Fundator / activity-sensing

Push sensor data stream from android phone via local server to cloud for monitoring and classification.

Activity detector

Streaming sensor data from Android phone via local proxy to server in cloud, that visualize the data, and make classification requests from another server, exposing a prediction API for a Temporal Convolutional Network.

The following programs must run for the application to work:

On the mobile

Download the app "Sensorstream IMU+GPS" from Google Play. Change the settings to the IP-address of your proxy server. Start stream.

On the proxy server(laptop)

• rcv_udp_realtime.py Receieves the raw sensor data from the phone on UDP port 5555, convert to a more friendly format, and relays to a RabbitMQ channel. Note: This must be on the same LAN as the phone.

On main server

• receive.py Listens on the RabbitMQ channel and write the streaming data to a Redis DB. It also writes a selected window of all the sensors that is used for prediction.
• prep_and_get_predictions.py This reads the most recent data from the Redis DB, prep it a little bit, and send to the Deep Learning API for prediction output.
• bokeh serve sensor_streaming_multiple.py --allow-websocket-origin=40.127.197.251:8080 --port 8080 This starts the bokeh server, and serves requests on port 8080, showing the webpage of the app.

On GPU server

• run_keras_server.py Exposes the prediction API by sending the content of the request to a pretrained TCN and returning the prediction.