Video Analytics for a Smart City

Surveillance cameras is so useful and it’s been widely used for auxiliary management and anti-terrorism security all over the world. When there is an incidence, the monitoring process of the surveillance video is time-consuming and labor-intensive. Whether it is event precaution, real-time monitoring in the matter, or security analysis in hindsight. Furthermore, large amount of video data are lost without effective information extraction, resulting in the inefficiency of the existing video surveillance systems.

We bring you this solution which is a video content structuring and analysis system as intelligent as a human vision system. It can extract all the useful information during the whole surveillance process without losing any clue for event analysis.

This system is really an important information module for the infrastructure of smart city, smart transportation and smart security.


This solution can accurately detect and recognize various types of objects and segment the object boundary in pixel-level as well.

Then, it will display a number of detailed attributes of objects. All of these structured data are stored in a distributed big-data platform. Which enables fast playback of the target object and alarm of suspicious incidents according to preset rules. With the fast innovating technologies of object tracing and clustering algorithms, the process of object retrieval is fast yet accurate. With this kind of technology, any object can be steadily tracked in the whole smart city.


This solution has advantage to manual monitoring in the field of smart transportation, with the accuracy of above 90%, it is able to recognize and count motor vehicles, non-motor vehicles and pedestrians on all existing roads on a 24 hours by 7 days basis.

A group of census data can be acquired by extracting the information from the video content of all roads and blocks. Such as traffic directions of all vehicle types, motion trajectory and congestion level. All these data are beneficial to effective decision of a smart transportation system.

This is an example generated map captured from the cctv. It can control traffic light via big data analysis.


We provide: pedestrian monitoring and crowd analysis

We provide: Smart perception and monitoring in traffic

We provide: Smart monitoring of crowds’ safety



Person Monitoring and Analysis:

  • Person Detection:
  • Can count a person:
  • Facial Recognition:
  • Rule Violation Detection:
  • Safety Helmet Detection:
  • Duty Monitoring:
  • Staff Monitoring:

Road and Traffic Monitoring:

  • Traffic Flow Estimation:
  • Traffic Rule Violation Detection:
  • Big Data Platform for Smart Transportation:
  • Dynamic Traffic Light Control via Big Data Analysis:
  • Vehicle Speed Estimation and Display routes in map: