KAUST's Fuel Lubricants Efficient Engine Technology (FLEET) Consortium, established with OSP last year, added Luberef and Ferrari as new members. FLEET has completed six projects in its first year, including studying liquid spray and combustion, developing fuel cells, and capturing energy from ship engines. Eight new projects have been announced, including lubricant exploration for electric and hydrogen vehicles and improving hydrogen engine performance. Why it matters: The expansion of FLEET and its new projects underscore Saudi Arabia's commitment to carbon neutrality through collaborative research and development in sustainable transportation technologies.
ADNOC, TII, and ASPIRE have launched a pilot project to integrate autonomous drone fleets for emergency response. The system will provide ADNOC's Crisis Management Center with real-time aerial intelligence during emergencies, integrating autonomous, long-range, and swarm-based drone operations. Fleets of drones can be rapidly deployed to scan large areas, search for people, and offer support. Why it matters: This partnership demonstrates Abu Dhabi's commitment to using advanced autonomy to protect people and critical infrastructure, potentially transforming emergency response across the UAE.
The paper introduces a novel method for short-term, high-resolution traffic prediction, modeling it as a matrix completion problem solved via block-coordinate descent. An ensemble learning approach is used to capture periodic patterns and reduce training error. The method is validated using both simulated and real-world traffic data from Abu Dhabi, demonstrating superior performance compared to other algorithms.
KAUST, Intel, and Brightskies have launched REDD, a collaborative self-driving mobility platform, converting a conventional car into a self-driving vehicle with integrated AI software. Brightskies developed the self-driving system, powered by Intel® NUC platforms, utilizing their BrightDrive system. KAUST researchers will use the vehicle to test new techniques, leveraging real-world data to improve self-driving technologies. Why it matters: This partnership advances autonomous vehicle research in Saudi Arabia, aligning with the Kingdom's Vision 2030 by creating a platform for innovation and testing in a real-world environment.
This paper presents a decentralized multi-agent unmanned aerial system designed for search, pickup, and relocation of objects. The system integrates multi-agent aerial exploration, object detection/tracking, and aerial gripping. The decentralized system uses global state estimation, reactive collision avoidance, and sweep planning for exploration. Why it matters: The system's successful deployment in demonstrations and competitions like MBZIRC highlights the potential of integrated robotic solutions for complex tasks such as search and rescue in the region.
Marcus Engsig at DERC has developed DomiRank, a new centrality metric to quantify the dominance of nodes within networks. DomiRank integrates local and global topological information to determine the importance of each node for network stability. The research demonstrates that nodes with high DomiRank values indicate vulnerable areas heavily dependent on dominant nodes. Why it matters: This metric can help identify critical infrastructure components and vulnerabilities in complex systems, enhancing resilience against targeted attacks.
ARRC researchers in collaboration with the University of Bologna and ETH Zürich have developed a CNN-based AI deck to enable autonomous navigation of a 27g nano-drone in unknown environments. The CNN allows the drone to recognize and avoid obstacles using only an onboard camera, running 10x faster and using 10x less memory than previous versions. The demo also featured a swarm of nano-drones flying in formation using ultra-wideband communication. Why it matters: This advancement could significantly enhance the capabilities of nano-drones for applications such as disaster response, where quick and efficient intervention is crucial.
KAUST researchers led by Dr. Muhammad Hussain have developed a flexible, transparent silicon-on-polymer based FinFET inspired by the folded architecture of the human brain's cortex. The team created a 3D FinFET on a flexible platform without compromising integration density or performance. They aim to demonstrate a fully flexible silicon-based computer by the end of the year. Why it matters: This research could lead to the development of ultra-mobile, foldable computers and integrated circuits, advancing the field of flexible electronics in the region.