Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Optimized Multi-Scale Attention Convolutional Neural Network for Micro-Grid Energy Management System Employing in Internet of Things Subject The topic of the resource convolutional neural network; ensemble Kalman filter; fault detection; internet of things; microgrid energy management; sheep flock optimization Description An account of the resource The combination of micro-grid energy management systems (EMSs) with the Internet of Things (IoT) offers a promising way to improve energy use and distribution. However, challenges such as device compatibility and the difficulty of managing energy efficiently make it hard to implement these systems effectively. This study offers a significant advancement in energy management by using IoT for microgrid systems. An Optimized Multi-scale Attention Convolutional Neural Network for microgrid EMS employing IoT (OMACNN-MGEMS-IoT) is proposed in this study, which enables efficient monitoring and control of energy resources. The proposed model's input data are gathered from the MQTT dataset. This research employs a Regularized Bias-aware Ensemble Kalman Filter (RBAEKF) for pre-processing input data, ensuring the removal of outliers and updating missing values. The MACNN is then used for effective fault detection within the microgrid. To enhance its performance, the Sheep Flock Optimization Algorithm (SFOA) is introduced to optimize the MACNN parameters, ensuring accurate fault detection. Implemented on the MATLAB platform, the performance of the OMACNN-MGEMS-IoT method is assessed through various performance metrics, demonstrating significant improvements. Notably, the proposed method achieves higher cost reductions of 25%, 22%, and 26% compared to existing approaches such as the IoT platform for energy management in multi-micro grid systems (IoT-PEM-MMS), a micro-grid system infrastructure implementing IoT for efficient energy management in buildings (MSII-IoT-EEM) and a hybrid deep learning-based online energy management scheme for industrial microgrids (HDL-OEM-IM). The findings highlight the impact of the proposed OMACNN-MGEMS-IoT method in enhancing energy efficiency and cost-effectiveness in microgrid systems. 2025 John Wiley &amp; Sons Ltd. Creator An entity primarily responsible for making the resource Vetriveeran D.; Sambandam R.K.; Sekar T.; Venkatachalam A. Source A related resource from which the described resource is derived Optimal Control Applications and Methods Publisher An entity responsible for making the resource available John Wiley and Sons Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2025-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1002/oca.3253" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/oca.3253</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216361861&amp;doi=10.1002%2Foca.3253&amp;partnerID=40&amp;md5=f50fb57b9643bc5db1bb8f0ef59ab081" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216361861&amp;doi=10.1002%2foca.3253&amp;partnerID=40&amp;md5=f50fb57b9643bc5db1bb8f0ef59ab081</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 1432087; CODEN: OCAMD Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vetriveeran D., Department of Computer Science and Engineering, Christ University, Bangalore, India; Sambandam R.K., Department of Computer Science and Engineering, Christ University, Bangalore, India; Sekar T., Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India; Venkatachalam A., Department of Computer Science and Engineering, Christ University, Bangalore, India