CANary

Creating telemetry system to view CAN data remotely.

CANary is a real-time telemetry pipeline for remotely monitoring Controller Area Network (CAN) data. It ingests CAN frames from a Battery Management System (BMS), transmits them over RF, and visualizes the data live via a Streamlit dashboard.

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Architecture Overview

The system is composed of embedded and host-side components that form a continuous data pipeline:

1. CAN Ingestion (Embedded)
   CAN frames are read from the BMS using the mcp2515 controller.

2. RF Transmission (Embedded)
   Each CAN frame is parsed into:

   • Message ID
   • Data payload: These are transmitted wirelessly using the RH_RF95 (LoRa) library.

3. RF Reception (Embedded)
   The receiver reconstructs the CAN frame from the RF packet and forwards it over serial to the host system.

4. Data Logging (Host)
   Incoming data is parsed and written to a .csv file in real time for persistence and analysis.

5. Visualization (Host)
   A Streamlit dashboard reads the live dataset and updates visualizations dynamically.

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Installation

# 1. Clone the repository
git clone https://github.com/UOP-Solarcar/CANary.git
cd CANary

# 2. Install Python dependencies
pip install -r requirements.txt

# 3. Compile and upload program to connected transmitter
cd transmitter
pio run -t upload
cd ..

# 4. Compile and upload receiver program to connected receiver
cd receiver
pio run -t upload receiver\main.cpp
cd ..

# 5. Run the Serial Receiver
cd application
python serialRcv.py

# 6. Run the Streamlit dashboard
streamlit run dashboard.py