10 Ways AI is Improving Remote Site Security

Bottom Line: Combining 24/7 video monitoring and AI-based techniques to analyze video streams in real-time provide greater contextual intelligence and predictive insights into potential threats than any other approach today.


Identifying patterns hidden in real-time video streams from remote sites using AI and machine learning proves effective in stopping onsite thefts of machinery and equipment and thwarting break-in attempts while also preventing vandalism. Getting remote site security right is essential for agriculture, construction, manufacturing, oil & gas, utilities, and critical infrastructure. Unfortunately, breach attempts on remote sites in each of these industries are increasing, as is equipment theft. According to the National Equipment Register, construction and remote site theft losses often exceed $1B a year. In addition, the latest model equipment, tools, and supplies are the most stolen and quickly resolved. Thus, the urgent need to improve remote site security becomes clear.

How AI Can Improve Remote Site Security


Combining all available data on a remote site's security status, from traditional access control systems to 24/7 video feeds from night vision, and thermal sensing cameras is the goal many companies are trying to achieve. Industries that rely heavily on remote sites want more contextual intelligence to help predict when a break-in, theft, or vandalism attempt will occur. Having AI and machine learning interpret real-time monitoring data from these various sources is proving successful at scale. AI and machine learning applications and techniques are supplementing the work security professionals are doing in monitoring centers. AI and machine learning deliver real-time contextual intelligence and insights to security professionals in monitoring centers that weren't available before, making them more effective at their work while protecting remote sites 24/7.


The following are 10 ways AI is improving remote site security today:


1. Getting a 360-degree view of remote site operations by combining 24/7 video feeds, sensors, and machine monitoring data AI algorithms use to build predictive models is revolutionizing remote site monitoring. It's proving invaluable to have a 24/7 stream of real-time video and sensor data available for modeling activity around the perimeter of and within a remote site. In addition, many remote sites rely on thermal and night vision cameras to capture a richer, more contextually relevant data stream AI can use to identify if there are any problems with machinery or potential threats to the site itself. Real-time monitoring using video and sensor data is revolutionizing remote site security, as the Twenty20 Solutions' dashboard below illustrates how comprehensive the 360-degree view of all remote site security is:

2. Automate the many checklists and manual workflows existing monitoring station team members use today by combining AI and Robotic Process Automation (RPA). Remote monitoring station teams can transition away from using manual checklists and screening procedures by adopting an AI-based monitoring system that interprets and can act on real-time video data if configured. In addition, many companies with remote sites integrate Robotic Process Automation (RPA) into their workflows to reduce the time it takes to create and send alerts, identify people and vehicles at remote locations, and avert false positives from animals and livestock.


3. Using AI to analyze the data from real-time video feeds and discover patterns in remote site activity not visible with conventional monitoring techniques delivers results. Using manual approaches to monitor remote sites misses many of the most valuable data that can predict threats ranging from burglary attempts, machinery thefts, or vandalism. Using AI to interpret and fine-tune predictive models using real-time video monitoring data catches what initially appear to be random events and looks to construct patterns from them.

4. AI can identify changes in activity levels, behaviors, patterns, and visits from people not expected at remote sites helping to avert burglaries, break-ins, and machinery thefts. It's possible to configure an AI platform designed to monitor remote sites so that once an abnormal or unexpected event is encountered, it automatically sends an Alert. Alerts can be configured to be sent directly to local law enforcement if the system detects an active burglary, break-in, or machinery theft incident.


5. Identifying machinery and processing equipment that needs preventative maintenance and repair based on elevated operating temperatures combined with real-time video analysis of their condition. Extending the life of assets and machinery at remote sites starts with real-time monitoring of their activity and condition. Combining video and sensors-based real-time data from remote sites' machinery, production, and plant engineering can quickly see if a given machine needs maintenance, repair, or overhaul (MRO). For example, thermal and night-vision monitoring cameras are adept at identifying when a given container, processing unit, or valve system is overheated or needs repairs. Identifying machinery and assets' conditions and averting their breaking down can pay for an AI-based remote monitoring system alone. For example, the following is an image from a remote sites’ thermal sensing security camera of a transformer that’s overheating and needs repair. A vital part of any remote site security effort is keeping machinery operating efficiently and safely over time.

An integral part of combining AI and remote site monitoring with real-time video feeds is identifying when machinery needs maintenance, repair, or overhaul (MRO).


6. Attain more accurate audit records of remote sites and keep them more in compliance and secure over the long-term by having 24/7 video streams to verify all activity. The more regulated the industry and its operations, the more critical it is to have real-time video and sensor data saved continuously from operations. For example, the cannabis industry requires 24/7 video recordings of farming locations as a compliance requirement for crop quality. The oil and gas industry’s regulatory compliance requirements include monitoring of remote sites for the security of machinery and process plant operations. Security has a compliance dimension that AI-based remote monitoring systems help provide real-time, accurate data for.

7. By relying on AI’s predictive analytics and modeling techniques to identify patterns of threats in, around, and between remote sites in real-time, it’s possible to assign threat scores to each remote location. One of the most valuable aspects of using AI for real-time remote site security is the opportunity to keep “learning” or fine-tuning mathematical models that are invaluable in predicting potential risks to remote sites. Creating AI-based models that can predict the most and least risky remote sites helps security teams define security strategies that can help calculate the aggregated risk scores each site receives based on the many factors AI-based scoring algorithms consider. The following is an example of how AI learns of which sites and the most and least risky using unsupervised and supervised machine learning techniques, which are foundational to AI.



8. Reduce unauthorized access to remote sites by integrating AI and remote access systems on the same platform. Stealing access credentials, including badges, access codes, and in some cases, smartphones with specialized apps on them to grant access to secure remote sites, is a favorite tactic of criminals looking to steal equipment. Organized crime relies on criminals willing to steal access credentials to access a network of remote sites so machinery can be stolen and resold. One of the best ways to stop this level of sophisticated theft is to have the card and access control systems integrated with AI-based real-time video analysis to identify every person attempting to enter the remote site positively. There needs to be a match between the person using the credential and the identity of the credential. If there isn’t, access is denied. This is proving very effective in securing remote agricultural, manufacturing, and oil & gas sites globally.


9. Ransomware attacks threaten to damage remote sites while taking a company's IT systems down simultaneously, making an integrated AI-based remote monitoring system essential. Criminals, cybercrime groups, and organized crime are ramping up their efforts to use ransomware while threatening to damage or even destroy remote sites businesses rely on for operations. With cybercrime increasing today, every company with remote sites needs to start thinking of combining on-the-ground intelligence with cyber threats to mitigate combined threats.


10. Identify the company and third party service providers’ vehicles and people onsite in real-time, granting access privileges to only the areas they need access to get work done. Identifying vehicles is foundational to ensuring site security. Using AI to differentiate between company vehicles, third-party service providers, and unknown vehicles is essential to protect any remote site. For example, the following figure from Twenty20 Solutions AI-based real-time video monitoring of a remote site parking lot with fleet vehicles stored in the background shows how machine learning scores every object in the frame. Knowing the identity of every vehicle is essential for ensuring remote site security.

Twenty20Solutions combines AI and machine learning techniques on a single platform to identify and classify every object in the above video frame, ensuring the security of remote sites and the assets stored there.



Conclusion

Strengthening the existing approach to protecting remote sites with AI and machine learning provides contextually rich, relevant, and real-time insights security professionals need to secure remote locations. Improving remote site security starts with real-time monitoring that provides 24/7 visibility into all activity. It is often the nuanced events and patterns of criminals/behaviors that AI-based systems identify and alert security teams, and in some instances, law enforcement. Protecting and preserving assets and machinery is imperative, and combining real-time video monitoring with intelligent sensors is actively protecting remote sites today. The entire spectrum of risks needs to be taken into account and each area of potential attack needs to be considered a threat vector that needs to be protected.