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The idea is to develop a smart home security system that uses IoT devices and Edge AI to monitor and secure a home. The system will use cameras, sensors, and AI algorithms deployed at the edge to detect unusual activities and potential threats in real-time, minimizing latency and ensuring privacy.
Components:
IoT Devices:
Cameras: IP cameras for monitoring different areas of the home.
Motion Sensors: Detect movement in restricted areas.
Door/Window Sensors: Monitor the status of doors and windows (open/closed).
Temperature/Humidity Sensors: Monitor environmental conditions to detect potential fire hazards or unusual activity.
Microphone: To detect glass breaking or other suspicious sounds.
Smart Locks: Control and monitor access to doors.
Edge AI Hardware:
Raspberry Pi/NVIDIA Jetson Nano: Deploy AI models to process video and sensor data locally.
AI Models: Pre-trained models for object detection, facial recognition, and anomaly detection.
Software and Tools:
MQTT Protocol: For communication between IoT devices and the central hub.
TensorFlow Lite/Edge Impulse: For deploying AI models on edge devices.
Node-RED: To create a flow-based programming environment for handling IoT data.
Arduino: For interfacing with various sensors and actuators.
Mobile App/Web Dashboard: For users to monitor the system and receive alerts.
Features:
Real-time Threat Detection:
Use cameras and Edge AI to detect intruders, suspicious movements, or unauthorized access.
The AI model could be trained to recognize faces of known residents and raise an alert if an unknown person is detected.
Smart Alerts:
Send instant alerts to the user’s smartphone via push notifications, SMS, or email when an anomaly is detected.
Provide real-time video feeds and sensor data through a mobile app or web dashboard.
Automated Actions:
Automatically lock doors and windows when suspicious activity is detected.
Trigger alarms or lights to deter potential intruders.
Activate cameras and start recording when movement is detected.
Privacy-Preserving AI:
Use Edge AI to process data locally on the device without sending it to the cloud, preserving user privacy.
Only send critical alerts and data to the cloud if needed.
Environmental Monitoring:
Monitor for potential hazards like fire (using temperature sensors) or floods (using water leak sensors).
Automatically notify the user and trigger safety protocols like shutting off electricity or water supply.
Energy Efficiency:
Use solar panels to power some of the IoT devices to create an eco-friendly system.
The system can go into a low-power mode when no activity is detected.
Challenges and Considerations:
Ensuring low latency and reliable communication between devices.
Implementing strong security measures to prevent unauthorized access to the system.
Optimizing AI models to run efficiently on edge devices with limited processing power.
Designing a user-friendly interface for monitoring and managing the security system.
This project would provide hands-on experience with IoT, Edge AI, and smart home automation, making it a comprehensive and impactful project in the field of IoT and Edge AI.
The reason why I chose the Maixduino Kit is because it has a separate chip dedicated to AI which will be useful in my build.