This project enables disabled individuals to control appliances via gestures using a wall-mounted camera and trained LSTM model. The model predicts gestures, transmitting commands to an Arduino Uno, which controls appliances using a relay . A video dataset of 100 diverse hand gestures was collected to develop the system, showcasing a wide range of movements for appliance control, as detailed in Table 1.1.
AIM AND OBJECTIVES:
This project aims to use hand gestures to control home appliances and devices for elderly and disabled people using computer vision technology. The main objectives of this system are:
- To collect a comprehensive dataset of hand gestures from a variety of individuals.
- Train a deep learning model using the collected dataset to accurately interpret and recognize hand gestures as distinct commands for device control.
- To conduct real-time testing.
- Integrating with Home Appliances
Methodology:
System Design:
The Hardware Design of the project is depicted in the following:
Testing and Results:
