Edge-Intelligent IoT: Convergence of AI, Edge Computing, and Sustainable Networks for Smart Environments

The Internet of Things (IoT) has emerged as a transformative force across diverse sectors including smart cities, industrial automation, precision agriculture, and digital healthcare. With the proliferation of billions of connected devices generating massive volumes of real-time data, traditional cloud-centric architectures are struggling to meet the demands of low latency, high scalability, security, and energy efficiency. These limitations necessitate a paradigm shift toward decentralized and intelligent architectures.Edge computing, by processing data closer to the source, offers a promising alternative by reducing latency, conserving bandwidth, and enabling real-time responsiveness. When combined with Artificial Intelligence (AI), edge devices become capable of local decision-making, enhancing the autonomy and efficiency of IoT systems. Additionally, sustainable networking practices are critical to support energy-efficient operations, especially for battery-powered or resource-constrained IoT deployments in remote and rural environments.The integration of AI, edge computing, and sustainable network design forms a robust foundation for the next generation of intelligent IoT ecosystems. However, this convergence also introduces new challenges such as standardization, interoperability, data privacy, distributed learning models, and resilient algorithm design, which must be addressed to fully realize the potential of edge-intelligent IoT systems.This Research Topic aims to advance interdisciplinary research at the intersection of AI, edge computing, and sustainable IoT networking. The goal is to foster innovative frameworks, methodologies, and systems that enable real-time, secure, and energy-efficient smart environments. We seek to bring together academics, practitioners, and industry leaders to contribute novel insights that can inform both theoretical advancements and practical implementations.This Research Topic welcomes original research articles, comprehensive reviews, and impactful case studies that explore cutting-edge developments and applications in edge-intelligent IoT. Submissions may address, but are not limited to, the following themes:- AI-driven edge analytics for real-time decision-making in IoT applications- Energy-efficient and low-power IoT system architectures- Edge security mechanisms, including lightweight cryptography and privacy-preserving models- Federated and distributed learning frameworks for collaborative intelligence across devices- Sustainable IoT deployment models for smart urban and rural infrastructures- Standardization and interoperability issues in heterogeneous and multi-vendor IoT systems- Bio-inspired algorithms, swarm intelligence, and adaptive communication protocols for edge-IoT environments- Green networking techniques and resource-aware routing in edge networksThe Research Topic aims to serve as a multidisciplinary platform for exchanging novel concepts and practical solutions to build scalable, resilient, and intelligent IoT ecosystems. We encourage contributions from the fields of computer science, electrical engineering, network systems, sustainability science, and applied AI. Topic editors: Weiwei Jiang, Rakesh Ranjan, Rahul Priyadarshi, Om Prakash Singh Source: https://www.frontiersin.org/research-topics/74699/edge-intelligent-iot-convergence-of-ai-edge-computing-and-sustainable-networks-for-smart-environments