Aksoy, RamazanKaraoglu, SenaYuzak, ErginÇiÇek, Gulay2026-01-312026-01-31202597830317803879783031780370https://doi.org/10.1007/978-3-031-78038-7_1https://hdl.handle.net/20.500.12662/10566This chapter examines the differences between the energy efficiency and environmental impacts of traditional houses and smart home systems in daily life. Compared to classical arrangements in traditional homes, the advantages of automation and energy management provided by using smart home systems are discussed. This chapter evaluates and compares the effects of both concepts on daily life, focusing on criteria such as comfort, security and energy saving between a traditional house and a house furnished with a smart system. The chapter also addresses the environmental sustainability of smart home systems. The potential of smart home systems to provide energy efficiency has the potential to reduce the environmental impact of this technology. The chapter addresses how smart home systems can be optimized, especially in terms of energy saving, to understand their environmental impact and discusses how this technology can contribute to a sustainable lifestyle. In this context, it evaluates the environmental sustainability and user convenience of future home designs by evaluating the environmental impacts of smart home systems compared to traditional homes. This study also aims to evaluate the performance of commonly used classification algorithms such as Neural Network, Support Vector Machines Rbf Kernel, Logistic Regression, Decision Trees, K Nearest Neighbor Algorithm, Support Vector Machines and Random Forest on smart home systems and traditional home energy consumption dataset. The effectiveness of each algorithm in energy consumption classification is analyzed using various performance metrics, and the results allow inferences to be made to support important decisions on the energy efficiency of smart home systems. This study provides valuable insights into identifying optimal classification algorithms for future smart home systems design to support energy saving and sustainability goals. © Springer Nature Switzerland AG 2025. All rights reserved.eninfo:eu-repo/semantics/closedAccessCoefficient of performanceEnvironmental management systemsSmart homesClassification algorithmDaily livesEnergyEnergy savingsEnergy-consumptionEnergy-savingsEnvironmental sustainabilitySmart-home systemSupport vectors machineTraditional houseEnergy savingBook Chapter10.1007/978-3-031-78038-7_12-s2.0-10500496961332N/A1