INDUSTRIAL REVOLUTION 4.0

Humans have witnessed changes in their lifestyle after every wave of industrial revolution. Right from 1st revolution of steam engine, 2nd revolution of Electricity, oil, gas, 3rd revolution of computers,electronics to the 4th revolution of internet and AI, ML which is referred as industrial revolution 4.0.
People would always use the technology they had available to help make their lives easier at business and personal level.
It's the network of these machines that are digitally connected with one another and create as well as share information that results in the true power of Industry 4.0.
The 4.o revolution includes IoT, Machine learning, Artificial intelligence, Robotics,Cloud computing, Big data, Data analytics, Video analytics.
These emerging technologies have applications in various industries Finance, logistics, IT, Retail, FMCG to name a few.

Video Analytics:

Video analysis or video content analytics, also known as video analysis or video analytics, is the capability of automatically analyzing video to detect and determine temporal and spatial events.
Machine learning and, in particular, the development of deep learning approaches, has revolutionized video analytics.
The use of Deep Neural Networks (DNNs) has made it possible to train video analysis systems that mimic human behavior, resulting in a paradigm shift.
It all started with systems based on classic computer vision techniques (e.g. triggering an alert if the camera image gets too dark or changes drastically) and moved to systems capable of identifying specific objects in an image and tracking their path.

One such example is Optical Character Recognition (OCR)
A real-world application of this would be the recognition of license plates at parking area, where the camera is located near the gates and could film the license plate when the car stops. However, running OCR constantly on images from a traffic camera is not reliable: if the OCR returns a result, how can we be sure that it really corresponds to a license plate?
In the new paradigm, models based on deep learning are able to identify the exact area of an image in which license plates appear. With this information, OCR is applied only to the exact region in question, leading to reliable and effective results.

• OCR( optical character recognition) : It is a process to recognize text and images of scanned documents and photos like identity proof, passport etc.
• LPR(License plate recognition) : Efficient license plate recognition with a minimal error rate
• Crowd detection : For customer segmentation which can be used in retail showroom.
• Face recognition : Identify identity of a person.

There is a plethora of off-the-shelf solutions in the video analytics domain, from classic security systems to more complex scenarios such as smart homes or healthcare applications.
There are a vast number of sectors that can benefit from this technology, especially as the complexity of potential applications has been growing in recent years.
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