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@article{186721,
        author = {Poonam and Dr. V.K. Srivastava},
        title = {AI-Enabled Intelligent Stone Surgery System for IoT-Connected Medical Platforms},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {3011-3024},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186721},
        abstract = {Particularly in the treatment of kidney and gallbladder stones, the combination of AI and IoT is transforming minimally invasive surgical methods in healthcare. This paper suggests an artificial intelligence-enabled intelligent stone surgery system using IoT connection, real-time data analytics, and machine learning to maximize surgical accuracy, thereby improving patient outcomes, and so optimizing the use of healthcare resources. The technology uses predictive analytics and artificial intelligence-driven image processing to help surgeons find ideal treatment approaches and stone composition, size, and composition. Smooth data interchange between smart surgical equipment, patient monitoring devices, and cloud-based healthcare systems made possible by real-time IoT-based monitoring guarantees constant evaluation and decision-making. Reducing procedural risks and increasing efficiency, the proposed architecture combines edge computing for low-latency processing, robotic-assisted approaches, and deep learning models for diagnostic accuracy. Performance assessment takes into account elements such surgical precision, reaction time, energy economy, and rates of post-surgery rehabilitation. The project intends to create an affordable, artificial intelligence-powered IoT surgical ecosystem improving accuracy, automation, and patient safety during stone removal operations. The results help smart healthcare systems to develop by allowing tailored and data-driven surgical operations on contemporary medical platforms.},
        keywords = {AI in Surgery, IoT Healthcare, Stone Surgery, Smart Medical Platforms, Machine Learning, Real-time Monitoring, Robotic-Assisted Surgery},
        month = {November},
        }