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#News(General) [ via IoTForIndiaGroup ]
So, if data is the new oil, then the question is, who is your refiner? Thanks to AI, solutions are emerging to fix these issues and start providing insights that automated systems can use in real time.
The Video Surveillance Case:
Video surveillance is one extreme example of the massive amount of data being used in industries like transportation, energy, construction, manufacturing and municipalities. Camera equipment has become significantly cheaper and more accepted in workplaces as necessary tools. With video comes visual data from numerous cameras — sometimes hundreds or thousands — and the inability of humans to review the amount of hours of video captured by all those cameras. Companies install video cameras. However, they stop watching the video feeds over time. The data only becomes important when a specific event requires review. Then, video monitoring becomes an exercise in forensics to pinpoint and verify a particular event or anomaly.
Andrew Ng, Co-Founder of Coursera, an AI pioneer at Google and Baidu and thought leader on machine learning, put it this way: “Pretty much anything that a normal person can do in 1 sec, we can now automate with AI And, this is 95% of what we do everyday.The Case For Unassisted AI
Unassisted AI is one aspect of how artificial intelligence can be applied. According to Marc Jadoul, IoT Market Development Director for Nokia, it’s the unassisted AI component to their Nokia Impact Scene Analytics solution that provides a key differentiating benefit for verticals like transportation, utilities, and the public sector. “Supervised AI can be very beneficial in certain situations. However, for it to work requires thousands of hours of video clips to teach the system. This includes feeding the system any number of situations and outcomes so it can learn how to identify those in the future.”
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