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Nethra Video Analytics
Instant and actionable insights from video.
Nethra Trailer
Preventative Surveillance
Nethra is a Deep Learning platform that uses trained neural networks to identify numerous actions and objects from live video. Turn passive CCTV into a proactive tool for prevention. Insights can be streamed from standard quality video footage and Nethra can be run on edge devices or installed locally. Nethra has been trained to identify and alert for a wide variety of different use cases, ranging from fighting, to car crashes to left luggage.
Faster than the Competition
In environments where response times can save lives or save businesses money, such as Defence, Health & Safety or Smart Cities every second counts. We've benchmarked Nethra against competitor frameworks and have found we exceed their object detection speeds by at least 45% and in some cases 630%. This means faster alerts and faster responses.
Powered by Big Data
Detecting events and delivering the information in real time is just one part of what Nethra does. The next step is making use of that information for proactive planning. Nethra’s visual insights can be combined with other data sources to provide accurate predictions and insights using Nethra’s built in big data analytics. One examples could be allowing emergency services including police forces, and crowd managers to plan resource allocation across a city based on past instances of certain events. Or in a retail setting Nethra can identity trends and patterns in movement throughout a busy shopping centre for advertisements.
Vast Number of Applications
There are many potential use cases for Nethra’s blend of precognitive video analysis and big data analytics. Focussing on crowd dynamics, Nethra can provide insights into numbers, clusters, distributions, movements and behaviours using machine learning. Combined with a smart cities infrastructure, aggregated data from city and highway video cameras can be analysed with Nethra, looking at volume, timing, and distribution of traffic to increase the efficiency of inner city transport. Alerts can be sent directly to law enforcement or decision makers when certain criteria are met allowing seamless responses.
