Video surveillance is a ubiquitous sight in most parts of the world, a system that refers to the use of closed-circuit television cameras in order to transmit signals to a limited number of monitors. The history of the technology is actually quite old, with the earliest mechanical CCTV developed in 1927 by Leon Theremin. This system consisted of cameras that were manually operated and which could transmit scans, as well as wireless shortwave transmitters and receivers. In 1942, Walter Bruch installed another form of early CCTV. However, it wasn’t until 1949 that closed-circuit television systems became available after being developed by American manufacturer Remington Rand, originally a typewriter producer and later a constructor of the UNIVAC line of mainframe computers.
Designed by CBS Laboratories, this system, called “Vericon,” was advertised as not requiring any additional government permit to operate because of its cabled connections between cameras and monitors, which replaced earlier over-the-air transmission. The technology has evolved considerably and consistently over the years, with videocassette recorder tech becoming available in the 70s, which made it easier to both record and erase information. The use of video surveillance became much more common around this time as well. Modern CCTV is Internet-based, uses IP cameras, and systems that can be combined with other data streams.
Now that artificial intelligence is developing at a faster pace than ever before and being integrated in more businesses and industry landscapes, experts have begun analyzing the ways in which it will change video surveillance as well.
The uses
The use cases of AI are varied and complex, so it is no surprise that it can be integrated in surveillance as well. The technology is used in order to analyze footage efficiently and in real-time, identify vehicles, individuals, or behavioral patterns, and automate monitoring. It can decrease the incidence of false alarms and enable more proactive security measures. Threats of all kinds, from unusual activity to unauthorized access, can potentially be identified faster so that the responses are more effective as well. The integration of AI makes the system more active and changes the approach to surveillance and security.
The range of SPRO NVRs supplied by DTS Digital support AI-powered intelligence in the form of smart alerts and highly precise detection due to the built-in features. Face detection and recognition, tripwire filtering, perimeter intrusion, and SMD Plus motion detection are included in their products as well, reducing the incidence of false alarms. The best thing is that the devices offer professional-grade services that are nevertheless user-friendly, making them highly reliable. AI-based systems can be connected to other security systems as well in order to create more comprehensive responses.
The features of a strong system
A good video surveillance system is one that does the job well and fits the requirements of the people using it. However, there are a few key characteristics that can determine if the devices are good or not. First and foremost, they need to be able to deliver high-resolution recordings. The products from DTS Digital, for instance, can record up to 12 MP (4K) and even in 32 MP resolution. Night vision must be reliable as well, while remote access should be available as well, so that you can access the cameras via mobile app as well, to keep your mind at ease and check that things are in order even when you’re away from home. Reliable storage, motion-activated recording, and two-way audio are often included as well to guarantee clear footage, consistent monitoring, and adaptability.
AI can improve these features and make them even more efficient. For example, in the case of the resolution, artificial intelligence provides intelligent decoding. Storage efficiency is optimized as well, analytics are assisted at all times, and there is seamless integration with either third-party cameras or additional video systems.
Predictive analysis
One of the most important features of AI is that it not only boosts efficiency, but it can also be used as a prediction tool. Predictive analysis powered by this technology is a very proactive approach to security that many see as the next step in their approach and the missing puzzle piece of their systems as well. The algorithms can provide forecasts based on historical data in order to come up with strategies that can address threats and minimize their impact.
For surveillance systems, the devices use machine learning features in order to determine patterns and irregularities throughout massive amounts of data. They can recognize deviations when they take place so that they’re separated from regular occurrences. Flagging a certain event as a security alert doesn’t necessarily make it a cause for concern, as the information should still be reviewed, but it provides you with a comprehensive view of what’s going on so that you’re not caught unprepared. Some security threats can be the result of quiet escalation that you wouldn’t have been aware of otherwise, but a complex system will allow you to have a
Very good idea of how things are evolving so that you develop measures that nip the issues in the bud, before they get the chance to cause real problems.
Smart Object Detection
Smart object detection is a feature that uses artificial intelligence in order to recognize, situate, and classify several different items within videos or images. Advanced algorithms are used for this purpose, typically based on complex networks or deep learning, so that the network can perform tasks with high accuracy and efficiency. The idea here is to mimic human visual abilities as closely as possible. The process works by gathering input and then analyzing it. The resulting information is processed from several different angles in order to determine the shape, hues, and edges of each object.
Localization and classification are implemented in the aftermath, so that each item is placed in its own specific category; once this is complete, the final output can be generated, as the detected objects are labelled and placed in their corresponding areas. This is a crucial feature to have if you’re in an area where it can be difficult to distinguish between things that are completely harmless and those which are potentially hazardous. Having detailed information about all the objects located in the camera’s view is also very important for overall security.
To summarize, while AI is still in its earliest stages and there’s undoubtedly potential for further developments in the future, the technology is already shaping the landscape of the video surveillance sector.
