Challenge
The main aim is to boost intelligent video analytics software with the extended anomaly analysis option to prevent illegal attacks on ATMs. There is high competition in the VMS solution providers market. Every company tries to offer its current and potential customers video monitoring software with the most attractive functionality sets. Among the most requested features is embedded AI-powered video analytics. It enables video security systems to instantly identify suspicious behavior & abnormal events to prevent potential threats. The VMS provider's clients include banking institutions. To avoid theft and unauthorized actions with ATMs, the customer decided to boost its existing solution with the anomaly detection algorithm.
The main aim is to boost intelligent video analytics software with the extended anomaly analysis option to prevent illegal attacks on ATMs. There is high competition in the VMS solution providers market. Every company tries to offer its current and potential customers video monitoring software with the most attractive functionality sets. Among the most requested features is embedded AI-powered video analytics. It enables video security systems to instantly identify suspicious behavior & abnormal events to prevent potential threats. The VMS provider's clients include banking institutions. To avoid theft and unauthorized actions with ATMs, the customer decided to boost its existing solution with the anomaly detection algorithm.
Solution
Our computer vision model is figuring out uncommon activities or observations that can enhance suspicions by being statistically distinct from the rest of the observations. Usually, anomalous data is something that doesn’t fit the common pattern. In other words, data anomaly detection is the identification of outlier values in the data series. Often data anomalies are connected with some kind of rare occurring events. For instance, equipment malfunctioning, medical issues, bank frauds, etc. Based on this relationship, it is possible to determine the points that will be considered anomalies. In our case, the anomaly detection algorithm was supposed to be aimed at identifying suspicious persons heading to the ATM.
Video management software works in its usual mode. As soon as persons with suspicious objects or with abnormal clothing accessories approach ATMs, the built-in analytics identifies this as a deviation from the standard, and an alarm notification is generated for the operator. For instance, the person with the balaclava on his head or the person with strange objects in his hands (f.e. gas balloon, gun, hook, etc.) at X-distance from the ATM is perceived as an anomaly. The operator gets the alarm notification and decides what to do next, skip the event, or call security guards & police. So, the developed algorithm defines anomalies and helps to prevent attacks on ATMs to steal money.
Video analytics software plays a significant role because it helps to respond to unwanted events faster and more efficiently. Such an approach helps banking institutions to secure themselves from fraud, robberies, or other types of illegal actions, reduce rates of crime about them, and increase the confidence of clients in the organization.
Our computer vision model is figuring out uncommon activities or observations that can enhance suspicions by being statistically distinct from the rest of the observations. Usually, anomalous data is something that doesn’t fit the common pattern. In other words, data anomaly detection is the identification of outlier values in the data series. Often data anomalies are connected with some kind of rare occurring events. For instance, equipment malfunctioning, medical issues, bank frauds, etc. Based on this relationship, it is possible to determine the points that will be considered anomalies. In our case, the anomaly detection algorithm was supposed to be aimed at identifying suspicious persons heading to the ATM.
Video management software works in its usual mode. As soon as persons with suspicious objects or with abnormal clothing accessories approach ATMs, the built-in analytics identifies this as a deviation from the standard, and an alarm notification is generated for the operator. For instance, the person with the balaclava on his head or the person with strange objects in his hands (f.e. gas balloon, gun, hook, etc.) at X-distance from the ATM is perceived as an anomaly. The operator gets the alarm notification and decides what to do next, skip the event, or call security guards & police. So, the developed algorithm defines anomalies and helps to prevent attacks on ATMs to steal money.
Video analytics software plays a significant role because it helps to respond to unwanted events faster and more efficiently. Such an approach helps banking institutions to secure themselves from fraud, robberies, or other types of illegal actions, reduce rates of crime about them, and increase the confidence of clients in the organization.
Results
Anomaly detection algorithm for identifying suspicious behavior that might lead to robbery and destruction of ATMs was successfully implemented as a part of built-in analytics in VMS. Thanks to the expansion of AI analytics video security provider was able to provide the additional functionality to its client – one of the main German banking institution – and thus to increase security measures with regard to ATMs.
In general, the modern world is the era of state-of-the-art technologies and AI solutions. Object detection, brand recognition, object tracking, face recognition, 3D reconstruction, and lots of other use cases are possible nowadays thanks to the power of technology and progress. The analysis of real-time images & live videos is the reality. Our teams develop custom AI/ML solutions that come in handy by understanding digital pictures and live videos.
Anomaly detection algorithm for identifying suspicious behavior that might lead to robbery and destruction of ATMs was successfully implemented as a part of built-in analytics in VMS. Thanks to the expansion of AI analytics video security provider was able to provide the additional functionality to its client – one of the main German banking institution – and thus to increase security measures with regard to ATMs.
In general, the modern world is the era of state-of-the-art technologies and AI solutions. Object detection, brand recognition, object tracking, face recognition, 3D reconstruction, and lots of other use cases are possible nowadays thanks to the power of technology and progress. The analysis of real-time images & live videos is the reality. Our teams develop custom AI/ML solutions that come in handy by understanding digital pictures and live videos.