KAUST researchers developed a low-cost, AI-powered drone system to recognize and track camels, addressing challenges faced by local herders. The system uses commercial drones, cameras, and machine learning to monitor camel herds in real time without expensive GPS collars. The AI model revealed insights into camel migration patterns, showing coordinated grazing and sensitivity to drone sounds. Why it matters: This system offers an affordable solution to preserve Saudi Arabia's camel herding tradition while providing valuable insights into camel behavior and contributing to the local economy.
KAUST Beacon Development is assisting NEOM in understanding and protecting marine megafauna in the Red Sea, utilizing AI to process drone footage of habitats. Researchers are surveying areas around Sindalah to study the distribution of species like dolphins, turtles, and dugongs. This data will help reduce risks to marine life from vessel traffic and human activities. Why it matters: The partnership showcases the use of AI and drone technology for marine conservation in the region, setting a benchmark for similar efforts and highlighting NEOM's commitment to sustainable ecosystem management.
KAUST researchers are using AI to analyze satellite imagery for the automated detection of ancient stone structures in northwest Saudi Arabia, including mustatils (rectangular structures dating to the late 6th millennium BCE) and ruins in circular and triangular shapes. They developed a deep learning algorithm trained on manually identified datasets to isolate similar features over a wide area. The tool converts detected pixels into geodetic coordinates using GPS, assembling them into an online map and database. Why it matters: This project exemplifies computational archaeology, speeding up archaeological discoveries, promoting cultural heritage, and providing a methodology useful to other sectors of the economy.
Saudi startup Firnas Aero, founded in 2018, offers drone-based inspection services targeting aviation, security, industrial, and delivery sectors. The company develops its own drones and AI-equipped software for faster and more accurate inspections than manual methods. Their solution involves drones capturing high-resolution images analyzed by AI to pinpoint issues, enhancing speed and accuracy. Why it matters: This showcases Saudi Arabia's growing entrepreneurial interest in drone technology and AI-powered solutions for industrial applications, potentially improving efficiency and safety across sectors.
Researchers in Saudi Arabia are applying computer vision techniques to reduce Camel-Vehicle Collisions (CVCs). They tested object detection models including CenterNet, EfficientDet, Faster R-CNN, SSD, and YOLOv8 on the task, finding YOLOv8 to be the most accurate and efficient. Future work will focus on developing a system to improve road safety in rural areas.