AIVI

ARTIFICIAL INTELLIGENCE VIRTUAL INVESTIGOTOR

AIVI is a groundbreaking technology that’s developed through machine learning neural network algorithms to enhance CCTV network systems. In simplest terms it’s a brain for your CCTV network to asses, investigate, alert and act as per your requirements. AIVI is a plug and play devise that supports both local and cloud deployments and provides fast access to front-end equipment for visual AI analysis. In addition to supporting the smart big screen application layer, it can also provide APIs to support third-party platform access.

 

AIVI-CONSTRUCTION

The need for a proactive solution in the global construction sector to effectively utilize funds /assets and supplies in order to improve operations for better conditions are ever being researched and studied. The significance of video-based data has become an important part of this initiative due to its inherent capabilities and real-time characteristics. However, in terms of surveillance video, there are thousands of cameras in the industry which are mainly viewed by human eyes thus consuming a lot of manpower. There is no doubt that it is far more impossible to monitor all videos, and difficult to record, resulting in low efficiency in resources deployed. Therefore, how to make use and explore the value of video data is of great magnitude to application scenarios in the construction industry. To address this concern in the industry, Ai group has developed AIVI construction.

 

Application

AIVI construction has the ability to monitor processes and abnormal behaviour in real time on site. This technology can monitor and track process related concerns, dynamics of workers /vehicles, building materials, construction equipment etc. It uses methods such as target detection and positioning, behaviour assessment and analysis to monitor and implement procedures such as dangerous object placement warning, health and safety concerns, process productivity maximization, warning of dangerous behaviour, etc. The system can be applied 24 hours to carry out comprehensive monitoring and reporting, to ensure the increase in productivity and safety of life and property.

Features

 

AIVI-TRAFFIC

AIVI traffic is developed to cater for traffic control and management needs in urban development environment which assist officials to fully utilise existing recourses deployed. This system can not only obtain real-time urban traffic conditions, but also identify traffic element information, report abnormal events such as vehicle precise trajectory analysis, traffic congestion assessment, and more.

 

URBAN TRAFFIC SITUATION DETECTION

Ai algorithm can be employed in identification of traffic parameters which includes traffic target detection and identification of traffic status parameters.

  • Traffic Target detection and identification includes vehicle detection, vehicle type detection, license plate detection, non-motor vehicle detection, pedestrian detection and  traffic light detection.
  • Traffic status parameter identification includes queuing length of the traffic, traffic speed, and traffic jam.

Through the identification of traffic parameters, AIVI can identify traffic situations and predict optimum traffic light configurations’ has the capability to evaluate the current situation of traffic accurately then analyse and lock down the cause of congestion

INSTINCTIVE  MONITORING OF URBAN POLICE SITUATION

AIVI traffic can now replace front-line police patrols. The 24-hr online Ai algorithms can instinctively scan through all existing CCTV infrastructure deployed on entire city road network with real-time alarm alerts of traffic accidents. It can be used in identifying traffic conditions such as fast lanes, bicycles/motorcycle lanes, pedestrian crossings, etc. Further situations such as Illegal behaviour, abnormal traffic flow at troublesome intersections can also be detected.  The data gathered from this can be used to optimise existing networks without the need of adding new field equipment, or police deployment in a complex social environment

Features