What Can AI Solutions Do to Combat Operator Fatigue?
When experienced for a long period of time, fatigue can lead to a wide range of health issues both physical and mental. People with long-term tiredness are often prone to depression and anxiety as a consequence. It disrupts their innate biological clock, making daily routines more difficult and can trigger insomnia, heart and kidney problems.
Furthermore, fatigue slows down reaction mechanisms in humans, reduces attention and alertness, while limiting short-term memory and weakening rational judgment. For security officers at work, fatigue severely affects their performance and decision-making, raising the risk for serious breaches and increased alert ignorance.
In this white paper, we discuss fatigue and the threat of fatigue in security surveillance. Operators are a critical part of the security system’s operations and fatigue reduction measures must be taken.
While conventional solutions exist, like making time adjustments to operators’ shifts, we should not fully rely on them. High-tech supported alternatives like AI solutions can be designed to help fight against operator fatigue, enhance safety, and productivity. Artificial Intelligence (AI) powered Management Systems are also introduced as life-savers for alarm monitoring companies, along with the benefits and reasons why they should be included as soon as possible in security work.
Understanding Operator Fatigue
Operator fatigue is defined as the tiredness and reduced alertness commonly experienced by people working in security system monitoring, aviation monitoring, transportation, etc. The causes of operator fatigue are known to be sleep deprivation, low sleep quality, long constant night shifts which result in accidents and overlooked security breaches.
How Operator Fatigue Reduces Safety in Security System Monitoring
In the past, the grainy, eye-straining image quality produced by early surveillance cameras were a major concern for operators. The introduction of High Definition cameras has since helped with this trend.
But at the same time, technological developments in both surveillance hardware have drastically altered the role of a security operator. They are no longer just watching a bunch of small-sized television screen. Operators now need to oversee alarms from door readers, intrusion panels, perimeter detection sensors, automation controls, and more. Today, the modern operator has to simultaneously monitor hundreds of cameras on a daily basis.
With the support of high-tech, AI powered systems, security employees can now make decisions more quickly and accurately using video analytics. AI video analytics operate based on machine learning algorithms set to closely mimic human vision by breaking down and learning from the video footage being analyzed. This advanced technology allows false alarm elimination of up to 95% in video surveillance setups merely by detecting and classifying the objects of interest and filtering out irrelevant information. Not only that, operators can also take part in defining precise criteria for the system to distinguish between true and false alarms unique to their own industrial preferences.
Owing to the nature of their job, personnel in security operations must constantly monitor and process a large amount of information derived from videos filled with unexpected movements. These footages may contain true or easily misinterpreted images observed from the motions of people, animals, vehicles and so on that can trigger confusing alerts by accident. As a consequence of multiple surveillance screens coupled with the continuous movements displayed on them, operators become worn out and start to lose focus over which situation is worth further investigation.
Operators being prone to tiredness and fatigue can easily lead to reduced safety in security surveillance. Because of this, operators’ detection of true and false alerts are no longer exact. The frequent false alerts observed everyday, especially during straining night shifts, put operators off-guard, leaving room for serious security breaches being overlooked. In the process of cameras monitoring, security officers will place more emphasis on the hotspots or sensitive points whereby if a stranger shows up, would signal potential security violations. Over time, when operators have grown tired of the screens, sign reading becomes inaccurate and danger is only noticed after the breach occurs. Tired operators are somewhat the reason behind shoplifts, robberies of expensive goods happening in tech malls, car dealerships, and jewelers, etc.
What Companies Have Tried Before AI
Although security operators work according to shifts, systems monitoring and maintenance must be done around the clock to ensure safety. Additionally, under low light conditions, more security breaches are bound to happen at night time meaning that there will always be required personnel risking their well-being to work at odd hours, which is proven by researches to have adverse effects on their bodies.
Before the application of AI into security operations, companies have been allowing operators to take more frequent breaks away from their stressful working environment. These short rests let security officers recover from fatigue but the debate remains over how long of a break would be enough. Levels of productivity and recovery from fatigue differ from person to person. This means that while a 10-minute break is enough for one operator, it might not be sufficient for another to recover from screen tiredness. Furthermore, the systems must not be left unattended during these breaks and security employees are subject to more frequent work rotations, which is not either cost or human resource effective for companies.
Apart from adjusting the working hours and break times, alarm monitoring companies also invest in false alert detection improvements. This is done by gaining a better understanding of false alerts through in-depth pattern-seeking studies. Based on the results, operators can then learn to more effectively distinguish between true and false alarms at speed. However, one major problem regarding these studies is that in absence of technology, they could eat up a lot of time. Thousands of security situations happen on a daily basis, meaning that new varieties of false alerts appear all the time. When AI technology is not an option for the security management systems, operators are left on their own to inspect and find the common grounds amid the sea of false alarms, which is draining work.
How Automated Decision Management Systems Can Help
Automated systems have been around for a while, however, the knowledge and expertise required to apply them into practice have always been an obstacle for companies when choosing them as a way to better operate. These systems are especially designed to be used conveniently by security operators, given that they receive appropriate training.
Situation intelligence and incidents are taken into consideration by the system in order to make automated decisions that are precise and timely. These functions help system operators efficiently monitor and filter out routine tasks, while paying strict attention to situations that appear to be abnormal. With their help, security personnel no longer have to spend the time and energy on as many screens, but instead, can better concentrate on responding to filtered alerts. Automated decision management systems also support operators by processing a large amount of incoming data to point out potential security breaches and suggest the possible responses to them. These systems can also be programmed and customized to distinguish between true and false alerts that are set by the organization, which in turn significantly reduces the workload on and alert ignorance seen in stressed security officers.
Regarding more complex uses, an automated system can collect and quantify data from a network of connected sensors and devices. It will then spot the more complicated situations by considering the possible relationships between various events from involved sensors and further classify them into individual meaningful incidents. When a security breach is found, the system will move on to alert its operators. Based on the pre-designed processes present in the organization, the systems can guide operators through the process of responding to a diverse range of breaches.
Overtime, the system gradually picks up and learns from false alerts. This is done by processing the footage and information accumulated from daily operations to find patterns of similar false alerts. In the future, should similar situations occur, the system will be able to make the decisions on the alarms themselves.
Automated decision making systems are the way to go for security companies because of many reasons. While assisting operators respond quickly to pre-designed scenarios, these systems can also work to increase security monitoring productivity. Automated systems themselves do not suffer from human operator fatigue, therefore they reduce the risks and errors in making timely security decisions.
As previously mentioned, the systems learn and improve directly from information collected from their day-to-day operations, and at the same time can suggest possible security situations, solutions based on video analytics. With the help from large storage devices and the cloud, these systems automatically store captured video footage, the analytics and newly designed scenarios to recall when a response is required. This advantage sure does outweigh the human operator’s memory.
Further Benefits of AI-powered Management Systems
Evidently, technologically advanced management systems at the moment have yet to entirely take the place of human operators, however, what they can offer are the high level of support, to reduce workload and operator fatigue. Apart from making a direct impact on the daily tasks of an operator, data collected on security situations and incidents from automated management systems can contribute to regular security reviews and improvements.
The insights provided by the systems may also come in handy for compliance audit reporting, problems indication and therefore recommend the different ways to help enhance security solutions. For example, among the data collected and processed by the system, a slow response time might show that there needs to be further investigation and perhaps more training could be helpful for security operators to increase speed. Another good example is that the system could process their collected data to present that certain response processes can be improved for security alerts.
Conclusion — Improve on the Security Operator Role and Enhance Monitoring Safety
In sum, it is clear that operator fatigue is a major health issue for security operators while being an obstacle to productivity for alarm monitoring businesses. It cannot be stressed enough that improvements should be made on the role of an operator in terms of working hours, environment, and their day-to-day tasks. Being overwhelmed and tired from unfavorable working conditions and stress is detrimental to the operators’ well-being in the long run and does not secure a stable career path for professionals. Other than that, decreased working effectiveness from fatigue allows more room for overlooked security breaches and alert ignorance.
In the process of improving both the security operator’s role and the team, high technological management systems should be perceived as a collaboration, instead of replacement. Better and heavily invested training, preparation courses help operators get on-board more confidently and efficiently alongside automated systems. With these elements present in the equation, the security team will stand well prepared to handle stressful, complex situations while remaining efficient and compliant to industry standards.
