This paper proposes a smart dome system for mosques that uses machine learning to automatically control dome ventilation based on weather conditions and outside temperatures. The system was tested on the Prophet Mosque in Saudi Arabia using K-Nearest Neighbors and Decision Tree algorithms. The Decision Tree algorithm achieved a higher accuracy of 98% compared to 95% for the k-NN algorithm.
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.
KAUST researchers have developed a dual-use wireless sensor system that monitors both traffic congestion and flood incidents in cities. The system combines ultrasonic range finders and infrared thermal sensors to provide real-time, accurate data on traffic flow and roadway flooding. Data is sent to central servers and assimilated with satellite data to form real-time maps and forecasts. Why it matters: This technology can provide up-to-the-minute warnings for flash floods and traffic, enabling rapid emergency response and potentially saving lives in urban environments.
KAUST has developed AirGo, a hybrid air quality monitoring system using mobile and stationary sensors. The system measures gases (carbon dioxide, carbon monoxide, sulfur dioxide, ozone, etc.) and particulate matter, providing real-time environmental data. AirGo is at technology readiness level 6 and is being scaled up for broader use through partnerships with manufacturers. Why it matters: This technology directly supports Saudi Vision 2030's environmental sustainability goals and the development of smart cities by providing granular air quality insights.
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.
AI technology presents significant opportunities to enhance home safety and security across Saudi Arabia. Potential applications include intelligent surveillance systems, predictive analytics for detecting anomalies, and automated emergency response mechanisms. These solutions aim to provide comprehensive protection for residents against various threats, including intrusions, fires, and other domestic hazards. Why it matters: This highlights Saudi Arabia's proactive approach to adopting advanced AI solutions to improve the quality of life and enhance public safety within its residential communities.
KAUST researchers in the Sensors Lab are developing neuromorphic circuits for vision sensors, drawing inspiration from the human eye. They created flexible photoreceptors using hybrid perovskite materials, with capacitance tunable by light stimulation, mimicking the human retina. The team collaborates with experts in image characterization and brain pattern recognition to connect the 'eye' to the 'brain' for object identification. Why it matters: This biomimetic approach promises advancements in AI, machine learning, and smart city development within the region.
KAUST and the Al-Madinah Region Development Authority (MDA) signed an MoU to enhance efficiency, resiliency, and safety in Al-Madinah. KAUST will share high-resolution climate change projections and assess soil loss dynamics. The collaboration aims to tackle challenges in the environmental and water sectors through research, development, and training. Why it matters: This partnership showcases KAUST's role in translating research into practical smart city solutions for regional development, addressing critical environmental concerns.