Lack of real-time dataThe urban transportation system is widely used and the data is scattered, especially for the large-scale deployment of unstructured data, which is not effectively processed.
Road traffic monitoring lags behindThe delay of traffic monitoring is likely to lead to traffic congestion, and the failure to timely limit and dredge the flow will affect the operation of urban traffic.
The demand for centralized processing of resources is hugeThe urban traffic scope is large, the number of equipment is huge, the energy consumption is large, and the intelligent analysis function of massive data is lack.
Traffic flow, vehicle identification, accident monitoring and personnel tracking for roads and tunnels; Subway passenger flow monitoring and suspicious person tracking; Station passenger flow, traffic flow monitoring, suspicious person tracking and other scenarios, formulate visual intelligent solutions for traffic management, build a comprehensive transportation big data center system, promote the development of data enabled transportation, and realize the construction of accurate and efficient traffic management system.
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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