Multi-sensor data fusion perspective for smart grid analytics

Abstract

In recent years, in parallel with the developments in technology, there is a constant change in the needs and demands of communities. Most of the emerging solutions developed in this context are based on intelligent systems that gather data from various sensors in different formats. Internet of Things (IoT) is viewed as one of the enabling technologies for smart grids. Except for smart cities, smart grids are one of the largest IoT deployments. IoT can potently improve existing smart grids by facilitating real-time control and monitoring of the grid components. The main challenge of IoT-based solutions is the requirement of combining data received from different types of sensors in different structures and formats into a useable format in a single structure. Since several factors and parameters play a role in this process, there is a need to reveal the problems and difficulties encountered in combining data and offer methods to deal with them. In this regard, in this study, a literature survey is carried out to present the background and state-of-the-art in multi-sensor fusion domain. In addition, taxonomies of the papers and methods are presented. The survey reveals that JDL approach is the most used model in multi-sensor data fusion. © 2025 Elsevier Inc. All rights reserved.