A large number of urban security videos are deployed, and most of the video data has not been intelligently analyzed, which in vain consumes a lot of network bandwidth and storage resources.
The public area environment is complex, and the demand for scenario application analysis is diverse. Users need AI to fully support the business and get rid of the lock of manufacturers and technology platforms.
Operation and maintenance costs the traditional public safety area management mode requires a lot of operation and maintenance costs.
With computer vision as the core, it is widely used in public security fields such as stadiums, hospitals, parks, scenic spots, squares, communities, buildings, blocks, and farmers' markets, to create intelligent video monitoring and management solutions covering multiple scene applications, such as face recognition, vehicle detection, fall behavior recognition, mask wearing recognition, smoking recognition, uniforms and hats wearing recognition, uncivilized parking, intrusion warning in dangerous areas Personnel track tracking, legacy monitoring, etc. Effectively ensure the safety of public areas, enable the city to have the most accurate visual perception, improve the level of social security management, and create a harmonious and safe social home.
The management system is prepared, operated and managed by the user, and the user independently grasps the data information.
Provide a variety of advanced algorithms, covering different computing power systems. For specific scenes, users can use semi-automatic annotation tools to optimize the algorithm.
On the premise of fully protecting users' data privacy, accurate analysis and identification, rapid response, and timely submission of results.
Low code no code (lcnc) platform, reduce AI development steps, software and hardware forms, multi scenario applications, and match the most cost-effective scheme according to requirements.
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