Analysis of Time Series of Physical Characteristics of an Ice Rink Using Internet of Things and Machine Learning Technologies
Abstract
Analysis of Time Series of Physical Characteristics of an Ice Rink Using Internet of Things and Machine Learning Technologies
Incoming article date: 19.10.2024Amid the climate crisis and rising energy costs, the need for improving energy efficiency is becoming increasingly critical. Governments aim to reduce carbon dioxide emissions, while businesses seek to optimize energy expenses. The digitalization of the energy sector and the adoption of Internet of Things (IoT) technologies create favorable conditions for the application of artificial intelligence (AI) in energy consumption management. This article provides an overview of AI technologies and their application in energy consumption management, using an ice rink as a case study. The energy consumption data collected from a real-world facility is analyzed, and methods of neural network modeling of time series for forecasting and optimizing management are examined. The results of the modeling are presented, demonstrating the potential of predictive algorithms in reducing energy costs and improving the operational efficiency of ice rinks.
Keywords: global warming, energy consumption, energy efficiency, digitalization, Internet of Things, artificial intelligence, energy management, machine learning, deep learning, time series, predictive algorithms