AI ML Empowered Smart Buildings and Factories
Akey Sungheetha, Rajesh Sharma R, R. Chinnaiyan, G S Pradeep Ghantasala · 2025
This chapter examines machine learning's important role in automating numerous tasks. In “intelligent” buildings, the use of mobile devices and computers may greatly simplify tasks like monitoring security, regulating the interior climate, and carrying out routine maintenance. The World Wide Web or Internet of Things is used by intelligent buildings to create connections between the various parts that comprise the building. The chapter also covers the development of artificial intelligence at smart buildings, with a focus on global issues. Specifically, energy conservation and consumption pose the biggest obstacles for all industries, but particularly for the home and industrial sectors. The foundation of Production 4.0 is founded by an innovative knowledge termed the internet of everything (IoeT). The IoT makes it possible for mechanisms and devices to communicate seamlessly. In the context of building engineering and construction industry 4.0, the chapter explores in detail the claims made by the domains of computing (artificial intelligence), informed machine learning techniques (ML), as well as deep learning algorithms (DL). It also looks at the idea of intelligent manufacturing for smart cities. These applications comprise architectural enterprise besides picturing, structural analysis and plan, material design in addition to optimization, off-site manufacturing while automation, construction supervision and progress tracking, longevity, life cycle assessment, smart functioning, building administration, and the circular economy are all included. Insights into the Smart building technology is based on the integration of devices, large information, with AI. To support smart building applications, a thorough examination and categorization of machine learning approaches are provided. A new era in city energy efficiency may result from this. Artificial intelligence (AI) can be used in intelligent structures to improve control, automation, and dependability—all of which will lead to a decrease in energy usage. Within the broader architecture, technology, and construction sector, the chapter highlights how IoT, big data, through artificial intelligence have become more integrated; thanks to the quick advancement of technology, which has been fueled by machine learning as well as IoT. Innovation besides technological advancement in the manufacturing have accelerated due to this convergence. This book chapter gives a thorough overview of how “smart” manufacturing is becoming the norm and how the traditional production-oriented manufacturing environment is soon to give way to one that is more data-oriented, automated, and smart.