Intelligent video analytics is a huge step forward in how we can better use software as a way to make sense of the world around us.
The world around us is constantly shifting and transforming and is full of so much more information than a static, single frame can give us. If businesses truly want to understand why, what or how something is happening, they need to analyse our world in motion.
Of course, a computer recognising a polar bear or a cat from a still picture is still relatively impressive. The bigger test however lies in AI’s ability to understand that cat in a shifting, real-time video stream- noting it as not only “a cat” but also as “animal”, “mammal” and “feline”. This sophisticated level of understanding requires a really considerable amount of computing power.
Enter Jaggu Video — an AI platform which gives you the power to automatically understand what is happening in live videos. It is the digital eyes with the brains to match. Our technology identifies not only different objects in video but activities, patterns of movement, behaviour, locations, anomalies, demography, logos, genders and colours. It filters and processes all this data in real time- automatically interpreting an unfolding visual scene.
Action Training
The science behind this technology is known as deep learning. It involves training simulated neural networks to recognise different ‘stuff’ from a large number of examples. A team of paid staff watch videos and add keywords- providing the system with the examples it needs to learn. Here at Jaggu this semantic understanding is highly complex- our AI has a hierarchical knowledge and identifies categories as well as objects in live, action-packed footage, first noting “vehicle” then recognising it as “a car” and then finally naming it an “Aston Martin”.
Shelf Life
Jaggu Video analysis in-store at Geometry’s new flagship
Retail is a competitive sector driven by constantly shifting shopper behaviour. It’s therefore more important than ever that retailers understand what is taking place in their shops and react quickly –customer and in-store insight being the new vital tools for a successful competitive advantage. In fact, Peak’s data science team recently found that retailers using AI grow 30% faster than those who don’t.
Image: The Verge
Jaggu Video monitors and measures in-store staff and consumer behaviour providing valuable insight into where retail organisations can improve their marketing, operational and staffing strategies. By giving retail business owners a live, constant stream of ‘shelf truth’ this technology frees up time spent on manual shelf inspections, improves product availability (and reduction of Out of Stocks) and can even reorder stock for you automatically. By analysing this situational and behaviour data, Jaggu helps companies understand the motivation for why, when and how a consumer makes a purchase decision at any given time. And, of course, this information is entirely objective- free of human error or bias.
Data Traffic
A live stream of automated video analysis for the council
Jaggu Video can also apply to traffic management- helping to measure pedestrian flow and vehicle traffic to dynamically improve congestion and reduce pollution. Jaggu’s AI-based systems utilises intersection cameras to manage traffic flow, by providing insights for various parts of the day and night. Furthermore, with the Chancellor today announcing a £420 million fund in the Budget to fix a record pothole problem, technology that could improve incident reporting and facilitate preventive maintenance of the road infrastructure seems more relevant than ever.
A city could also gain real-time, meaningful data for optimising the organisation of planned infrastructure. For example, this might involve planning where to position street lights in accordance with where crowds tend to congregate for events. When combined with other applications like smart parking, we hope our platform could also help with shaping infrastructure changes or future development.
AI Insight. Human Interpretation.
While our AI is great at identifying what’s going on in a video at a high level (e.g. someone is brushing their teeth or looking at their phone), we do not claim to be able to extract all the context needed to make those uniquely human calls. Ours is a collaborative technology that aids, not makes, decisions.
For example, Jaggu Video can identify that a “person is running,” but it will not be able to interpret if their pace is due to missing the bus or being late for work. This vital next step is still left up to people that see the data- we just help you get to an actionable response faster.
Our Intelligent video analysis is better focusing human attention on what matters most, to dynamically change the way users make sense of the world around them. After all, actions speak louder than words and we want to help you listen.
