection of the present utility model.

Figure 3 is a flow decision chart of the fall detection algorithm of the present invention.

Figure 4 is a circuit hardware connection diagram of the present utility model.

Figure 5 is an array pixel diagram of the care recipient of the present invention when standing normally.

Figure 6 is an array pixel diagram of the caregiver when the caregiver falls down according to the present invention.

Implementation

The utility model will be further described below in conjunction with the accompanying drawings:

As shown in Figure 1-4, a human fall detection device based on an infrared array includes an infrared array sensor. The infrared array sensor is connected to a single-chip computer. The single-chip computer is connected to the Internet of Things module and the GSM module respectively. The infrared array sensor, single-chip computer, and Internet of Things Both the module and the GSM module are connected to the power supply module.

The microcontroller includes chip STM32, and the infrared array sensor includes chip AMG8833. Pin 2 of chip STM32 is connected to pin 93 of chip STM32. Pin 3 of chip STM32 is connected to pin 92 of chip STM32. Pin 6 of chip STM32 is connected to ground. Pins 13 and 9 of chip STM32 are connected to the power supply module. Pin 10 of chip STM32 is connected to pin 12 of chip STM32 through resistor R4, capacitors C9 and C10. One end of capacitor C9 is connected to one end of capacitor C7 and grounded. The other end of C7 is connected to pin 9 of the chip STM32, and capacitor C7 is connected in parallel with capacitor C8.

The Internet of Things module includes the chip ESP8266. Pins 1, 3, 4, 29 and 30 of the chip ESP8266 are connected to the power supply module. Pin 2 of the chip ESP8266 is connected to the antenna. Pin 7 of the chip ESP8266 The resistor R6 is connected to pins 11, 28, 50, 75 and 100 of the chip STM32. Pin 26 of the chip ESP8266 is connected to pin 25 of the chip STM32. Pin 25 of the chip ESP8266 is connected to Pin 26 of the chip STM32 is connected.

The GSM module includes the chip SIM900A. The J1.1 pin of the chip SIM900A is connected to the power supply module. The J1.2 pin of the chip SIM900A is connected to the J1.7 pin of the chip SIM900A and grounded. The J1.5 pin of the chip SIM900A is connected to the chip. Pin 68 of the STM32 is connected, and pin J1.6 of the chip SIM900A is connected to pin 69 of the STM32 chip.

The power supply module includes a voltage stabilizing chip 1117A. Pins 1 and 3 of the voltage stabilizing chip 1117A are connected to pin 3 of the isolating switching power supply U8. Pin 4 of the isolating switching power supply U8 is grounded. Pins 1 and 3 of the isolating switching power supply U8 are connected to the ground. Pin 2 is connected to pins 1 and 2 of the socket J1 respectively. Pin 1 of the voltage stabilizing chip 1117A is also connected to pin J1.1 of the chip SIM900A. Pins 1 and 4 of the voltage stabilizing chip 1117A are also connected. There is a capacitor C4 connected in between, and the capacitor C4 is connected in parallel with the capacitor C3. The capacitor C3 is connected in parallel with the light-emitting diodes and the resistor R1 connected in series. Pin 4 of the voltage stabilizing chip 1117A is connected to pins 4, 5, and 13 of the chip AMG8833 respectively. pin is connected to pin 9. Pin 4 of the voltage stabilizing chip 1117A is also connected to the parallel capacitor C11, capacitor/12 capacitor C13 and capacitor C14. Pin 4 of the voltage stabilizing chip 1117A is connected to pins 1 and 3 of the chip ESP8266. Pin No. 4, Pin No. 29 and Pin No. 30 are connected.

In this utility model, the chip AMG8833 and the chip STM32 are connected through the IIC interface, the chip ESP8266 and the chip STM32 are connected through the GPIO, the chip SIM900A and the chip STM32 are connected through the serial port, and the sensing data of the chip AMG8833 is transmitted to the STM32 through the IIC interface for data processing. Process and identify, and send the alarm signal to the ESP8266 and SIM900A chips for alarm and notification.

The entire device is arranged in the middle of the top of the room, with a height of about 3-3.5 meters from the ground. There is no large obstruction between the object and the detected object. The AMG8833 array sensor in the device will detect three times per second. When someone falls in the room, the AMG8833 array sensor will display a rectangular light-colored array, which is similar to the light-colored array when standing. The ratio is longer, as shown in Figures 5 and 6. Therefore, the device recognizes the fall behavior and sends an alarm to the APP on the bound mobile phone. It also sends an alarm text message to the set phone number to achieve indoor fall detection and alarm. Function, each independent room can install one set and operate independently of each other. No matter the person being cared for is in an independent space, it can be sensed and detected at all times.

As shown in Figure 4, CN1 and P1 are connected to ESP8266 and STM32 respectively, and the host computer programs them to realize the device's fall detection and data upload functions to the server.

The following is a detailed description of the specific working process of the present utility model.

1. Implementation method of device detecting falling behavior

(1) AMG8833 collects data three times per second, and each data format is an 8*8 temperature data array.

(2) AMG8833 transmits data to STM32 in real time through the IIC interface.

(3) STM32 performs calculations, feature extraction and data classification judgment on data.

(4) The judgment and process of data calculation, feature extraction and data classification are as follows:

i. STM32 obtains the array data of each frame and performs the maximum variance operation on pixels.

ii. If the maximum variance value is greater than the threshold, start extracting data features, which are the number of mutation frames Fs, the maximum variance in the range Vfm, and the maximum threshold number of pixels Nm.

The number of mutation frames is defined as the number of frames in which human body movements change significantly in a short period of time. The maximum variance of the range is defined as the value of the maximum variance pixel point within the frame interval of human activity. The maximum threshold number of pixels, Nm, is defined from the moment when the variance changes significantly to the current frame. Among all data frames in the frame, compare the number of pixels with larger variance among the 8*8 pixels in each frame.

iii. Perform KNN classification on the extracted feature data to determine whether a fall occurs. If there is no fall, return to step i. If a fall occurs, alarm information is sent to ESP8266 and SIM900A.

iiii. If the array data received by the sensor does not change or the change value is too small within a period of time after sending the alarm, it will be judged that the person who fell is still in a fall state, and the alarm information will be sent to ESP8266 and SIM900A again.

2. Implementation method for the device to recognize the fall behavior and send text messages to the server and the mobile phone of the person being reminded.

(1) After STM32 determines the falling behavior, it sends alarm information to ESP8266 through serial port 1, and sends alarm information to SIM900A through serial port 2. Among them, ESP8266 uses the MQTT protocol to connect to the external network through the home network and router to transmit data to the Alibaba Cloud server.

(2) After receiving the alarm information, SIM900A sends an alarm text message to the mobile phone number set in the program.

(3) After receiving the fall alarm, the Alibaba Cloud server sends an alarm and notification to the mobile visualization development program (WeChat applet, mobile APP or web visualization toolbox) generated by its platform.

The utility model is based on an infrared sensor among environmental sensors, and uses a microcontroller to collect sensor array data and classify it to identify and judge falling behavior. If a fall is recognized, the device connects to the Internet of Things platform with the ESP8266 chip, which can receive alarm information on the mobile APP. At the same time, it can also send alarm text messages to designated mobile phones through the GSM module to achieve dual alarm reminders.

It is simple to use. You only need to power the device and place it in a suitable location to detect falls around the clock. There is no need to wear or charge the device. It has strong privacy protection, and the sensor resolution and its characteristics can be used as little as possible while achieving normal functions. Obtain the user's private information and avoid the possibility of privacy leakage from the source; the function is implemented with high accuracy, and multiple verifications are used in the analysis of falling behavior, including human body detection, action classification, timing verification, and long-term residence after falling Secondary alarm, thereby achieving high-accuracy identification and detection and avoiding misjudgments and false alarms.

The present utility model is not limited to the above-mentioned embodiments. On the basis of the technical solutions disclosed in the present disclosure, those skilled in the art can make some substitutions and modifications to some of the technical features without creative work based on the disclosed technical content. , these substitutions and deformations are within the protection scope of the present utility model.

Claims (4)

1. Human body fall detection device based on infrared array, its characterized in that: the system comprises an infrared array sensor, wherein the infrared array sensor is connected with a singlechip, the singlechip is respectively connected with an Internet of things module and a GSM module, and the infrared array sensor, the singlechip, the Internet of things module and the GSM module are all connected with a power supply module;

the singlechip includes chip STM32, infrared array sensor includes chip AMG8833, the No. 2 foot of chip STM32 links to each other with the 93 foot of chip STM32, the No. 3 foot of chip STM32 links to each other with the 92 foot of chip STM32, the 6 foot ground connection of chip STM32, the 13 foot and the 9 foot of chip STM32 link to each other with power module, the 10 foot of chip STM32 links to each other with the 12 foot of chip STM32 through resistance R4, electric capacity C9 and C10, electric capacity C9 one end links to each other with electric capacity C7 one end ground connection, the electric capacity C7 other end links to each other with the 9 foot of chip STM32, electric capacity C7 connects in parallel has electric capacity C8.

2. A personal fall detection device based on an infrared array as claimed in claim 1, wherein: the internet of things module includes chip ESP8266, and No. 1 foot, no. 3 foot, no. 4 foot, no. 29 foot and No. 30 foot of chip ESP8266 link to each other with power module, and No. 2 foot and the antenna of chip ESP8266 link to each other, and No. 7 foot of chip ESP8266 links to each other with 11 feet, no. 28 feet, no. 50 feet, no. 75 feet and No. 100 feet of chip STM32 through resistance R6, and No. 26 feet of chip ESP8266 link to each other with No. 25 feet of chip STM32, and No. 25 feet of chip ESP8266 link to each other with No. 26 feet of chip STM32.

3. A personal fall detection device based on an infrared array as claimed in claim 2, wherein: the GSM module comprises a chip SIM900A, wherein a J1.1 pin of the chip SIM900A is connected with the power supply module, a J1.2 pin of the chip SIM900A is connected with a J1.7 pin of the chip SIM900A and grounded, a J1.5 pin of the chip SIM900A is connected with a 68 pin of the chip STM32, and a J1.6 pin of the chip SIM900A is connected with a 69 pin of the chip STM32.

4. A personal fall detection device based on an infrared array as claimed in claim 3, wherein: the power supply module comprises a voltage stabilizing chip 1117A, a pin 1 and a pin 3 of the voltage stabilizing chip 1117A are connected with a pin 3 of an isolating switch power supply U8, a pin 4 of the isolating switch power supply U8 is grounded, a pin 1 and a pin 2 of the isolating switch power supply U8 are respectively connected with a pin 1 and a pin 2 of a socket J1, a pin 1 of the voltage stabilizing chip 1117A is also connected with a pin J1.1 of a chip SIM900A, a capacitor C4 is connected between the pin 1 and the pin 4 of the voltage stabilizing chip 1117A, a capacitor C3 is connected in parallel with the capacitor C4, the capacitor C3 is connected with a light emitting diode and a resistor R1 which are mutually connected in series, the pin 4 of the voltage stabilizing chip 1117A is respectively connected with a pin 4, a pin 5, a pin 13 and a pin 9 of a chip AMG8833, the pin 4 of the voltage stabilizing chip 1117A is also connected with a capacitor C11, a capacitor C13 and a capacitor C14 which are mutually connected in parallel, and the pin 4 of the voltage stabilizing chip 1117A is connected with a capacitor C3, a pin 1, a pin 3 and a pin 30.