Data & Analytics
This paper presents a robot integrated with a microcontroller that provides multiple functions to help with data logging, analysis, and reporting to identify hazards and improve safety protocols.
Aurora Innovation and Detmar Logistics have inked a deal for 30 autonomous trucks that will begin hauling sand in the region next year.
Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows, where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.
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Artificial intelligence systems can be trained to recognize visual content in drawings and provide a simplified context. The complete paper highlights the use of AI to process a scanned drawing and redrawing it on a digital platform. -
Artificial intelligence is already part of the work done in an office near you, and, before you know it, it will be in your office as well. Gaining familiarity and an understanding of it will serve you well.
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Time-stamped data anomalies can lead to more-accurate identification and faster diagnosis.
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The A-frame is DNV certified. TechnipFMC’s ROVs will deploy in GoM later this year.
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As the world’s top oil producers prepared for a weeklong meeting in April to plan a response to slumping prices of crude, espionage hackers commenced a sophisticated spearphishing campaign that was concentrated on US-based energy companies.
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"Sooner or later, we will get machines that are at least as intelligent as humans are," says Christof Koch, chief scientist and president of the Allen Institute for Brain Science in Seattle, Washington.
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As can be common in many technical fields, the landscape of specialized roles is evolving quickly. With more people learning at least a little machine learning, this could eventually become a common skill set for every software engineer.
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To keep pace with the digital age, the critical infrastructure and automation industries are looking beyond today’s control systems for new, common technologies to help balance requirements for uptime with digital technologies. Open standards can help.
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This paper describes an automated work flow that uses sensor data and machine-learning (ML) algorithms to predict and identify root causes of impending and unplanned shutdown events and provide actionable insights.
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Increasing accuracy in models is often obtained through the first steps of data transformations. This guide explains the difference between the key feature-scaling methods of standardization and normalization and demonstrates when and how to apply each approach.
