Leveraging Video Object Detection for Efficient Video Transmission

Based on Patent Research | CN-110233995-A (2024)

Sending high volume video data from mobile trawlers over limited satellite links creates massive bottlenecks. Standard methods waste bandwidth by transmitting every frame, leading to high costs and slow delivery. Video object detection solves this by identifying and locating specific items within a sequence of images. This method allows systems to filter content locally. Only important visual data reaches the base station. This process ensures efficient data flow while lowering operational expenses for remote monitoring.

SOLUTION OVERVIEW

Raw streaming to AI detection

Video object detection technology provides a direct solution for telecommunications managers struggling with congested satellite links and high data transit costs. The process begins at the edge, where local hardware receives a continuous stream of visual data from mobile maritime cameras. The system uses specialized algorithms to scan every frame, identifying and categorizing specific objects like equipment or crew activity. Once these items are localized, the software filters out static backgrounds, transmitting only the relevant segments to the base station for final review.

By automating the analysis of visual feeds, this technology integrates seamlessly with existing network management workflows to optimize satellite throughput. It acts like a smart mail sorter that identifies urgent documents and discards junk mail before it ever enters the expensive air transport system. This automation reduces the burden on manual monitoring teams and ensures that critical alerts reach onshore centers instantly. As remote connectivity becomes more essential, this intelligent filtering will be a cornerstone of sustainable and efficient maritime communication strategies.

HOW IT WORKS

Capturing detections from remote video

Capturing Local Video Streams

Onboard cameras located on mobile maritime trawlers continuously gather high volume video data from their surroundings. This raw visual input serves as the primary source for the system, providing a live feed of all vessel activities and environment conditions.

Identifying Relevant Visual Objects

Local hardware at the edge uses specialized algorithms to scan every incoming frame for relevant items like crew members or equipment. The system categorizes these objects and marks their exact location within the image sequence, ensuring that every important event is documented.

Filtering Redundant Background Information

Once the software localizes specific activities, it discards redundant visual information and non-essential background scenery. This step transforms the high-bandwidth video into a streamlined selection of data that only contains the most critical visual evidence.

Transmitting Optimized Data Packets

The system sends only the prioritized segments across limited satellite links to the shore-based monitoring station. By reducing the total volume of data transmitted, this final stage minimizes network congestion and lowers overall operational costs for telecommunications managers.

Potential Benefits

Significant Satellite Bandwidth Savings

By filtering out static backgrounds and transmitting only detected objects, the system drastically reduces the volume of data sent over expensive satellite links.

Substantial Operational Cost Reductions

Intelligent data prioritization minimizes high transit fees associated with raw video streams, allowing maritime operations to maintain remote monitoring within sustainable budgets.

Enhanced Real Time Alerting

Automated object detection identifies critical events at the edge, ensuring that urgent visual information reaches onshore base stations instantly without being delayed by network congestion.

Optimized Network Management Efficiency

This solution integrates into existing workflows to act as a smart filter, preventing junk data from entering the air transport system and streamlining communications.

Implementation

1 Edge Hardware Deployment. Install ruggedized processing units and high-resolution cameras on maritime vessels to capture raw video feeds locally.

2 Model Configuration. Configure the object detection algorithms to recognize specific maritime targets such as crew members and equipment.

3 Network Gateway Integration. Connect the local edge hardware to existing satellite communication systems to facilitate prioritized data transmission.

4 Filtering Logic Calibration. Define the visual triggers that determine which video segments are essential for transmission to the base station.

5 Centralized Monitoring Setup. Establish a shore-based interface to receive and review the optimized visual alerts from the remote vessels.

Source: Analysis based on Patent CN-110233995-A "It is a kind of to cooperate with the trawler intelligent monitoring system handled and processing method with bank base based on boat-carrying" (Filed: August 2024).