FogHorn, a developer of Edge AI software for industrial and commercial Internet of Things (IoT) solutions, announced that Aramco, an energy and chemicals company, has deployed edge-powered computer vision solutions built on the FogHorn Lightning Edge AI platform at multiple sites.
This is designed to enhance safety, provide proactive monitoring for equipment failure, and enable automation of drilling equipment and processes. Aramco selected the FogHorn Lightning Edge AI Platform to build an efficient infrastructure for future automation, digitalisation, and standardisation projects across various facilities.
Video cameras are powerful sensors that observe a multitude of processes and can be leveraged to improve operations, production, and worker safety by providing insights that other sensors and control data do not capture. However, edge computing is required to cost-effectively process and infer data from these types of high-bandwidth sensors, especially in remote areas where little to no connectivity is available, such as oil and gas facilities.
The FogHorn Lightning Edge AI platform addresses these challenges by embedding intelligence locally, at or near the source of streaming sensor, video and control data, providing unprecedented low latency for onsite image processing and analysis.
While video cameras were previously used to acquire images and videos, edge computing makes it possible for them to be “conscious” and “intelligent”, and play a critical role in automation, digitalisation and remote management of operations.
Nabil Al Nuaim, Aramco’s chief digital officer, says, “Technologies like these help us to reach a successful digital transformation for Aramco and the regions it operates in.” He adds that “Aramco’s investments in this field aim to increase accessibility of new digital technologies and create awareness of the benefits these novel technologies can have in areas such as health, safety, security and the environment. A perfect example of this is how FogHorn’s software could help strengthen Aramco’s leadership in flare minimisation.”
“Camera-based edge analytics enables automation of remote energy facilities and support our IoT edge infrastructure. Edge analytics streamline operations and provide staff with mission critical information to make time-sensitive decisions,” comments Mahdi Adel, CEO of Aramco Ventures.
“The Lightning Edge AI Platform facilitates the integration of new sensors and collects, validates, and enriches sensor data to identify patterns and create models that predict and mitigate problems, leading to more efficient operations. Our FogHorn-powered solutions enable real-time responses and help optimise production and safety at our facilities.”
Aramco utilised the Lightning Edge AI platform to develop and deploy effective camera-based monitoring solutions across multiple plant and rig locations to increase operational safety and efficiency, particularly in the following use cases:
Remote drilling rig inspection
Well control incidents are complex and Aramco wanted to implement an effective, automated solution that could respond immediately. The company deployed a camera-based system, powered by FogHorn streaming video analytics, allowing workers to monitor blowout preventer (BOP) activity via a dashboard and effectively shut down operation during a well control incident immediately, compared to manual “spacing out”. Automating these activities significantly reduces operational, safety, and environmental risks during drilling rig operations.
This technology was conceived as a proof-of-concept for the Drilling at the Edge (DATE) program in Aramco’s Exploration and Petroleum Engineering Centre Advanced Research Centre (EXPEC ARC). DATE is a major technology initiative that coordinates people, algorithms, data, machines, and processes on a drilling rig (i.e., at the edge) around real-time information, to accelerate decision making and optimise operations.
On-site safety compliance
Aramco implemented a new automated surveillance system, named the “IR 4.0 Safety Eye”, using digital image processing, powered by the FogHorn Lightning edge analytics platform, to provide safety monitoring in real time. The computer vision solution streams live closed-circuit video from standard surveillance cameras through AI software, which detects fixed and moving personnel and assets, and generates automatic alerts via email or text when a hazard or non-compliance is detected.
Emissions monitoring for environmental compliance
Aramco actively monitors its flare stacks to help reduce negative environmental impact. With the help of FogHorn edge-enabled video analytics, Aramco can enable intelligent monitoring of flare stacks in real time, powered by AI and deep learning techniques. Aramco’s FogHorn-powered machine vision solution provides valuable insights that can be used for flare gas recovery systems to minimise flaring and the resulting emissions.
“Energy organisations must embrace digital solutions as their businesses expand. Innovative technologies such as edge computing and video analytics solutions reduce operational costs and help companies keep up with growing industry demands while avoiding major incidents along the way,” says Sastry Malladi, CTO at FogHorn. “By pairing the clear comprehensibility of video streams with intelligent analytics, video becomes a powerful sensor that Aramco has leveraged to significantly improve business operations, production, safety, and efficiency.”
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