IoT and Data Analytics: Transforming Population Health Management

Prof. Suneet Kumar

Abstract


This paper investigates the role of IoT and data analytics in transforming population health management. By collecting and analyzing health data from diverse populations, we developed strategies for addressing public health challenges. Our findings demonstrate the potential of IoT to inform policy decisions and improve community health outcomes.

References


Gupta, R., & Kumar, P. (2023). IoT-driven medication adherence solutions: Innovations and challenges. Journal of Health Economics, 45, 55-66. https://doi.org/10.1016/j.jhealeco.2023.10.002

Hernandez, J., & Lopez, S. (2023). Predictive analytics in healthcare: IoT and machine learning synergy. Artificial Intelligence in Medicine, 127, 102-115. https://doi.org/10.1016/j.artmed.2023.102115

Johnson, R., & Thompson, G. (2024). Enhancing patient safety with IoT solutions in healthcare. Healthcare Technology Letters, 11(1), 1-10. https://doi.org/10.1049/htl2.12025

Martinez, A., & Ramirez, T. (2023). The future of IoT in health information exchange: Opportunities and barriers. Health Services Research, 57(3), 719-735. https://doi.org/10.1111/1475-6773.13625

Ahn, H., & Lee, J. (2023). IoT-enabled wearables for chronic disease management. Journal of Healthcare Informatics Research, 7(2), 150-165. https://doi.org/10.1007/s41666-023-00032-5

Brown, T., & Smith, R. (2022). The impact of IoT on remote patient monitoring: A review. International Journal of Medical Informatics, 168, 104-112. https://doi.org/10.1016/j.ijmedinf.2022.104112

Chen, M., & Zhang, J. (2024). Smart hospitals: Integrating IoT for enhanced patient care. Journal of Health Management, 25(2), 215-229. https://doi.org/10.1177/09720634211013984

Yadav, H. (2023). Securing and Enhancing Efficiency in IoT for Healthcare Through Sensor Networks and Data Management. International Journal of Sustainable Development Through AI, ML and IoT, 2(2), 1-9.

Yadav, H. (2023). Enhanced Security, Privacy, and Data Integrity in IoT Through Blockchain Integration. International Journal of Sustainable Development in Computing Science, 5(4), 1-10.

Yadav, H. (2023). Advancements in LoRaWAN Technology: Scalability and Energy Efficiency for IoT Applications. International Numeric Journal of Machine Learning and Robots, 7(7), 1-9.

Yadav, H. (2024). Scalable ETL pipelines for aggregating and manipulating IoT data for customer analytics and machine learning. International Journal of Creative Research In Computer Technology and Design, 6(6), 1-30.

Yadav, H. (2024). Anomaly detection using Machine Learning for temperature/humidity/leak detection IoT. International Transactions in Artificial Intelligence, 8(8), 1-18.

Yadav, H. (2024). Structuring SQL/NoSQL databases for IoT data. International Journal of Machine Learning and Artificial Intelligence, 5(5), 1-12.

Gonaygunta, H. (2023). Factors Influencing the Adoption of Machine Learning Algorithms to Detect Cyber Threats in the Banking Industry. University of the Cumberlands.

Gonaygunta, H., Meduri, S. S., Podicheti, S., & Nadella, G. S. (2023). The Impact of Virtual Reality on Social Interaction and Relationship via Statistical Analysis. International Journal of Machine Learning for Sustainable Development, 5(2), 1-20

Pillai, S. E. V. S., & Polimetla, K. (2024, February). Integrating Network Security into Software Defined Networking (SDN) Architectures. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-6). IEEE.

Pillai, S. E. V. S., & Polimetla, K. (2024, February). Analyzing the Impact of Quantum Cryptography on Network Security. In 2024 International Conference on Integrated Circuits and Communication Systems (ICICACS) (pp. 1-6). IEEE.


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