Silently guarding your loved ones
Table of Contents
Introduction to the Project
- Title: Unobstructive Monitoring of Vulnerable Elderly
- Problem Statement: To mitigate physical and mental health risks faced by the elderly through remote monitoring that preserves the privacy of vulnerable elderly individuals
- Project Goal: To develop a non-invasive home-monitoring system for vulnerable elderly that provides unobtrusive fall detection and activity level tracking that preserves individual privacy and can be readily integrated into existing infrastructure
This repository contains the code for testing sensors and data analysis for the activity level monitoring subsystem. For the fall detection subsystem, refer here
Progress
Presence Detection (from Review 1)
Demo
Activity Level Analysis (from Review 2)
Demo
Background Subtraction Pipeline (Review 3)
Demo
Credits to Andrews Sobral for a GoDec Python Implementation and OpenCV for computer vision API. We experimented a lot with the different functions and parameters available before achieving this r
Device Requirements
The Activity Levels Monitoring subsystem (as of Review 4) require the following devices:
- MLX90640
- RPI 3b
- NUC / Central Processor
For instructions on older sensors that we have experimented with, refer here.
Setup instructions for this repo
- For general testing with the MLX90640, refer to MLX_SETUP.md
- For setting up the RPI, refer to RPI_SETUP.md
- For setting up the NUC, refer to NUC_SETUP.md