Sadeem, a startup founded by KAUST Ph.D. graduates, develops flood and traffic sensors powered by solar batteries and transceivers. The company's technology originated as a Ph.D. project and has been supported by the KAUST Entrepreneurship Center, including participation in the KAUST Hikma IP-based Startup Accelerator program. Sadeem's sensors are designed to mitigate damage and save lives from floods, with ten nodes currently operating on the KAUST campus. Why it matters: The development and deployment of such sensor technologies in Saudi Arabia could improve urban resilience and disaster response in flood-prone areas across the GCC region.
KAUST startup Sadeem, which provides solar-powered smart city solutions for flood, traffic and environmental monitoring, won the Best Global Startup award in Dubai in 2017. Since then, Sadeem has focused on building its business model and infrastructure to accommodate expansion. Sadeem recently installed its smart city sensors, including the Aura air quality monitor, in Madinah, Saudi Arabia. Why it matters: This expansion demonstrates the potential for Saudi-based startups to provide innovative solutions to local challenges and scale their impact internationally.
This paper introduces a deep vision-based framework for predicting coastal floods under climate change, addressing the challenges of limited training data and high-dimensional output. The framework employs and compares various deep learning models, including a custom compact CNN architecture, against geostatistical and traditional machine learning methods. A new synthetic dataset of flood inundation maps for Abu Dhabi's coast is also provided to benchmark future models.
Researchers have developed a CNN-based deep learning model for predicting coastal flooding in cities under various sea-level rise scenarios. The model utilizes a vision-based, low-resource DL framework and is trained on datasets from Abu Dhabi and San Francisco. Results show a 20% reduction in mean absolute error compared to existing methods, demonstrating potential for scalable coastal flood management.
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.