Automated anomaly detection is gaining popularity across various industries as it enables companies and organizations to ensure business continuity. This technology powered by Artificial intelligence can detect anomalous activities happening on business premises, such as accidents or fire, spills, etc. In this article, we’ll learn the possibilities of automated anomaly detection, how it works, and how to set up an anomaly detection system in your business.
Technically, anomalies mean the deviation in a quantity from its expected value. In layman’s terms, an anomalous event is an activity or a group of activities or events that are not expected to happen in a given place at a given time. For example, the occurrence of fire in a factory is an anomalous event. A theft happening in a supermarket, a fight happening in a street, an unauthorized vehicle entering a business premise, etc are examples of anomalous activities.
Identifying such events in real-time is very important as it could affect the business continuity of the organization. A mere accident could halt the entire operations in a factory if not timely intervened to prevent the consequences. For the same reason, organizations employ a lot of staff to monitor the whereabouts of the organization. To identify any activities or events that could potentially affect the business and notify the concerned authority to take immediate actions to salvage the situation.
As the business grows, manual surveillance becomes a bottleneck. Huge business premises and the growing complexity of business operations make manual surveillance costly as it requires large manpower just for surveillance and monitoring. And for that reason, organizations installed CCTV cameras in every corner of their business premises and set up a control room from where security officials can monitor the business processes. But, with a limited attention span, humans are not a good fit for continuous monitoring of the video footage from many CCTV cameras.
What if some or many aspects of security surveillance can be automated?
Wouldn’t that ease the burden from security officials and make the entire security assurance more effective?
That’s what is offered by automated anomaly detection.
Automated anomaly detection system demo
The anomaly detection process can be automated using Artificial intelligence technology, to be specific, computer vision technology. In this technology, the video streams from CCTV cameras are analyzed by software to recognize what is happening in the video. This is a continuous process and when a deviation from the regular set of activities is detected, the software can raise a flag. Further, it can alert the concerned officials about the deviation so that timely intervention can be made.
The video below shows the anomaly detection feature of Emotyx – an AI-powered real-time video analytics suite. In the video, you can see how the software detects the unusual events happening in the video feed and correspondingly trigger various parameters to detect the type of anomalous event. Such a system can detect anomalous events like fire, leakage, explosion, fight, crimes, unauthorized access, etc happening in premises.
The objective of anomaly detection is to identify anomalous activities. Generally, this can be done using three different techniques, that are unsupervised anomaly detection, supervised anomaly detection, and semi-supervised anomaly detection.
In supervised anomaly detection, the system is trained with a labeled data set. The training data would contain data corresponding to normal events and unusual events. For example, a video database with customers shopping in a retail store is labeled ‘normal’ and a similar dataset of videos where people stealing from the retail store is labeled ‘unusual’ When the system is trained with this data, in the future when a person tries to steal something from a retail store, the system can identify this unusual activity and alert the store security officials.
In unsupervised anomaly detection, there is no labeled training data used for training the detection system. It works under the assumption that the majority of the instances occurring in the video footage are normal and a deviation from this pattern is identified as an anomaly. For example, consider a production facility, on normal conditions, the working of machinery, etc would constitute the majority of events. Any deviation, say, for example, an occurrence of fire would trigger the system as it detected an event that has deviated from the majority of events.
In semi-supervised anomaly detection, a detection model is constructed, that represents the normal behavior of a system from a given normal training data set. Using the constructed model, the system can detect unusual activities by calculating the likelihood of occurrence of events as compared to the constructed model.
Almost all kind of businesses can benefit from anomaly detection, especially those businesses which has large business premises like shipping ports, banks, etc. The police department, prisons, public safety departments, can benefit from automated anomaly detection to detect crimes and to enable timely interventions.
In one of the previous articles, we saw the possibilities of real-time anomaly detection in smart cities. Anomaly detection systems can transform the CCTV surveillance cams into a security infrastructure. It can help to detect anomalies happening in public places like subways, airports, office entry gates, parking lots, etc. For example, in a traffic intersection anomaly detection enabled CCTV cameras will be able to identify rule violations, automated number plates tracking, and more.
The smooth running of manufacturing and production facilities is critical for brick and mortar businesses. Automated anomaly detection for warehouses, factories, and manufacturing units can bring in many benefits as well. A factory is responsible for thousands of activities. From processing raw materials and to packaging, there are thousands of operations that need to be work like a well-oiled machine. Anomaly detection systems can identify potential threats that could affect the business operations, such as leakage of fuel, the occurrence of fire, improper usage of machinery, etc, and notify officials to take immediate actions.
For banking institutions, anomaly detection can help identity theft attempts in ATMs and raise automated panic alarms to notify law enforcement officials in case of a robbery attempt inside banking institutions, etc. Anomaly detection in the banking sector can help banking institutes to better equipped to fight thefts and robbery attacks.
Anomaly detection can bring many benefits to businesses and organizations, but, how to get started is the part where most business owners are stuck in. The best way forward is to use anomaly detection software like Emotyx, which can be ‘plugged’ into your existing CCTV infrastructure. The software can operate on top of your existing CCTV infrastructure, irrespective of the hardware, or the video management software used by it. Emotyx can analyze the visual feeds generated from the cameras and produce actionable insights to make your business more secure. If you’d like to get a demo of how it works, feel free to reach out to us.
Automated anomaly detection system demo