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Moving towards an AI-enabled future

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McKinsey Global Institute claims that artificial intelligence is contributing to a transformation of society 10 times faster and at 300 times the scale, or roughly 3000 times the impact of the Industrial Revolution.

This is observed by the upsurge in artificial intelligence and computer vision adaptation as well as the demand to keep up with the technology and innovation in businesses in the last few years. According to a report by IDC, aggressive investments have been made in cognitive and AI solutions and in fact, global investments are expected to reach $57.6 billion by 2021.

Such investments are catalysed by the advent of modern computer vision and image processing techniques. AI-powered computer vision coupled with hardware-based accelerators have opened up the possibilities of analysing images in real-time to identify objects and activities.

Since, a typical CCTV image is more than 100,000 Bytes, in this context, it might be quite apt to surmise that a picture is worth hundred-thousand words!

At present, there are over 500 million CCTV cameras installed and the number is expected to rise to over a Billion by 2021. While these cameras cover everything from manufacturing, yards, warehouses, retail outlets to several parts of modern cities, so far they have been used retrospectively for monitoring and forensic analysis.

However, there is substantial growth in their usage in various verticals. For instance, retail outlets are getting equipped with the capability of knowing their customer demographics, dwell time and even emotions. Even the government is contemplating their use in smart city initiatives as they could prove beneficial if suspect activities are filtered from the live CCTV footages. Likewise, manufacturing premises bolster their safety parameters by ensuring any hazardous non-compliance is actively analysed and reported.

In fact, stepping up occupational health & safety for people at all levels is the new benchmark that some of the companies are trying to work towards. If this becomes a norm, it could make a sustainable difference in global OSH challenges and promise a brighter future.

Thus, an AI-enabled future lies in the best use of distributed vision technologies while delving into the deeper end of machine learning and deep learning to explore and understand the potential of these technologies better.

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