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Enhance control rooms with surveillance and intelligence

Mines are typically focused on a core product, such as gold, diamonds, platinum, copper or other minerals. The extraction and production process typically involves a large area of mining, as well as processing and refining facilities that need to be protected. The focus on security typically intensifies; the value of the material increases as one gets to the finished product, with high-risk areas having the major security provisions.

Simply put, stealing finished or near-finished products has the most impact on profitability. However, criminals are prepared to go down the value chains to get anything they can, so security needs to be applied throughout the process. Mines also represent opportunities for theft of a whole range of equipment, facilities, fuel, and infrastructure components such as cables, IT resources, tools, electrical equipment, vehicles, and even scrap that can impact profitability and operational capacity.

I have made the point in a previous article on why situational awareness of operators is so important to CCTV detection (www.securitysa.com/19326r). Even so, the sheer size of mines, the dispersion of assets, and the diversity of targets that can get stolen make mining environments one of the most difficult places to do CCTV surveillance.

How well CCTV can perform in detecting the most critical threats is a combination of risk analysis, experience, and, most importantly, information or, specifically, intelligence. Intelligence and investigation information are important in directing surveillance resources to the most critical hotspots, people, and targets. By combing assessed risk from certain people or vehicles, and relating this to potential high-risk target areas at certain times or locations, the ability to detect and apprehend suspects increases dramatically.

Combining information and surveillance

In the early days of CCTV implementation, investigation departments where one of the main lines of pursuing and convicting suspects. They were exclusive, and sometimes reluctant to share any information with anyone. This often led to CCTV gathering of information being a one-way street, with operators not even knowing the outcomes of incident information they passed on. This balance was partly addressed by having specialised surveillance functions, sometimes referred to as third tier, which is targeted, focused or dedicated surveillance, where investigations worked more closely with CCTV operator personnel to share and mutually gather intelligence to aid in detection and conviction.

The model worked and continues to work well, but there has been an increasing general recognition that intelligence needs to be shared more widely with smart surveillance contributing, and local and big data systems providing clues for operators to focus on as part of their normal daily duties.

Increasingly, we are seeing the combination of intelligence with smart surveillance and traditional CCTV functions in order to pick up potential threats in a series of zones around and within the mine as soon as possible during the incident cycle. The more sources of information and the more widely spread they are, the better the prediction of events, incidents, and surveillance targets can be established. This requires greater quality of CCTV around high-risk surveillance points, as well as an understanding of crime tactics and techniques to look out for combined with an awareness of vehicles and vehicle movement; also of people of interest internally and externally.

For example, a person being dropped off by a car on a mine perimeter should be briefly checked if it is in an unusual area, but a known suspect getting dropped off on a public road from a car linked to previous crime incidents, near a sensitive section of the perimeter, would immediately create a critical viewing alert for operators. Similarly, cars stopping, or people being dropped off, in areas where there is typically little activity would also be an alert.

These kinds of notifications are becoming increasingly possible with integrated analytics capabilities and AI, although the current status of systems still seems well below potential. With technology like drones and links to surrounding camera sources, this information can be increasingly picked up from zones wider and further away from the central risk area, resulting in improved forewarning, threat analysis, and response preparation.

Pattern variations like unusual movements, concentrations of people, closeness to risk areas at unusual times, direction of movement, unusual postures, carrying objects, etc., are all aspects that should be responded to. The widespread nature of mining operations means that not only is early detection important, but the extent of a timeous response and capacity for extended pursuit also comes into play, and the more prepared security can be to deal with this kind of issue, the better.

Information confidentiality

One of the issues in the distribution and sharing of information has always been, how the confidentiality of information can be secured. Investigators are very reluctant to give information away if it leads to people of interest becoming aware they are on investigation lists. Similarly, intelligence information that gets divulged may end up changing suspects’ behaviour or tactics around weaknesses in detection systems. Ideally, one would hope all such information to be strictly confidential.

Criminal syndicates have a strong thrust to infiltrate control room personnel across many, if not all, mining operations. This can lead to information being leaked. This is not necessarily all bad, and knowing they are being looked at does have possible disruptive effects on syndicates and their members. It is likely to interrupt their activities as people avoid showing suspect behaviour or suspend crime operations for a while. Indeed, sudden changes in behaviour may confirm suspicions about targeted people.

Syndicates may also feel the need to cycle through other people or vehicles to maintain a presence, and this use of more people may also set off warning indicators. It also potentially enlarges the group being looked at, and the connections could facilitate further investigations. The company can also release deliberately misleading information to disrupt syndicates as long as it does not impact innocent people.

Smart surveillance technology and the use of big data in combination with conventional CCTV control room strategies increase the potential for security service delivery. This is not only for increased detection opportunities, but also for confirmation and verification of alarms and operator observations. This means that operators can work more smartly and adapt more easily to criminal strategies, even in such a spread-out mining environment.

Given the need for confidentiality of certain key investigation or intelligence information, access to information does need to be protected to allow access to only certain CCTV functions, such as specialists or third-tier parties. These would be selected personnel who would work closely with investigations to help target people of interest or to review particular combinations of people and areas of high risk. Nevertheless, there is extensive information that can be used in the day-to-day control room operations to assist in viewing strategies and enhance operator performance.

Dr Craig Donald.

Dr Craig Donald is a human factors specialist in security and CCTV. He is a director of Leaderware, which provides instruments for the selection of CCTV operators, X-ray screeners and other security personnel in major operations around the world. He also runs CCTV Surveillance Skills and Body Language, and Advanced Surveillance Body Language courses for CCTV operators, supervisors and managers internationally, and consults on CCTV management. He can be contacted on +27 11 787 7811 or [email protected]

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