Video surveillance has existed for years but it is now used more than ever. From the corner of the streets to the elevator of buildings, we are watched everywhere. A lot of factors contribute to the rising popularity of video surveillance.
Apart from fast internet, development in technology, and better devices, algorithms have a huge part to play in it. With the introduction of AI-based video surveillance systems, things have become fairly simple for everyone. Machine learning and see learning are some other technologies that are highly impactful when it comes to video surveillance.
Back in the day, people complained that video surveillance was unable to detect the right objects or often reported false alarms. However, this is not the case now as the algorithms have improved and the techniques have advanced.
How Algorithms Can Enhance Video Surveillance Systems?
AI-Based Video Surveillance
Artificial Intelligence is a great addition to video surveillance as it can identify humans, objects, and even different situations. It analyses the footage to go through the audio as well as video carefully. Such video surveillance systems can be fed with data to make the software realize which situations are normal and which are fishy.
Once the software captures something that is not normal, it sends out alerts immediately to warn the security team. Since AI never gets bored or has a short attention span, it can track every movement to ensure optimum security. Undoubtedly, AI tools can increase the efficiency of any organization.
Machine Learning
Machine learning is all about collecting a wide array of data and then training models according to this available data. This technology has brought some breakthrough results in the field of video surveillance. With machine learning, the accuracy of video systems leveled up.
Apart from accuracy, the ability to distinguish between different objects increased. Objects like cars, different animals can now be identified easily. Also, sounds of different frequencies are identifiable with the help of this algorithm. Most critical problems were solved with the arrival of this technology that led to the betterment of video surveillance systems.
Deep Learning Algorithms
Deep learning is a branch of machine learning. This technology is a family of algorithms and unlike machine learning, it is not complex. Moreover, the software just needs to be trained using this algorithm by collecting different images.
Since it can eliminate the never-ending problem of false alarms, deep learning may just prove to be the most efficient strategy for video surveillance. In simple words, deep learning mimics the mechanism of the human brain to process information. Plus, algorithms based on this technology are exceptional as they allow you to train or control the system.
Increased Efficiency
The security of an organization can be constantly increased using deep learning algorithms. Since the models can be updated continuously, more data can be collected. This process can be repeated till the results are satisfying enough. Alongside, the more data is fed to the system, the more it will understand the human environment.
High accuracy can now be expected out of video surveillance systems because of these factors. Most computer algorithms have an accuracy rate of 95% but this is not the case with deep learning as it offers an accuracy as high as 99%.
Solving Major Issues
When it comes to face or object identification then deep learning’s improvement is unstoppable in this area. Most facial recognition applications are based on the algorithms of deep learning. Apart from his accuracy and identification of objects, one of the greatest advantages of this technology is that it can figure out abnormal events.
Unexpected events can be easily spotted by this tech so it will drastically reduce the cases of false alarms. Several people who were hesitant of opting for video surveillance systems because of the false alarms factor are now open to this idea of AI-based surveillance.
Behavioral Analysis
AI-based surveillance systems can now understand the behavior of humans and determine if the situation is normal or not. Features like size, speed, actions, color, and orientation contribute to figuring out the behavior of humans. By tracking the patterns and matching them with the data helps the software in realizing whether the condition is alarming.
To Conclude -
Deep learning technology is being rapidly opted by various industries as it offers various benefits. Especially when it comes to video surveillance, this technology has proved to be a game-changer. Several solutions popped out by simply scratching the surface of deep learning technology so it has a lot in store for the future.
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