What Do Machine Learning Systems In Cameras Do: An Extensive Guide 

Machine learning is responsible for the future called today we all envisioned a few decades ago. Some of the wildest imaginations depicted across cartoons, science fiction novels, movies and other pop-culture sources are reality now because of Machine Learning Technology helps CCTV Cameras and its allied technologies like artificial intelligence, data science and Big Data. 

When machine learning is incorporated into a device or a module, it not only becomes more efficient but smart as well. It gains the ability to think autonomously and make crucial decisions by itself. That’s exactly what’s happening in the surveillance sector as well. CCTV camera and other surveillance units that have only complemented investigative procedures so far are now detecting and mitigating crimes and hazards in real time. 

They are replacing the human eye and becoming more proactive and active in keeping a premises or an area safe and secured. Machine learning systems in cameras are truly a value addition the industry has been waiting for. However, not much has been explored in this space on the different use cases and benefits of machine learning in surveillance units. 

That’s why this write up will arrive as an eye opener for the uninitiated. Let’s get started. 

Machine Learning Systems In Cameras: Their Use Cases

1. Facial And Object Recognition

Surveillance cameras powered by machine learning models are facial recognition-ready. Meaning, they can not only surveill and transmit real-time footage of environments to stakeholders but detect people, too. With more advanced implementations, faces can be easily matched with criminal databases to detect and isolate fugitives, child traffickers and other criminals.

Another refined implementation of this is object detection, where security cameras are trained to detect suspicious objects and notify law enforcement authorities instantaneously. For example, machine learning-powered CCTV solutions can automatically detect the presence of guns or firearms in crowds and immediately raise an alarm without having to wait for an incident to occur and help the police track down the criminal. That’s why cameras of today are proactive in mitigating crimes. 

Similar purpose is also applied across industries and manufacturing units, where instead of firearms and guns, security cameras pick up instances of fire, gas leak, water pipe breakdown, equipment malfunction, employee injury and more. 

2. Retail Analytics

Retail analytics is fast becoming an integral part of security cameras today. If you hadn’t noticed, consumer dynamics has been extremely volatile over the last few years. This has confused marketers and retail shop owners on what to stock up, how much to stock up and more. 

With CCTV solutions backed by machine learning technology, retail owners now have a better understanding of their target audiences and their preferences. Insights from camera footage across aisles help retail owners know what products are in demand, how to optimize their supply-chain and inventory, which aisle should be dedicated for a particular category of products for higher sales and more. Surveillance cameras in the retail space are helping businesses and chains make informed business decisions apart from securing the place. 

3. Retail Security

Speaking of securing a retail space, CCTV solutions are going an extra mile in preventing crimes in shops and retail stores as well. Strategically placed cameras across aisles and shops help in the detection of shoplifting customers and immediately raise a siren for officials to look into. They are also being implemented to prevent open-fires in retail stores through object detection technology. 

4. Covid-19 Detection

While thermal cameras have existed for quite some time, they have been mainly used to detect the presence of wild animals at night. In commercial spaces like airports, transportation hubs, commercial complexes, workplaces and more, the implementation of thermal cameras have been unheard of majorly. 

But times have changed. Specifically, after the pandemic, the need for thermal cameras powered by machine learning is fast becoming inevitable. With this, business owners and stakeholders can detect people with high body temperature and isolate them for probable Covid-19 infections. Adequate safety protocols to ensure the curtailment of the disease can also be established with cameras’ ability to detect people who are not wearing a mask or are not following social distancing. 

5. AI-Powered Dash Cams

Security cameras are not meant for fixed deployment across premises alone. They can also be mobile and implemented in fleets of vehicles such as connected cars, logistics vehicles, cabs and more. Thanks to the power of edge computing and cellular connectivity, security cameras can now function from anywhere with the same AI-powered abilities. 

Due to this, they are being increasingly deployed as dash cams for real-time monitoring of fleets. They are used by stakeholders to monitor the movement of vehicles, respond to prolonged halt times, send emergency support vehicles, notify rerouting of vehicles and more. 

Further, the cameras on dashboards are also empowered with several abilities such as assessing fastest routes, detecting objects, animals and potholes in advance, forecasting weather conditions, notify cornering and sudden accelerations and more. The entire setup is optimized for the safety and security of drivers and the goods being transported. 

6. Parking And Vehicle Classification

When deployed in bustling places like airports, malls, railway stations and other spaces, machine learning systems in cameras can detect what category of vehicle is entering the premises and redirect it to appropriate dedicated parking spaces. 

For instance, passenger vehicles such as cabs and cars will be routed to a different location when compared to supply-chain fleets. There are also sub-divisions under supply-chain fleets for more optimized parking and utilization of space. Besides, this is also used in tracking movements in vehicles and people through ANPR cameras. 

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Conclusion

The magic of machine learning in the surveillance industry has just begun. We are only standing at the dawn of a new era. As more innovations happen, we will get to witness and experience the rolling out of several new and futuristic features and deployments that will only continue to offer optimum safety and convenience. 

What do you think?

In the meanwhile, if you’re looking to leverage the potential of this technology in your premises and deploy a sophisticated CCTV camera for your business, reach out to us with your requirements today.