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@article{179692,
        author = {Praneet Amul Akash Cherukuri},
        title = {A Scalable Edge-Cloud Framework for AI-Driven Autonomous Robotics in Industrial Environments},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {8772-8780},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179692},
        abstract = {The fusion of Artificial Intelligence (AI) with robotics and edge-cloud computing is driving a transformative shift in industrial automation, enabling machines to operate autonomously, adaptively, and intelligently. This review explores a scalable edge-cloud framework designed to support AI-driven autonomous robotics in dynamic industrial environments. By analyzing over a decade of academic and industrial advancements, the article synthesizes insights into the architecture, algorithms, and deployment strategies that have defined the evolution of this field. Key metrics such as latency, energy efficiency, accuracy, and bandwidth consumption are critically examined through experimental findings. Despite substantial progress, persistent challenges related to system scalability, security, interoperability, and generalization remain. The review concludes by outlining future research directions, emphasizing the need for more robust, collaborative, and adaptive AI-robotic systems. This paper aims to serve as a foundation for researchers, engineers, and policymakers invested in shaping the next generation of intelligent industrial automation.},
        keywords = {Autonomous robotics, edge computing, cloud computing, industrial automation, AI-driven systems, machine learning, Industry 4.0, edge-cloud architecture, real-time robotics, cyber-physical systems.},
        month = {May},
        }