Parcels and Theft Detection
Overview
The Parcel Drop-in, Pickup, and Theft Detection system is an AI-driven solution designed to monitor and track parcels left outside homes or businesses. By leveraging computer vision and deep learning technologies, the system provides real-time detection of parcel drop-ins, pickups, and possible thefts. The goal is to enhance security and convenience by automating parcel monitoring, ensuring packages are safely delivered and retrieved, and providing immediate alerts in case of suspicious activities.
Objectives
- Automate parcel detection: Accurately identify parcels dropped off by couriers or picked up by users using AI-driven object detection.
- Prevent theft: Detect unauthorized handling of parcels and provide real-time alerts to homeowners or business owners.
- Optimize home security: Enhance smart home camera functionality with specialized parcel monitoring features.
- Ease of use: Provide an intuitive interface to review parcel events and control camera functionality.
Technical Architecture
The system architecture integrates multiple components to achieve seamless detection and monitoring:
- Smart Camera: High-resolution cameras connected to a cloud-based server are installed at the location of interest. These cameras capture live video streams.
- Object Detection Model: A YOLO-based model trained to detect parcels, vehicles, and humans processes the video feed. The model runs inference on 640×640 input images to ensure efficient real-time processing.
- Event Classification: Using bounding boxes, the system classifies events such as parcel drop-ins, pickups, or possible thefts based on movement patterns and interactions with the parcel.
- Notification System: If a theft or unauthorized action is detected, an alert is sent to the user through an app or email notification.
- Storage and Review: Recorded events are stored in a cloud database, allowing users to review past parcel interactions and adjust system settings.
Tech Stack
- Object Detection: YOLOv5 model trained for parcel, vehicle, and human detection.
- Deep Learning Frameworks: PyTorch for model training and inference.
- Cloud Infrastructure: AWS for hosting video streams, model inference, and database storage.
- Frontend Interface: React-based web and mobile applications for event viewing and control.
- Backend: FastAPI for serving detection results and handling user interactions.
- Notification Services: Twilio API for sending real-time alerts
Conclusion
The Parcel Drop-in, Pickup, and Theft Detection system adds significant value to smart home security by addressing one of the most frequent issues in e-commerce—parcel theft. With its efficient and scalable architecture, the system not only ensures package safety but also offers peace of mind for users who frequently receive deliveries. It is a forward-looking solution, ready to be integrated into existing smart home platforms.
For more information on how aiblux can help you with custom software solutions, contact us or explore our services.
