Preliminary Research and Documentation
The complete project comprises of the following modules:
- Real time object tracking system developed on AI/ML platforms using high resolution cameras
- Intruder alert system
Real time Object Tracking System
A real time object tracking system is designed to identify, tag and monitor people and objects and store their image information in a database. Software applications can process this data and create workflows that help in securing seapods, and tracking boats, yachts and even.
High resolution cameras, installed at strategic points like beaches, buoys and seapods continuously scan and monitor the water surface for ships, boats and yachts. Underwater cameras are installed on buoys, seapod bases, or mounted on rocks to monitor underwater activity. Data and images from both sources are collated and a unique ID is generated for each boat that passes by these strategic locations. The unique ID along with the image code is stored in a database. Technologies like TensorFlow or YOLO (You Only Look Once) use AI and ML to analyze the ship and a log is created every time the ship or boat passes by.
Optionally, a unique display code, QR code or AR code is generated and assigned for each boat by legal authorities. These are displayed on the ship and can be scanned and identified by cameras and software from far away.
Figure 1 - Sample image to illustrate real time object tracking and tagging boats using AI.
When an unidentified boat approaches a sea pod, the software triggers an alarm and notifies the residents, security personnel and legal authorities.
Intruder identification and theft prevention comprises of the following modules:
- Motion sensors
- Facial recognition system
- Alarm system
Data and images from all these sources are collated and a unique ID is generated for each person. Technologies like OpenCV, TensorFlow or YOLO (You Only Look Once) use AI and ML to identify a person a log is created every time the person passes by the camera.
Motion sensors or movement sensors are electronic devices that detect and measure movement. It uses ultrasonic sensor technology and emit sound waves to detect presence of objects. Motion sensors are installed in different areas of the seapod. When residents are away, these motion sensors scan the covered area for intruders. When motion is detected, the sensor triggers an alarm and sends a notification to the resident and local authorities.
Facial Recognition System
High resolution cameras, installed at strategic points inside and outside seapods, buoys and boats continuously scan and monitor the area for intruders. Underwater cameras are installed on buoys, seapod bases, or mounted on rocks to monitor intruders trying to gain underwater access to seapods.
Intruder identification software allows owners and residents to enter images and details of family to enter names and image capture of family and friends. This data is stored in the database.
Figure 2 - Sample image to illustrate facial recognition system for family and friends using OpenCV and AI.
When an intruder breaks in to the seapod, the cameras scan the intruders face and compares it against the entries in the database. If no match is found, it triggers an alarm and sends a notification to the owners, residents and local authories.
Figure 2 - Sample image to illustrate facial recognition system for intruder using OpenCV and AI.
This project is being developed as an open-source project with the following licensing: