Human Fall Detection in a Video Clip, with Email Alert to User

Fall detection using CLIP for context prediction

This project aims to develop AIoT-based fall detection system for elderly care, ensuring quick and accurate detection of the elderly falls

Simulates an embedded fall detection system, and its communication with a server

Preprocessing my fall detection dataset using data standardisation and sliding windows, and splitting this data into train/validation/test sets. Modelling performed on PyTorch using LSTM and CNN networks. The final models were exported to `.tflite` files to be run on a mobile phone. The best performing model was the ResNet152 with 92.8% AUC.

A classic implementation of Federated Learning for identifying FALL and ADL from images with Transfer Learning.

A repository to contain explorations in embedded systems programming

Final Year Dissertation Write-Up

A Hands-on Tutorial on Deep Learning for Object and Pattern Recognition

YOLO-powered Smart Human Motion Analysis is a cutting-edge project leveraging YOLO (You Only Look Once) for real-time object detection. This repository provides a robust solution for accurately tracking and analyzing human motions, offering a versatile tool for applications in sports, healthcare, and surveillance.

An app that aims to bridge the gap between the elderly and their family members.

NOT WORKING

A public surveillance camera system capable of privacy encryption and protection 可加密及保護隱私之公共監視器

Home Surveillance System in MATLAB with two functionalities : Fall Detection (https://github.com/harishrithish7/Fall-Detection) & Change Detection ; which can send E-mail alerts.

An iOS fall detection data collection system. It uses CoreMotion for retrieving accelerometer, magnetometer, and gyroscope sensors, and interfaces with a PolarH10 chest strap for ECG data using the Polar SDK.

Real-time health monitoring and GPS tracking of Mountain climber including fall detection feature. IOT, Arduino IDE, C++,Sensor Intigration.

Fall detection research for Android app BeSafeBox

Autoencoder for gait recognition and elderly monitoring.

This repository contains the code submitted for Software Engineering module (BS2203). The programs demonstrate the use of the MQTT protocol to provide a fall detection system for the elderly.