The oil sector is already engaged in availing technology to maximize and optimize their efficiency and revenues.
Energy, Oil and gas wealth is considered as one of the most valued commodities across the globe. As the revenue in the sector spikes, the security risks it faces also increases with more cyber and physical attacks taking place in the recent years. Unlike other industries, energy, oil & gas sector get a big bang on its whole working system every time a security breach happens. Ultimately, video analytics combined with artificial intelligence (AI) is shoving hackers the exit door with its extended technological influence.
According to a report, global energy was valued at US$1.7 trillion, which is a 2.2% of the global GDP in 2016. Oil and gas industry is one of the most lucrative industries; it’s also one of the most dangerous. The potential of AI is already being discovered in the energy industry, which is investing majorly in the technology and other data related improvements with a goal to secure their future competitiveness in a fast-changing environment. The oil sector is already engaged in availing technology to maximize and optimize their efficiency and revenues. Artificial intelligence applications like computer vision, machine learning, chatbots, intelligent robots, virtual assistant, etc. are leveraging its features in the oil sector.
However above all these, the major challenge that the industry faces in recent years is physical and cyber security attacks. A survey from Siemens with the Ponemon Institute reveals that nearly 70% of oil and gas organizations have endured security compromises. PwC’s Global State of Information Security Survey conducted in 2016 unraveled that 42% of energy enterprises admitted being victims of phishing attacks. Henceforth, the energy sector is highly investing in security systems. According to a study by Frost & Sullivan, the total oil and gas infrastructure security market was estimated at US$31 billion in 2011 and is anticipated to grow to US$31 billion by 2021. The increase in the number of physical and cyberattacks and its security spending have made conglomerates to take technology as a back door solution. Energy, oil & gas utilities’ are integrating AI and video analytics into their enterprise’s security to encrypt the working system. Using video cameras as sensors, the security threats in the utilities’ are being monitored 24/7. When it is combined with software, the utilities’ get secured to every endpoint.
Use cases of video analytics in Energy, Oil & Gas Utilities
The job of securing facilities involved in the production of oil and gas encompasses vast geographic areas and features a steady stream of people and vehicles throughout the year. The volatility of the product these companies produce and the potential economic impact if something goes wrong demonstrates the high stakes involved with securing such facilities. To help organizations mitigate myriad threats, security managers depend on advanced video surveillance to provide real-time situational awareness. By availing AI and machine learning mechanism in the video surveillance, it increases the accuracy, clarity, speed and performance of security detection. Utilities’ use integrated real-time video analytics to monitor both physical and cybersecurity threats.
Thermal, infrared and night-vision camera: Thermal, infrared and night-vision cameras are installed at the utilities to keep track of the consistency of every access attempt to a facility, machine, or asset. The security team will get alerts on any kind of breach, vandalism, or threat within seconds. The alerts are also sent to administrators if the breach is to the physical asset. The threat surface or the unit can be jeopardized from access to stop the damage.
Monitoring machinery failures: Machinery failures are common in a mechanized environment. However, the cost and time it takes to rectify and reinstall the machinery is a lengthy process that cripples the normal functionalities. Utilities are using video analytics to identify potential equipment and process failures, which could be just as devastating as a security incident. The video analytics also keeps track of the machinery conditions even before it stops functioning.
Analysing video with machine learning algorithms: Industries are availing AI and machine learning to make predictions for the future based on the past data available. The same is applicable for energy, oil & gas utilities’. Analyzing raw video feeds and events they have captured using unstructured machine learning algorithms can help create an entirely new mathematical models that assess risk, site stability and machinery reliability.