KAUST is developing wearable sensors to monitor athletes' physiological responses, aiming to enhance performance and prevent injuries, aligning with Saudi Vision 2030. In partnership with a global motor racing team, KAUST is using electrochemical sensors to monitor drivers’ hydration and stress markers, enabling customized interventions. KAUST's wearable technology could continuously observe physiological parameters during training and in competition, helping coaches predict injuries and optimize training. Why it matters: These advancements in sensor technology and data analysis position KAUST as a key player in sports training innovation and could significantly impact athletic performance and healthcare in the region.
KAUST Academy has launched a summer training program called "Artificial Intelligence in Sports" in partnership with Vista Equity Partners and Stats Perform. The program included 20 intensive sessions of lectures, labs, and competitions for students with Python and ML knowledge. Participants used real data from football competitions including the Saudi Pro League. Why it matters: This program supports Saudi Arabia's Vision 2030 by investing in local talent and linking academic knowledge with real-world applications, particularly in preparation for hosting the 2034 FIFA World Cup.
KAUST is developing high-performance sensors for Saudi athletes, showcased at the Saudi Sports Sensors Workshop 2025. Olympian Rakan Alireza is collaborating with KAUST to utilize sensor technology in his training for the 2026 Winter Olympics. The workshop, co-chaired by KAUST Professor Dana Alsulaiman, aimed to foster collaboration between researchers and the sports community to advance sports science in Saudi Arabia. Why it matters: This initiative aligns with Saudi Vision 2030 by promoting sports innovation, localizing technology, and improving national health and athletic performance.
KAUST Ph.D. student Mousa Alharthi studies membrane desalination technologies and is also a cycling enthusiast. Alharthi translated Arabic language advertisements for cycling races in Jeddah for his English-speaking colleagues in the Red Sea Cyclists group. The Saudi Cycling Federation began holding amateur events in the Kingdom in 2017 to develop young Saudi talent and generate awareness about cycling. Why it matters: This highlights KAUST's role in supporting not only scientific research but also promoting sports and healthy lifestyles in line with Saudi Vision 2030.
This paper explores the use of deep learning for anomaly detection in sports facilities, with the goal of optimizing energy management. The researchers propose a method using Deep Feedforward Neural Networks (DFNN) and threshold estimation techniques to identify anomalies and reduce false alarms. They tested their approach on an aquatic center dataset at Qatar University, achieving 94.33% accuracy and 92.92% F1-score. Why it matters: The research demonstrates the potential of AI to improve energy efficiency and operational effectiveness in sports facilities within the GCC region.