Safety in Energy, Oil & Gas Utilities: AI and Video Analytics


The oil sector is already making use of technology to maximize and optimize their revenues and efficiency.

Energy, oil, and gas are considered the most valued commodities across the globe. When the revenue in the sector increases the security risk, it also increases with cyber and physical attacks taking place in recent years. Unlike other industries, the energy, oil & gas sectors get a steady-state with the working system every time a security breach happens. Finally, video analytics combined with AI (Artificial Intelligence) is pushing hackers to the exit door with its extended technological influence.

A report shows that global energy valued at US$1.7 trillion, that is 2.2 percentage of GDP in 2016. Energy, oil, and gas are some of the most profitable industries as well as the most dangerous. The possibility of Artificial Intelligence discovered in the energy industry that is investing in the technology and other data related improvements intending to secure their future competitiveness in a fast-changing environment. The oil sector is already making use of technology to maximize and optimize their revenues and efficiency. AI applications like Machine Learning (ML), computer vision, chatbots, intelligent robots, virtual assistants are holding their features in the oil sector.

The major challenge faced by the industries in the recent year is that of physical and cybersecurity attacks. A survey by Siemens with the Ponemon Institute reveals that about 70 percent of oil and gas industries face security problems and about 42% of energy enterprises admitted being victims of phishing attacks as per PwC’s Global State of Information Security Survey conducted in 2016. The increase in the number of physical and cyberattacks and its security spending have made conglomerates to take technology as a back door solution as well as the energy sector is highly investing in security systems. Energy, oil & gas utilities are combined with AI and Video analytics into enterprise security to encrypt the system. With the help of video cameras as sensors, the security threats in the industries are monitoring all day.

With the help of AI and Machine Learning (ML) mechanism in the video surveillance, it increases the accuracy, clarity, speed, and performance of security detection. Industries use integrated real-time video analytics to monitor both physical and cybersecurity threats. Thermal, infrared, and night-vision cameras are used to keep track of the consistency of every access attempt to a facility, machine, or asset. Monitoring machinery failures, video analytics used to identify potential equipment, and process failures. Analyzing video with machine learning algorithms used by industries to make predictions for the future based on the past data available.


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