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@article{183515,
        author = {Richa Joshi},
        title = {IoT-Based Dynamic Scheduling Interface for Real-Time Healthcare Visualization Using Big Data Analytics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {1970-1974},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183515},
        abstract = {Efficient scheduling and real-time information dissemination are critical to streamlining hospital operations and improving patient care. This paper presents a cost-effective Dynamic Scheduling Interface (DSI) that integrates Internet of Things (IoT) components—namely the ESP32 microcontroller and P10 LED matrices—with big data analytics and machine learning models to deliver live updates on doctor duty rosters, operating-theatre availability, and patient appointment times. By leveraging cloud platforms for data storage and processing, the DSI ensures scalability and supports predictive forecasting of peak demand periods. A mobile/web dashboard provides administrative control, while on-site LED displays relay information in under two seconds. Field testing demonstrated a 60 % improvement in staff efficiency, an 85 % accuracy in load forecasting, and a per-unit cost reduction of 30 % compared to conventional digital signage systems.},
        keywords = {IoT, ESP32, P10 LED Matrix, Big Data Analytics, Machine Learning, Real-time Scheduling, Healthcare Visualization},
        month = {August},
        }