Artificial Intelligence Aims To Save Lives on Marine Vessels
The introduction of artificial intelligence (AI) cameras on marine vessels is planned to embrace a smarter automated analytic response and reporting culture, which, in turn, is expected to lead to increased safety oversight of critical offshore operations in areas that have been determined to have a lack of physical safety coverage.
Digital transformation is changing every aspects of life. Not far behind other industries, the oil and gas industry’s adoption of digital transformation is evolving in almost every domain. The Abu Dhabi National Oil Company (ADNOC) is using digital technology initiatives across the value chain, including in the health, safety, and environment (HSE) domain. The introduction of artificial intelligence (AI) cameras on marine vessels is planned to embrace a smarter automated analytic response and reporting culture, which, in turn, is expected to lead to increased safety oversight of critical offshore operations in areas that have been determined to have a lack of physical safety coverage.
New computing power, AI, and smart sensors have shifted operating models to a new data-driven decision-making approach. This is expected to lead operators to move forward with adopting technologies, enabling the industrial internet of things and analytics-based awareness to improve operations, reduce risk, and increase safety in near real time. Augmented/virtual reality, surveillance drones, and smart cameras are now economical and viable technologies to reduce HSE risks. Operators now can integrate or cross use these technologies with wearable devices to alert personnel at each point remotely.
The HSE AI assistant is another evolving initiative in the industry. The automation of data retrieval from data repositories or centralized data lakes, and a proper risk-assessment process, could significantly improve and simplify the work of specialists working remotely. This evolving initiative also helps develop models to assist in the examination of various event scenarios and predict and mitigate emergencies, thus reducing the need for human supervision. A growing number of environmental protection initiatives use AI agents and machine learning models, which prove to be more effective in executing routine tasks faster and with higher accuracy. These initiatives’ most-pressing environmental issues are climate change, biodiversity issues, healthy oceans, discharges to water, waste generation, water security, emissions to air, weather, and disaster resilience.
AI and machine learning are playing important role in solving engineering problems. With the advent of AI technology, therefore, many common business processes have been automated, thus enabling personnel to increase their focus on more-important tasks while technologies such as the AI system can handle many of the time-consuming oversight tasks. Machine learning can help find solutions to problems in vision, speech, and robotics. The machine-learning algorithms naturally are starving for data for their training data sets. Data for these sets is divided into labeled categories. For example, an image of a helmet is labelled as “helmet” or “yellow helmet.” Data can come in a structured or unstructured form, timestamped or in real time, or as semistructured data. This paper focuses on unstructured data sourced from video streams and images.
The ultimate business objectives of the HSE and AI initiative are
- Save lives and identify and eliminate potential risks
- Empower vessel captains to be able to identify and respond to violators immediately
- Improve the HSE culture of the vessel crew
- Generate live HSE data analytics automatically
- Get more insights with the aim of improving safety in operations