

The Smart Lab IoT Automation Project
Transformed IEEE Concordia's workshop into a smart lab with self-hosted IoT network using WiFi, Zigbee, MQTT, and ML-based automation running inference on Google Coral TPU hardware accelerator.
Sep 2024 — Jan 2025
completed
IoTMQTTHome AssistantNode-RedZigbeeMachine LearningCoral TPU
Overview
Led a team of 6 in transforming the IEEE Concordia club's workshop to a modern smart lab through interconnected devices, self-hosted services, and intelligent automation. This parent project encompasses multiple sub-projects, each contributing to a cohesive ecosystem of locally hosted smart devices.
Technical Stack
Network Infrastructure
- Containerization: Docker Compose
- Self-hosted IoT network (no cloud dependency)
- WiFi and Zigbee connectivity for diverse devices
- MQTT message broker for efficient communication
- InfluxDB for time-series data storage and analytics
Custom Hardware
- Built custom WiFi and Zigbee IoT devices
- Custom sensors deployed throughout the lab
- Unified automation through Home Assistant
Software Stack
- Home Assistant: Core home automation platform
- Node-RED: Flow-based automation programming
- InfluxDB: Time-series database for sensor data
- Grafana: Real-time dashboarding and visualization
- Portainer: Container management interface
- Zigbee2MQTT: Custom IoT network coordination
IoT Communication Protocols
- MQTT (Message Queue Telemetry Transport)
- Zigbee
- TUYA
- Ethernet
- Bluetooth Low Energy (BLE)
- WiFi
Automation & Control
- Node-Red for optimized automation flows
- Voice control integration via Alexa
- Automated lab routines for energy efficiency
Technical Highlights
This project demonstrates expertise in:
- Multi-protocol IoT network design
- Docker containerization and orchestration
- Real-time data pipeline architecture (sensor → database → visualization)
- Custom embedded systems development
- Home automation logic programming
- Network security in IoT environments
- System integration across diverse platforms
Security System
- ML object detection on camera feeds
- Inference running on CORAL TPU for edge computing
- Automated control of lights, soldering irons, cabinet locks
- Real-time data-driven decision making
- Network security implementation throughout
Technologies: Home Assistant, Node-RED, Docker, MQTT, Zigbee, ESP32, Python, InfluxDB, Grafana, Linux
Role: Project Manager & Lead Developer
Status: Active Development
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