In 2012, Saudi Aramco formed an Intelligent Systems team composed primarily of KAUST graduates to prototype robots for oil and gas operations. The team developed SAIR (Saudi Aramco Inspection Robot) in 18 months, a robot capable of visual and ultrasonic inspection of steel assets and gas sensing. SAIR is wirelessly operated, compact, and detects corrosion in hard-to-reach places. Why it matters: This highlights the critical role of KAUST in supplying talent for advanced technology development in Saudi Arabia, particularly in robotics for the energy sector.
KAUST and the Social Responsibility Association (SRA) are hosting their third annual AI hackathon at KAUST with 73 participants from across Saudi Arabia. The hackathon aims to deliver 14 social projects in technology and innovation across the tracks of social issues, housing, tourism, and education. KAUST supports the event to foster entrepreneurship and transform ideas into scalable solutions that serve society. Why it matters: The event highlights the growing focus on AI-driven solutions for social challenges within Saudi Arabia, aligning with Vision 2030's goals for digital entrepreneurship.
This paper introduces a novel fuzzy clustering method for circular time series based on a new dependence measure that considers circular arcs. The algorithm groups series generated from similar stochastic processes and demonstrates computational efficiency. The method is applied to time series of wind direction in Saudi Arabia, showcasing its practical potential.
KAUST and Saudi Aramco collaborated to develop a laser-based sensor for detecting trace amounts of gas leaks in petrochemical plants. The sensor uses machine learning to identify specific gases, differentiating it from previous sensors that only detect large leaks. The technology can differentiate between closely related industrial gases like benzene, toluene, ethyl benzene and xylene (BTEX). Why it matters: This innovation enables proactive monitoring and rapid pinpointing of leaks, enhancing safety, environmental protection, and operational efficiency in the petrochemical industry.
KAUST has signed an agreement with the Aviation Investigation Bureau (AIB). The agreement was signed between AIB Director General Abdulelah O. Felemban and KAUST Director of the Core Labs Justin Mynar. The partnership aims to foster collaboration between the two entities. Why it matters: This agreement could lead to advancements in aviation safety and investigation techniques through shared research and resources.
This paper proposes a smart dome model for mosques that uses AI to control dome movements based on weather conditions and overcrowding. The model utilizes Congested Scene Recognition Network (CSRNet) and fuzzy logic techniques in Python to determine when to open and close the domes to maintain fresh air and sunlight. The goal is to automatically manage dome operation based on real-time data, specifying the duration for which the domes should remain open each hour.