The KAUST Smart Home has received LEED Platinum certification, ranking second globally with a score of 94. The project retrofitted an existing home with features like 120 solar panels and hydropanels producing drinking water from atmospheric humidity. It also includes a leak detection system and smart fill windows controllable via touch panel. Why it matters: This demonstrates how existing infrastructures in the region can be improved to meet sustainability goals using smart technology.
Khaled Alrashed, president and CEO of Saudi Electricity Company for Projects Development, discussed the challenges of future smart cities at a KAUST event. He emphasized the importance of smart grids, AI, and large-scale optimization for improving urban living. The Saudi Electricity Company is partnering with KAUST, including using the Shaheen supercomputer, to develop these technologies and predict grid load. Why it matters: This collaboration highlights Saudi Arabia's ambition to become a leader in smart city technology and renewable energy, leveraging local expertise and resources.
Cybersecurity specialist James Lyne spoke at KAUST's 2018 Winter Enrichment Program (WEP) about cybersecurity threats and techniques. Lyne demonstrated hacking and phishing attacks, emphasizing how hackers can exploit personal information by bypassing basic security measures. He highlighted the increasing sophistication of cybercriminals and the existence of illicit marketplaces on the dark web where hacking applications are sold. Why it matters: Raising awareness of cybersecurity threats is crucial for protecting individuals and organizations in Saudi Arabia and the broader region as digital infrastructure expands.
MBZUAI Professor Fakherddine Karray is developing deep learning algorithms for human activity recognition to monitor the health and safety of elderly people. The AI tools analyze movement, posture, and facial expressions to detect early warning signs of health emergencies. Remote patient monitoring systems integrate smart devices and secure communication to allow elderly patients to stay at home and communicate with healthcare providers. Why it matters: AI-powered smart homes can provide affordable healthcare solutions for the rapidly growing elderly population in the region and worldwide.
KAUST hosted the "Human-Machine Networks and Intelligent Infrastructures" conference, co-organized by Prof. Jeff Shamma and Asst. Prof. Meriem Laleg. The conference explored the blend of engineered devices and human elements in large-scale systems like smart grids. Keynote speaker Dr. Pramod Khargonekar discussed cyber-physical-social systems and emerging trends. Why it matters: The conference highlights the growing importance of understanding the interplay between AI, infrastructure, and human behavior in the development of smart cities and intelligent systems in the region.
MBZUAI researchers are applying federated learning to optimize smart grids while protecting user data privacy. This approach leverages techniques from smart healthcare systems to enhance energy efficiency and local energy sharing. The research addresses the challenge of balancing grid optimization with the risk of user identity theft associated with traditional data-intensive smart grids. Why it matters: This research demonstrates a practical application of privacy-preserving AI in critical infrastructure, addressing key concerns around data security and fostering trust in smart grid technologies.
Siemens CTO Rainer Speh spoke at KAUST about smart cities, noting that urban populations are growing, especially in cities like Riyadh and Jeddah. Cities consume two-thirds of the world's energy and generate 70% of CO2 emissions. Siemens is working on a driverless subway system in Riyadh as part of its smart city initiatives. Why it matters: Smart city initiatives are crucial for managing resources and reducing emissions in rapidly growing urban centers in Saudi Arabia.
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.