A proposed recognition system aims to identify missing persons, deceased individuals, and lost objects during the Hajj and Umrah pilgrimages in Saudi Arabia. The system intends to leverage facial recognition and object identification to manage the large crowds expected in the coming decade, estimated to reach 20 million pilgrims. It will be integrated into the CrowdSensing system for crowd estimation, management, and safety.
KAUST has launched the KAUST Challenge: Ideas and Solutions for Hajj & Umrah 2020, in partnership with The Makkah Cultural Forum. The challenge aims to catalyze research, innovation, and economic development in Saudi Arabia. The KAUST Challenge will award 1 million SAR in cash and other prizes for ideas to improve the Hajj and Umrah experience and advance efforts to make Makkah a smart city. Why it matters: This initiative connects AI innovation directly to Saudi Arabia's Vision 2030 and the specific needs of religious tourism, a unique application area.
KAUST and Umm Al-Qura University (UQU) have signed a memorandum of understanding (MoU) to collaborate in education, training, scientific research, and professional development. The MoU includes developing joint training programs, updating curricula, providing consultancy, and organizing workshops. The partnership aims to support academic and technological advancement, enhance national talent, and align with Saudi Vision 2030. Why it matters: This collaboration strengthens Saudi Arabia's knowledge-based economy by integrating KAUST's research environment with another major university.
A research paper proposes a smart waste management system called TUHR for Makkah, Saudi Arabia, leveraging IoT and AI to handle waste accumulation during the annual pilgrimage. The system uses ultrasonic sensors to monitor waste levels and gas detectors to identify harmful substances, alerting authorities when containers are full or hazards are detected. The proposed system aligns with Saudi Vision 2030 by promoting sustainability and improving public health through optimized waste management.