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Title Unleashing The Power Of Data And Security By Integrating Deep Learning And Blockchain In Smart City Infrastructure Development - A Future Perspective
ID_Doc 59642
Authors Aravinth S.S.
Year 2025
Published Deep Learning and Blockchain Technology for Smart and Sustainable Cities
DOI http://dx.doi.org/10.1201/9781003476047-3
Abstract As urban populations continue to grow and technological advancements reshape our world, the concept of smart cities has emerged as a beacon of innovation in urban development. This chapter explores the transformative potential of two cutting-edge technologies, deep learning and blockchain, in the context of smart cities. Deep learning, a subset of artificial intelligence, offers powerful tools for analyzing vast amounts of urban data to optimize various aspects of city life, including traffic management, public safety, energy usage, waste management, and healthcare. Concurrently, blockchain technology provides decentralized and secure platforms for transactions, supply chain management, identity verification, smart contracts, and data privacy, addressing critical challenges faced by modern cities. By examining the applications of deep learning and blockchain in smart cities, this chapter delves into the synergistic possibilities and challenges of integrating these technologies into urban infrastructure. Real-world case studies highlight successful implementations and lessons learned, while future perspectives envision the continued evolution of smart cities powered by deep learning and blockchain innovations. As a result, this chapter emphasizes the critical importance of collaboration, innovation, and strategic planning in unlocking the vast potential of deep learning and blockchain technologies to revolutionize smart cities and improve urban life on a global scale. By fostering partnerships, driving innovation, and implementing thoughtful strategies, cities can harness the transformative power of these technologies to create more efficient, sustainable, and resilient urban environments for the benefit of all residents. © 2025 selection and editorial matter, V. Subramaniyaswamy, G Revathy, Logesh Ravi, N. Thillaiarasu, and Naresh Kshetri; individual chapters, the contributors.
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