Loading...
R. Asokkumar is an Assistant Professor in the Department of Computer Science and Engineering at Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh. His contribution covers AI-enabled smart manufacturing and emerging intelligent engineering applications.
The Internet of Things (IoT) and cloud computing have emerged as essential technologies for the creation of intelligent, interconnected engineering systems. The Internet of Things facilitates the collection and exchange of real-time data across physical devices, sensors, machines, and infrastructure, whilst cloud computing offers scalable storage, processing, analytical, and service functionalities.This chapter elucidates the essential principles, frameworks, communication technologies, and applications of IoT and cloud computing in the context of intelligent engineering systems. It examines IoT sensor strata, network frameworks, edge and fog computing, cloud infrastructures, data governance, security measures, interoperability, and AI-driven analytics. The section also explores the amalgamation of IoT and cloud technology within intelligent manufacturing, urban environments, energy frameworks, transportation, healthcare, agriculture, and infrastructure oversight. Innovative methodologies including edge AI, digital twins, federated learning, 5G/6G communication, and serverless computing are likewise investigated. Ultimately, the chapter underscores significant obstacles and prospective research avenues for developing scalable, secure, intelligent, and sustainable IoT-cloud ecosystems.
The swift increase in urban demographics has posed considerable difficulties in overseeing transportation, electricity, water, garbage, public infrastructure, and environmental assets. Intelligent urban areas tackle these issues by incorporating Artificial Intelligence (AI), the Internet of Things (IoT), communication infrastructures, cloud computing, and data-centric decision-making frameworks. IoT devices facilitate the ongoing acquisition of real-time data from urban infrastructure, whereas AI methodologies convert this information into practical insights for forecasting, enhancement, automation, and intelligent management. This section delineates the principles, frameworks, and primary utilisations of AI and IoT in the management of smart city infrastructure. It examines IoT sensor frameworks, communication technologies, cloud and edge computing, machine learning, deep learning, and intelligent decision-support systems. Prominent domains of use encompass intelligent transportation, traffic oversight, energy infrastructures, water supply systems, waste disposal, ecological surveillance, public security, and structural integrity assessment. The section additionally explores nascent technologies including digital twins, edge artificial intelligence, federated learning, 5G/6G communications, and interpretable AI. Ultimately, issues concerning scalability, interoperability, cybersecurity, privacy, data integrity, and sustainable implementation are examined alongside prospective research avenues for creating robust, efficient, and citizen-focused smart city frameworks.