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Integrating IoT and Artificial Intelligence: A Comprehensive Framework for Creating Smart Environments

Integrating IoT and Artificial Intelligence: A Comprehensive Framework for Creating Smart Environments
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Author(s): G. Swetha (RR Institute of Technology, Bangalore, India), M. S. Veena (RR Institute of Technology, Bangalore, India), Tejaswini Krishnamurthy (RR Institute of Technology, Bangalore, India), S. Druva Kumar (Dayananda Sagar College of Engineering, India), M. Shruthi (Dayananda Sagar College of Engineering, India), S. Vishwanatha (Jain University, India), D. Rajeshwari (The National Institute of Engineering, India), N. Raghu (Jain University, India), Kamal Narayanan (University of Nevada, Las Vegas, USA)and G. B. Arjun Kumar (Dayananda Sagar College of Engineering, India)
Copyright: 2026
Pages: 28
Source title: AI-Based Data Mobility and Intelligent Modeling for Smart Cities
Source Author(s)/Editor(s): Sultan Ahmad (Prince Sattam Bin Abdulaziz University, Saudi Arabia), Sudan Jha (Kathmandu University, Nepal)and Md Alimul Haque (Veer Kunwar Singh University, India)
DOI: 10.4018/979-8-3373-4202-3.ch006

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Abstract

The convergence of Artificial Intelligence and the Internet of Things has paved the way for the development of smart environments that are efficient, adaptive and sustainable. The IoT enables vast networks of interconnected sensors, device and actuators to capture real-time data, AI provides the intelligence needed to process, analyze and act upon this information. Together, they transform reactive systems into proactive context-aware ecosystems capable of decision-making and automation. This chapter presents a comprehensive framework for integrating AI with IoT highlighting its architecture, component and applicability across domains such as smart cities, healthcare, agriculture, transportation and industrial automation. The framework emphasizes enabling technologies including edge, fog and cloud computing, communication protocols and open platforms like FIWARE, which collectively support scalability, interoperability and real-time analytics. the study also critically addresses challenges related to data management, security, privacy, ethical considerations and workforce readiness.

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