Advanced Signal Processing and Sensor Data Analysis for Efficient Smart Grids

Smart grids increasingly rely on IoT devices to monitor, control, and optimize energy distribution in real time. As the number of connected sensors and devices grows, so does the volume and complexity of data these systems must process. Advanced signal processing techniques offer a path to handling this data more efficiently — improving accuracy, reducing latency, and supporting faster decision-making across the grid.This Research Topic welcomes contributions exploring how signal processing methods can enhance IoT-enabled smart grid performance. Topics of interest include, but are not limited to:• Signal processing techniques for real-time grid monitoring, state estimation, and fault detection• Data compression, feature extraction, and filtering methods for sensor networks in energy systems• Noise reduction, interference mitigation, and signal enhancement for reliable grid communication• Machine learning-assisted signal processing for predictive maintenance and anomaly detection• Energy-efficient signal processing algorithms for resource-constrained sensing devices• Distributed and cooperative signal processing for smart grid applications• Signal processing for power quality monitoring and disturbance classification• Signal processing methods supporting renewable energy integration and microgridsWe welcome original research, reviews, and case studies that advance the practical and theoretical understanding of signal processing’s role in building smarter, more efficient, and more resilient energy grids. Topic editors: Obada Al Khatib, Ali Hellany, Mohamad Nassereddine, Waheb A. Jabbar Source: https://www.frontiersin.org/research-topics/86360/advanced-signal-processing-and-sensor-data-analysis-for-efficient-smart-grids