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January 2025
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Service Hotline:400-810-0466
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SAI video analytics for security, command, safe cities, emergency response, traffic, and campuses.

Apply multiple algorithms, flexibly schedule front-end cameras, and schedule back-end computing on demand

Secure, reliable, efficient, and easy to manage, meeting relevant national technical standards

Intelligent, efficient visual big data analytics enabling second-level retrieval of trillion-scale data

Video data source: the video transcoding/broadcast platform integrates SDKs of different vendors, meeting access needs of mainstream vendors’ devices and platforms, supporting third-party extension; meanwhile, encapsulate standard-protocol external interfaces to provide unified external services
Video cloud platform: the video cloud-storage platform is cloud storage based on a distributed file system; on top of HDFS, it further builds a cloud-storage architecture suited to various applications on video-surveillance platforms, such as real-time video preview, video recording playback, and other data storage and query services
Video big data platform (view library): view-library construction refers to the GA/T 1400.4-2017 standard, aggregating and storing structured data from various videos as the view library’s information source for system retrieval, query, and statistical analysis
Algorithm fusion and aggregation platform: has high-energy-efficiency, high-accuracy detection and recognition algorithms built on deep neural networks (person re-identification, open third-party algorithm introduction); capture and recognition accuracy both reach industry-leading levels
Intelligent video-analysis platform: the platform performs structured parsing of live video, historical recordings, offline video, checkpoint images, person images, and more, extracting structured descriptive information of persons, vehicles, and other targets, and passing it to the video-analysis platform for corresponding service applications
Intelligent video-application platform: build business applications such as dynamic face deployment and control, static face retrieval, vehicle recognition, and person-trajectory tracking, meeting all industries’ needs for video analysis
Use a dual-network (video private network and information network) architecture with centralized construction to cascade province, city, and county (district) levels.
Open information-sharing channels, break data barriers, and use a unified analytics platform to avoid duplicate construction and save investment.
Layer and decouple so that, with back-end overall computing unchanged, front-end cameras can be scheduled flexibly, implicitly raising overall analysis capability.
Use advanced AI and big data analytics for dynamic warning and precise targeting; checkpoint alerts, video-led investigation, collision comparison, and in-depth analysis raise work efficiency.

津公网安备 12011602000521号
津公网安备 12011602000521号



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