Vehicle Big Data
Solution Overview
SOPHON utilizes deep learning processors as the foundational infrastructure for intelligent monitoring and auxiliary management of congestion, safety, violations, and road conditions in urban traffic. This effectively enhances rapid response and scientific handling capabilities for unforeseen incidents, while also improving traffic operational efficiency and safety levels. It ensures smooth and unobstructed roadways.
Solution Value
Resource Integration
Support for diverse resource access including images, video streams, etc.; Comprehensive integration of various resources such as electronic police, checkpoints, and video, effectively expanding data accessibility.
Multi-dimensional Features
Support for the identification and processing of multi-dimensional structured features including vehicle type, category, color, license plate, as well as vehicle-specific features and occupants.
Enhanced Practical Application
Integrates functions such as vehicle search, big data analysis, violation detection, early warning, deployment, and inspection, building a comprehensive and practical application of vehicle big data.
Typical Cases
Yuxi City Vehicle Big Data Project
The project utilizes the SOPHON's computational capability to construct video structured analysis, accomplishing structured recognition of pedestrians, vehicles, motorcycles, and tricycles in key areas. By incorporating new image parsing capabilities for people and vehicles, it meets the requirements for intelligent front-end devices to reparse images for transmission. The project integrates and filters video data from key road sections, important locations, critical intersections, etc. It focuses on real-time passing data and, based on Algorithmin's intelligent computing infrastructure, conducts in-depth structured analysis applications locally. This project has initially addressed difficulties in networking and judging passing data, querying data, and implementing in-depth applications. It has improved the handling of violations, congestion relief, and addressed challenges in controlling special vehicles such as construction vehicles, hazardous material transport vehicles, tricycles, and motorcycles.
Traffic Police Project in a Certain Area of Qingdao City
The project utilizes the SOPHON's computational capability to construct video structured analysis, completing structured recognition of pedestrians, vehicles, motorcycles, and tricycles in key areas. By incorporating new image parsing capabilities for people and vehicles, it meets the requirements for intelligent front-end devices to reparse images for transmission. The project includes the addition of traffic event detection business, analyzing behaviors such as separate lanes for passengers and cargo, illegal parking, abnormal behaviors of motor vehicles, non-motorized lane occupation, vehicle collisions, vehicles crossing, vehicle reversing, road congestion, and motor vehicle lane occupation. It achieves automatic and rapid processing of video image information, fully support road traffic needs