Current Research

Floods are one of the most common natural disasters, and cause more than 4,000 casualties per year worldwide. Unfortunately, no sensing systems currently exist to accurately monitor and forecast (short term) floods. We propose a new type of all-weather flood sensing system based on Unmanned Aerial Vehicles (UAVs) releasing disposable Lagrangian microsensors.
We are currently developing a new type of dual urban traffic/flood sensor based on passive infrared (PIR) thermopiles and ultrasonic (US) rangefinders.
Our current focus is the development of a common framework based on Mixed Integer Linear Programming to solve various problems associated with transportation networks: state estimation and control, cybersecurity, user privacy and sensor fault detection.
The DSS Lab has developed a new ARM Cortex M4-based computational platform for smart cities applications. This platform will be used for a new Lagrangian/Eulerian solar powered wireless sensor network currently investigated at KAUST, and will enable distributed data processing within the sensor network, greatly simplifying the implementation by removing the need for a backend server.