Urban IoT and Quantum Computing: Bridging Cryptographic Security and Sustainable Development V. Saranya, K. Vijayalakshmi, S. Udhayashankar Post Quantum Cryptography and Iot Communications for Sustainable Urban Development, 2025 As quantum computing advances, existing cryptographic techniques used in smart city infrastructures face increasing vulnerability, especially within internet of things (IoT) networks. This chapter explores the critical role of post-quantum cryptography (PQC) in securing urban IoT ecosystems against quantum threats while addressing sustainability challenges. It covers PQC principles, algorithm families, integration with IoT communication protocols, and the protection of critical sectors such as energy, healthcare, and transportation. The chapter also explores quantum-specific network attacks, supply chain vulnerabilities, and the role of green cryptography and AI-assisted security. Emphasis is placed on balancing quantum resilience with energy efficiency to ensure secure, scalable, and sustainable smart cities. The chapter concludes by identifying future research directions to guide the transition toward quantum-safe and eco-conscious urban infrastructure.
AI and applied microbiology in sustainable waste recycling and the circular economy S. Anusha, B. Yamini, S. Udhayashankar, V. Priya, M. Ezhilvendan, R. Vinoth, R. Siva Subramanian AI Technologies for Enhancing Recycling Processes, 2025 Recycling and sustainability are areas of paramount concern in the contemporary world and this paper explores the strategies of applied microbiology as well as artificial intelligence (AI) to enhance these methods. It brings into focus the notion of circular economy, which is of paramount importance in cyclical waste management that meets the least ecological influence and optimizes the resource utilization. The paper is grouped into the following segments: an outline of waste recycling and managerial aspects, the principles of sustainability, the role of applied microbiology in waste degradation, and the integration of artificial intelligence in waste sorting and recycling. Therefore, by adopting an interdisciplinary approach, it offers valuable insights to researchers, policymakers, and industry stakeholders, who are involved in the development of lasting and efficient waste management systems, which are based on the principles of circular economy.
Energy Efficient Big Data Processing: A Comprehensive Survey on Techniques, Trends, and Future Directions D. Ravindran, G. Mariammal, S. Udhayashankar, K. Dhivya, D. Lekha, T. Maheshwaran, V. Sathya Energy Efficient Algorithms and Green Data Centers for Sustainable Computing, 2025 The exponential rise in big data has resulted in higher energy requirements in data processing frameworks, which present a major environmental and practical concern. As the amount of data being generated grows, cost effective and energy efficient big data processing has become critical. This paper reviews different techniques that improve energy efficiency in big data processing from hardware level optimization, software level adaptation and data level optimization. Proposed and implemented low power processors and energy aware storage; energy efficient scheduling; data compression; and data reduction strategies such as edge computing have been found to be effective in the energy management of big data processing. Other new paths include artificial intelligence based energy management and green data centers. The goal of this survey is to give an overview of the existing situation, show examples of the implementation of energy-efficient BD processing frameworks, and point out the possible directions for their further development.
Energy-Efficient Solutions and Environmental Impact Reduction in Mobile and Wireless Computing T. Veeramani, D. Prabhu, B. Yamini, V. K. Ramya Bharathi, R. Vinoth, S. Udhayashankar, P. J. Beslin Pajila Energy Efficient Algorithms and Green Data Centers for Sustainable Computing, 2025 With the advancement of the mobile and wireless computing technologies more and more attention has been paid to their impact on environment. This paper provides an overview of green solutions pertaining to the energy conservation and carbon emission of portable gadgets, wireless networks and communication systems. It covers fundamental concepts like low power hardware design, energy efficient cellular network and efficient power control mechanisms. The viability of renewable resources as well as the energy harvesting and wireless charging technologies in enhancing sustainability of the devices is also described. Furthermore, the paper analyses the implementation of edge computing, energy-aware networks, and AI solutions for enhancing energy efficiency in mobile and wireless networks. Green mobile networks and sustainable IoT are illustrated by case studies of real-world applications. Last, the paper presents a discussion of the threat, including the trade-off between performance and energy consumption, and directions for future research to improve sustainability in this field.
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