CS3237 AY20/21 Team 12 Project Repository

Gesture recognition using LSTM

Team

• Glen Wong Shu Ze
• Lim Hao Xiang, Sean
• Liu Wei Jie Nicholas
• Permas Teo Pek Neng

Instructions

Setting up the environment

1. Create a virtual environment called venv: python -m venv venv
2. Activate the environment: .\venv\Scripts\activate
3. Install all requirements by executing: pip3 install -r install.requirements
4. Exit virtual environment: deactivate

Running React App

1. Add .env file in \frontendV2 and \src\demo directory to access EC2 instance
2. Change directory to frontendV2: cd frontendV2
3. To install: npm install
4. To run: npm start

Setting up of the cc2650 device

1. Please make sure your device is not paired with any device at the moment; this includes closing the SensorTag app on your phone after use.
2. Please make sure you reset your SensorTag device to factory settings using the instructions at TI Sensor Tag User Guide ; This UI option is only available in Windows;

Running the live prediction code

1. Open a command prompt
2. At the root directory, change directory to demo folder: cd src/demo
3. Start MQTT broker (or server): python demo_receive.py
4. Open a new command prompt
5. At the root directory, change directory to demo folder: cd src/demo
6. Start MQTT client: python demo_send.py

Notes

Credits

1. https://github.com/hbldh/bleak/tree/develop/examples
2. https://github.com/IanHarvey/bluepy/blob/a7f5db1a31dba50f77454e036b5ee05c3b7e2d6e/bluepy/sensortag.py
3. TI SensorTag User Guide # GATT Server
4. Skeletal Code Reference for MQTT React App: (https://www.preciouschicken.com/blog/posts/a-taste-of-mqtt-in-react/).
5. This project was bootstrapped with Create React App.