1. Project Introduction
1.1 Project Design
This is a fall detection and alert system specifically designed for elderly care scenarios, focusing on the core needs of home safety for the elderly. It enables real-time fall detection and immediate alerts. The system is particularly suitable for frequently active areas where the elderly are prone to slipping, such as kitchens and bathrooms. Upon detecting a fall, it quickly triggers an audible and visual alarm, facilitating prompt emergency response and valuable rescue time, effectively addressing the pain points in elderly care of "difficulty in detection and delayed assistance".
The system uses the Control Board as its core controller, paired with HUSKYLENS 2 for intelligent fall behavior recognition. The entire device is plug-and-play, requiring no complex debugging or training. It can unobtrusively integrate into the daily lives of the elderly, building a reliable safety barrier for their home safety. Additionally, the system can be extended to applications in high-risk industry work monitoring, post-surgery, and critical patient monitoring, providing all-weather safety protection for more people.
1.2 Demo Video
2. Implementation Principle
The core logic is as follows:
HUSKYLENS 2 detects falls in real-time and transmits the detection result to the Control Board. Once the Control Board receives the fall signal, the buzzer will play an alarm sound and the RGB light will turn red.
3. Hardware and Software Preparation
3.1 Equipment List
3.2 Hardware Connection
Make connections by referring to the diagram below.
3.3 Software Preparation
Download and install the Mind+ installation package (Version 2 and above) from the official website. Double-click to open it after installation.
4. Project Making
4.1 HuskyLens 2
First, select the protocol type for HuskyLens 2.
Tap System Settings -> Protocol Type -> Select I2C communication mode, then return to the main menu interface.
Swipe left and right to find the "Falls Detection" function.
When HUSKYLENS 2 detects a falling action, it will frame the target object in the image and display the prompt "Falls:IDx xx%", where the percentage represents the confidence level that the action is identified as a fall.
For more detailed usage of HuskyLens 2, please refer to the following URL:
https://wiki.dfrobot.com/_SKU_SEN0638_Gravity_HUSKYLENS_2_AI_Camera_Vision_Sensor
4.2 Programming
Open the programming software Mind+, choose "Coding" mode, then click "Upload" to create a new project.
Next, add the required extensions in Mind+, including micro:bit and HuskyLens 2.
Enter the "Extensions" page, switch to "Board" tab, search for"micro:bit", and click "micro:bit".
Click again after downloading until "Remove" appears in the top-right corner to confirm successful loading into the program.
Load the "HuskyLens 2 AI Camera" library by the same way from "Module" page.
Click the "Back" button to return to the programming interface.
Click the "Connect Devices", choose your device and "Connect".
After the device is successfully connected, write the program as follows:
The analysis of the core code is as follows:
There is a complete program file for this project in the attachment. (Note: The .mp file is compatible with both Mind+ v1.x (e.g., v1.8.1) and v2.x (e.g., v2.0), while the .mpcode file only works with Mind+ v2.0)
Open Project->Open Local File to load project.
Select the project in the attachment and click "Open".
Click "Upload" to run the program.
The effect is as follows:
5. Attachment
Program-Fall Detection.zip 
