Pipeline Management

The Challenges of Deploying AI to the Edge

Article

Artificial intelligence (AI) is in the midst of rapid, seemingly exponential advancements. However, most of what is seen in the news and read in articles deals with the consumer side of the technology. While AI technology is also rapidly improving in industrial settings, some significant challenges remain, specifically in AI edge computing applications.

The issues presented by AI edge computing can be categorized into hardware limitations, software and algorithmic challenges, security and privacy concerns, and deployment and maintenance difficulties.

Ruggedized Edge Computing for Oil & Gas Exploration

Case Study

A natural gas company wanted to begin an exploration campaign. It would be monitored from their field base located at a current fracking site. From the base, they needed to supervise progress, run analytics and other operational software and perform maintenance procedures as needed for equipment. The team needed a ruggedized, powerful computer at the base that could withstand intense shock, vibrations, and extreme operating temperatures.

On their exploration campaign, they wanted to incorporate an edge computing system for asset management, data analysis, and crisis control operations. Due to the high cost of exploration, they wanted to predict maintenance measures and prevent prohibitive downtime periods. They also wanted to mitigate energy waste: they needed to measure and record energy consumption by machine assets to optimize the process. They requested a text notification system that delivers warnings and a remote trigger function to shut off processes not hardwired in. The system also needed to transition past the exploration phase to monitor pressure and flow of pipelines successfully constructed.

Reducing the Regulatory Burden with IIoT

Article

The U.S. has an estimated 200,000 miles of pipelines carrying hazardous gases and liquids. A leak in that network, or a system failure after a natural disaster, could have catastrophic consequences for the surrounding area, so pipelines are subject to a very tight regulatory regime. A dedicated agency, the Pipeline and Hazardous Materials Safety Administration (PHMSA), generates reports based on large amounts of data gathered from private operators.

IoT makes it possible to gather this data and forward it electronically to regulatory bodies such as PHMSA. With small, low-energy sensors, it is feasible to monitor pressure throughout the pipeline, making it easy to identify potential leaks. More complex systems, such as small robots that can be sent through the pipeline to detect even the tiniest breaches in pipe integrity, are currently in development.

C1D2 Computing for Thermal Energy Management

Case Study

Sealevel partners with a customer that specializes in the design and manufacture of heat tracing and leak detection equipment for industrial, commercial, and residential applications. The company’s main focuses are the petrochemical and oil & gas industries, but they make products for a wide array of commercial and residential heat tracing applications as well. Sealevel has designed and manufactured multiple generations of rugged touchscreens for the customer that meet the extreme requirements for hazardous location certification, IP protection, impact resistance, and wide operating temperature range.