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 Faculty Publications Conference Paper Faculty Publications- Conference Papers 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/. Creator An entity primarily responsible for making the resource Nwibo, Ezekiel Gabriel; Iwendi, Celestine; Sharma, Vandana; Nwigwe, Simon; Ojo, Olayinka Anthony; Odirichukwu, Jacinta Chioma Title A name given to the resource Prediction of Campus Energy Consumption Patterns Using Machine Learning Techniques Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 12th International Conference on Reliability, Infocom Technologies and Optimization ,Trends and Future Directions, ICRITO 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRITO66076.2025.11241252" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRITO66076.2025.11241252</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105029841206?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105029841206?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Nwibo E.G., School of Arts and Creative Technologies, University of Greater Manchester, Department of Computing, Bolton, United Kingdom; Iwendi C., School of Arts and Creative Technologies, University of Greater Manchester, Department of Computing, Bolton, United Kingdom; Sharma V., Christ University, Computer Science Department, Bengaluru, India; Nwigwe S., Doctoral College, University of Greater Manchester, Department of Research, Bolton, United Kingdom; Ojo O.A., University of Greater Manchester, Department of Computing, Bolton, United Kingdom; Odirichukwu J.C., Federal University of Technology Owerri, Department of Computer Science, Nigeria Description An account of the resource The exponential increase in campus energy consumption results from the rise in population density, leading to urbanisation and the use of higher energy-intensive devices within the environment. This study explored high-performance data analytics techniques to visualise energy consumption across buildings using datasets obtained from a load audit of the entire distribution network within the Federal University of Technology, Owerri (FUTO). Advanced time series models were used to predict and forecast the consumption patterns for a year. Visualisations for this research provided detailed insights into the energy profile across all the clusters, while the SARIMA, ARIMA, and Prophet models predicted the energy demands. The heatmap for the correlation matrix reveals a constant energy scale throughout the week (weekend average energy usage is at least 40% of the weekday). A comparative performance was done to analyse the scalability and predictive abilities of the individual models. Results from the study indicate that SARIMA has the lowest mean square error (4.4896) and the highest R2 score (0.8362). The study concludes that the adoption of machine learning models for energy forecasting and prediction is vital for modern-day energy management in the University. 2025 IEEE. Subject The topic of the resource ARIMA; Artificial Intelligence; Energy Management; Machine Learning; Prophet; Renewable Energy; SARIMA Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833155421-7; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online