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Introduction to AI in Video AnalyticsThe automotive market is on its way to a new face with video analysis's birth. The latest AI and production combination promise a stronger, more efficient, and hassle-free working environment in factories. AI-powered production is set to transform how you work with technologies and with less trouble and better, more refined results. Its primary goal is to detect temporal and spatial events in videos automatically.
Benefits of AI-based Video AnalyticsIt's challenging to monitor and maintain surveillance systems, particularly when dealing with many cameras. It is a hassle to keep track of all that is going on, and it takes a lot of manpower to tackle it. This is not the case with analysis. It uses comprehensive and complex algorithms to analyze recorded streams. Reviewe camera images pixel by pixel, with almost nothing lost. Intelligently tailor to satisfy particular security or business requirements, analytics filters.
According to the Artificial Intelligence Global Surveillance index, at least 75 out of 176 countries globally are actively using AI-based surveillance technologies. Source - How AI Is Making An Impact On The Surveillance World
What are the Challenges?
- For many years, the amount of data collected from video analysis tools has risen; data storage is becoming a problem with the tremendous volume of data obtained.
- The data obtained by CCTV monitoring systems are just as successful as your team can handle. If the human resources do not adequately handle the knowledge you have deployed to do so.
- With rising cases of hacking and internet breaches reported worldwide every day, the security component of the CCTV surveillance system raises a major problem for your company's everyday operations.
What are the technologies involved in Analytics?Analytics is a challenging job, a video will be read frame by frame in a processing, and for each frame, image processing will be performed to remove the features from that frame. There are many libraries for image processing. OpenCV is an open-source computer vision and Machine Learning library built primarily for Image Recognition and processing tasks. On the other hand, Tensorflow is an open-source machine learning library created by Google to detect high precision objects. It is possible to consider a processing as a mixture of three key tasks:
- Object Recognition
Recognition of objects is a form of computer vision for recognizing objects in pictures or recordings. The main consequence of deep learning and machine learning algorithms is object recognition. We can quickly spot characters, things, scenes, and visual information while humans look at an image or watch a film.
Real-Time Video Analytics
Triggering Real-Time Alerts
- Appearance similarity alerting: Based on entity appearance resemblance requirements, surveillance operators may customize a warning.
- Count-based alerting: Alerts can be activated when, within a given period, a certain number of objects (vehicles or people) are observed in a pre-defined location.
- Face recognition alerting: Intelligence services may use it to quickly identify offenders and issue warnings in real-time, based on digital images extracted from film or externally imported if facial recognition technology is approved.
Face Recognition uses computer algorithms to find specific details about a person's face.Click to explore about our, Face Recognition and Detection with Deep Learning
What are the Industrial Applications of Video Analytics?There are various Industrial applications of AI-based Video Analysis. Listed below are several applications:
Smart cities / Transportation
Text-Image Analytics Solutions for Enabling Enterprises to derive actionable insights from Images to increase business efficiency. Source: Computer Vision Services and Solutions
How does Video Analytics work?The design of a solution can differ depending on the individual use case but the scheme stays the same, so there are two different methods of reviewing recorded content: in real-time, by configuring the device to trigger warnings for particular events and accidents that occur at the moment, or in post-processing, by running specialized searches to enable forensic investigation activities.
Video Analytics SolutionsMany off-the-shelf applications in it, from classic surveillance platforms to more complex situations such as smart homes or healthcare software. If one of these standard solutions satisfies your use case, they could be an alternative for you. Generally perform some form of program adaptation or parameterization, and these implementations only allow customization to a certain extent. However, with a this approach, which needs more optimized tools but the most organizations strive to obtain unique information to achieve individual objectives.
ComparisonHowever, tracking each camera continuously is nearly impossible for security personnel. So this means employees do not even have extensive situational awareness. In comparison, surveillance cameras capture overwhelming amounts of videos and still, if they need to perform a post-incident report, security personnel also don't have the resources to manually review the stored footage.
In our everyday activities, AI-based Video Analytics solutions help us. Many sectors can benefit from this technology, especially as the sophistication of possible applications in recent years has increased. The area of video analysis makes both more reliable and less repetitive processes. It is less costly for enterprises, from smart cities to surveillance controls in hospitals and airports. To individuals tracking retail and shopping centers. We recommend talking to our expert.