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@article{185008,
        author = {A JOTHI SORUBA THAYA and J.JEBA PRASANNA JOICE and P.RAJALAKSHMI and C.ARUL JOHNSI},
        title = {Assessing the Effectiveness: A Comparative Study of Healthcare Interventions},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {4138-4143},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185008},
        abstract = {Continuous and precise patient monitoring is essential in intensive care settings to ensure optimal outcomes. This study investigates the development of an advanced framework leveraging Internet of Things (IoT) technologies for comprehensive monitoring of critical physiological indicators in intensive care units. The proposed system aims to minimize reliance on manual observation by enabling uninterrupted tracking of vital signs such as core temperature, oxygen saturation, heart rate, blood pressure, and electrocardiographic activity. Additionally, it integrates biochemical analysis for patient samples, assessing parameters like glucose, lactate, circulatory status, blood cell counts, and electrolyte levels, including calcium and potassium. Edge computing nodes are employed for local data processing and storage, compiling detailed clinical profiles from real-time patient data and securely archiving them in cloud-based platforms. This architecture allows healthcare professionals to access up-to-date patient information and analytical summaries remotely, enhancing decision-making capabilities. Automated alert functions are incorporated to promptly notify clinical teams of any abnormal physiological changes. The research provides a comparative analysis of current intelligent IoT solutions in critical care monitoring, highlighting the unique advantages of the proposed approach. The study concludes by discussing potential future enhancements, such as strengthening cyber security measures and integrating artificial intelligence to further improve system performance.},
        keywords = {Healthcare, IoT, Cyber Security, Machine Learning},
        month = {September},
        }