Nawal Alsaleh

Centre National de la Recherche Scientifique

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About

Nawal Alsaleh is a researcher specializing in sensor-fault detection, signal processing, and real-time monitoring systems. Her work focuses on improving the reliability and responsiveness of fault detection algorithms, particularly through the application of information theory. In her most cited paper, "Fast and Real-Time Sensor-Fault Detection using Shannon’s Entropy" (2021), Alsaleh introduces an adaptive thresholding method combined with a sliding time window to detect sensor anomalies in real time. A key innovation of this work is the implementation of an optimal sliding time window length that operates without any preliminary learning phase—a significant departure from conventional approaches that require prior training data. This contribution enhances the speed and adaptability of fault detection systems, making them more suitable for dynamic and resource-constrained environments. While her citation count is still growing, Alsaleh’s research holds promise for applications in industrial automation, robotics, and embedded systems where early and accurate fault detection is critical. Her work represents a step toward more intelligent, self-correcting sensor networks.