🔌 AI-powered smart charging station for light electric vehicles (e-bikes & e-scooters) using ESP32 – featuring intelligent energy management, real-time monitoring, and cloud integration.
firmware/: Contains the ESP32 code.ml/: Contains the AI/ML models.dashboard/: Contains the web dashboard code.docs/: Contains project documentation.
The firmware includes placeholders for cloud synchronization (firmware/src/cloud_sync.cpp and firmware/src/cloud_sync.h). This is intended to enable features like:
- Remote monitoring of sensor data.
- Sending AI model predictions to the cloud.
- Remote control of charging (start/stop).
- Over-the-air (OTA) firmware updates (future).
Current Status: The implementation contains only placeholder functions. No actual cloud connection is made.
Intended Cloud Options (to be explored):
- MQTT: A lightweight messaging protocol suitable for IoT devices. This would involve an MQTT broker (e.g., Mosquitto, or a cloud-based service like AWS IoT Core, Google Cloud IoT Core, Azure IoT Hub).
- Google Firebase: Realtime Database or Firestore for data storage and Functions for backend logic.
- Google Sheets API: For simple data logging directly to a Google Sheet (suitable for basic telemetry).
The choice of cloud platform will depend on factors like scalability, cost, ease of integration, and specific features required. The current code includes commented-out sections for WiFi and PubSubClient (MQTT) libraries as a starting point.