Multi-Sensor Integration
Combines mmWave radar, Doppler motion detection, environmental sensors, and sound monitoring for comprehensive room activity analysis.
Room Activity Scanner
Room Activity Scanner is an embedded IoT solution designed for health and wellness monitoring through intelligent room activity detection and comprehensive environmental sensing. Built on the ESP32-S3 microcontroller platform, this system provides real-time monitoring of human presence, motion, air quality, and environmental conditions with a focus on low-cost implementation and power efficiency.
Key Features
Real-Time Data Streaming
MQTT-based communication enables instant data transmission to cloud platforms and automation systems for live monitoring and alerts.
Room Automation Control
Integrated relay control system enables automated response to room conditions, controlling lights, fans, and other appliances.
Low-Power Design
Optimized firmware architecture and power management ensure efficient operation suitable for continuous monitoring applications.
System Overview
The Room Activity Scanner implements a modular, layered architecture for sensor data acquisition, processing, and communication:
[Sensor Layer] → [Data Acquisition] → [Processing] → [MQTT Communication] → [Cloud/Dashboard]Core Components
| Component | Description | Role |
|---|---|---|
| YD-ESP32-S3 | Dual-core Xtensa LX7 @ 240MHz, 512KB SRAM, 16MB Flash | Main processing unit, sensor interface, WiFi/MQTT communication |
| HLK-LD2420 | 24GHz mmWave radar sensor | Presence detection via UART interface |
| RCWL-0516 | Doppler radar module | Motion detection via GPIO |
| BMP280 | Environmental sensor | Temperature and pressure via I2C |
| MQ-2 | Gas sensor | Air quality monitoring via ADC |
| INMP441 | MEMS microphone | Sound level monitoring via I2S |
| Relay Module | Electromechanical relay | Device control via GPIO |
Use Cases & Applications
Health and Wellness Monitoring
Elderly Care & Safety
Non-intrusive monitoring for seniors living independently. Detects presence, tracks activity patterns, and generates alerts for unusual behavior without compromising privacy.
Sleep Quality Analysis
Monitors motion, sound levels, and environmental conditions to assess sleep quality and identify disturbances for health optimization.
Healthcare Facilities
Patient room monitoring for presence detection, environmental compliance, and staff efficiency without intrusive surveillance.
Smart Building Automation
- Energy Optimization: Automatic control of HVAC and lighting based on occupancy, reducing energy waste
- Comfort Management: Maintains optimal temperature and air quality by triggering ventilation and climate control
- Security Enhancement: Intelligent intrusion detection integrated with automated lighting and alert systems
- Accessibility: Voice-free automation for individuals with mobility or communication challenges
Getting Started
Activity Monitor Firmware
Get started with the current implementation featuring HLK-LD2420 radar sensor integration, relay control, and MQTT communication.
Development Status
The project is under active development with core functionality implemented and ready for testing:
- ✅ HLK-LD2420 Radar Integration: Presence detection operational
- ✅ Relay Control: Manual and automated device control
- ✅ ADC Reading: Gas sensor data acquisition
- 🛠 MQTT Publishing: Basic functionality working, refinement in progress
- 🛠 Sensor Calibration: Baseline establishment and drift compensation
Future Enhancements
Complete Sensor Suite Integration
- BMP280 environmental sensor (I2C)
- INMP441 sound monitoring (I2S)
- Advanced calibration algorithms
Enhanced Connectivity
- Robust MQTT with QoS levels
- Secure TLS/SSL communication
- Automatic reconnection and message queuing
Web Dashboard & Analytics
- React + FastAPI + MongoDB stack
- Real-time visualization
- Historical data analysis
- Multi-device management
Technical Foundation
Development Environment
- Framework: ESP-IDF (Espressif IoT Development Framework)
- Language: C programming
- Platform: Ubuntu Linux
- Target: ESP32-S3 (16MB Flash)
- Communication: MQTT protocol
- Connectivity: WiFi 802.11 b/g/n
Data Format
Sensor data is published in JSON format via MQTT for easy integration:
{ "device_id": "room-scanner-001", "timestamp": "2025-04-10T13:45:00Z", "presence": true, "motion": true, "temperature": 24.3, "pressure": 1012.8, "air_quality": 350, "sound_level": 47}Open Source
This project is open-source under the MIT License, encouraging experimentation, customization, and community contributions.
- Repository: github.com/SiliconWit/room-activity-scan
- Issues: Report bugs and request features on GitHub
- Contributions: Pull requests welcome!