Nethra Video Analytics
Instant and actionable insights from video.
Observe, Predict, Prevent
Nethra is a ‘precognitive’ video platform, that uses sophisticated deep-learning algorithms to analyse patterns and see possible outcomes, in real-time. Nethra transcends the limitations of the human eye and what a human being can process at one time. It’s costly in terms of time and manpower for humans to observe key warning signs and events in video, but by relying on AI to analyse multiple streams resources can be deployed quicker and more efficiently. Whether saving precious seconds by predicting an accident in a manufacturing plant or enabling proactive policing in crime hot spots the scope for Nethra Video Analytics applications is vast and exciting.
Live Insights From Multiple Feeds
Nethra uses deep learning to analyse live and batch video data. By training Nethra to recognise actions it can automatically analyse live video and flag not just when those actions occur but when they’re likely to occur. Training the deep learning algorithms requires thousands of hours of footage but when done Nethra will be able to detect those actions with a high degree of accuracy in batch video or live streams. These distinct actions can be as different as an emerging fight or someone using their phone while driving. Nethra’s video analytics software will pick up visual information the human eye would miss and it does it across multiple simultaneous video feeds, freeing valuable manpower for more practical jobs that only a human can perform.
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.
Case Study: Identifying Cancer Cells with Machine Learning Using Oscar
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