Due to rapid advancement in Deep Learning, AI video analytics, also known as intelligent video analytics, has attracted increasing interest from businesses and organisations. AI video analytics has introduced the automation of tasks that were once exclusive purview of humans. The recent improvement of video analytics have been a game-changer, ranging from applications that count people at events, to automatic license plate recognition, along with other security helpfulness.
What is AI video analytics?
AI video analytics is like artificial intelligence for video surveillance that uses computer software programs to analyse image and audio. The video surveillance can help security recognise humans, vehicles, objects, and events. For example, a person who moves suspiciously, traffic signs that are not obeyed, sudden appearance of flames and smoke.
AI video analytics perform real-time monitoring in which objects, object attributes, movement patterns, or behaviour related to the monitored environment are detected. The analytics can also be used to detect trends and patterns that answer business questions such as:
- When is customer presence at its peak in a store and what is their age distribution?
- How many times is a red light run, and what are the specific license plates of vehicles doing it?
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Industries that will most benefit from using video analytics
- Healthcare – Historically, healthcare institutions have invested large amounts of money in video surveillance to ensure safety of their patients, staff, and visitors. Commonly, theft, infant abduction, and drug diversion are some of the most common crimes within the healthcare industry which can be addressed by surveillance systems.
- Retail – Brick and mortar retailers can use video analytics to understand who their customers are and how they behave, improving sales and customer satisfactions.
- Security – Video surveillance is an old task of the security domain. But from the time that systems were monitored exclusively by humans to current solutions based on video analytics, video surveillance will be better at monitoring large groups of people as it has better facial and license plate recognition and crowd management systems.
How to choose the right AI video analytics for your business?
Given so many choices of video-based analytics out there, every organisation just wants to find the best for their business to reduce the cost of poor choices. The criteria to choosing the right AI video surveillance vary for each business, but here are some key metrics to consider across the field:
- Open platform – it allows users to have complete flexibility, avoid being locked into any particular manufacturer, and utilise the best-of breed solution available in each category.
- Easy to use and set up – one of the main goals of applying AI to security is to help users automate the process of watching hours. Therefore, choose a system that will make it easy for you to operate. Consult the IT or security team if necessary.
- Robustness and reliable performance – a more sobut solution means less time and resource spent on false alarms.
- Versatility – a more versatile analytics solution can recognise more types and behaviours of objects for more use cases.
- Low total cost of ownership – a good analytic software solution is not only capable of many functions, its algorithms are efficient enough to fit more into the same server specs, and it does not require expensive cameras to have good accuracy, thereby increasing cost saving for the entire system.
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