Empowering Diabetes Management through IoT: A Comprehensive Research Study on Diabetic Health Monitoring and Control

Priyanka Kumari

Abstract


The prevalence of diabetes has reached epidemic proportions worldwide, necessitating innovative and effective approaches for its management. The integration of Internet of Things (IoT) technology with diabetic care holds great promise in revolutionizing the way diabetes is monitored and controlled. This research paper presents a comprehensive study that explores the potential of IoT-based solutions for diabetes management.

The objective of this research is to evaluate the impact of IoT on various aspects of diabetic health, including real-time monitoring of blood glucose levels, insulin administration, dietary management, physical activity tracking, and patient-doctor communication. The study also investigates the potential benefits of incorporating wearable devices, continuous glucose monitoring (CGM) systems, and smart insulin pumps into diabetes care routines.

To conduct this research, a sample group of diabetic patients is recruited, and IoT-enabled devices are deployed to monitor their health parameters over an extended period. Data collected from these devices are analyzed, and their impact on diabetes management outcomes is assessed. Furthermore, the research explores the integration of artificial intelligence and machine learning algorithms to provide personalized insights and predictive capabilities, enhancing the overall efficacy of diabetes care.

The paper also addresses potential challenges related to data security, privacy concerns, and interoperability of various IoT devices and proposes strategies to mitigate these issues. Additionally, it highlights the importance of user-friendly interfaces and seamless integration of IoT devices with existing healthcare systems to encourage widespread adoption among both patients and healthcare providers.


References


A. Kumar, S. Gupta, N. Yathiraju, S. Bose Chakraborty, K. Dodda and D. Verma, "The Novel E-Way of Identifying the Face Mask and To Ware the System in the Crowd Management System," 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 999-1002, doi: 10.1109/ICACITE57410.2023.10182427.

R. Pandey, S. Saha, N. Yathiraju, I. S. Abdulrahman, R. Nittala and V. Tripathi, "Integration of RFID and Image Processing for Surveillance A Based Security System," 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 380-384, doi: 10.1109/ICACITE57410.2023.10182987.

M. Nagaraju Naik, A. Kaur, N. Yathiraju, S. Das and K. Pant, "Improved and Accurate Face Mask Detection Using Machine Learning in the Crowded Places," 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 572-576, doi: 10.1109/ICACITE57410.2023.10182567.

N. Yathiraju, P. Raman, R. Madala, P. Surgonda Patil, A. Kumar and S. Ashwin, "Research and Innovation to Market Development: Artificial Intelligence in Business," 2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM), Chennai, India, 2023, pp. 1-6, doi: 10.1109/ICONSTEM56934.2023.10142715.

Yathiraju, N., & Mohapatra, A. (2023). "The Implications of IoT in the Modern Healthcare Industry post COVID-19," International Journal of Smart Sensor and Adhoc Network: Vol. 3: Iss. 4, Article 3. DOI: 10.47893/IJSSAN.2023.1226

Yathiraju, N., & Dash, B. (2023). Gamification Of E-Wallets With The Use Of Defi Technology-A Revisit To Digitization In Fintech. International Journal of Engineering, Science, 3(1).

Yathiraju, N., & Dash, B. (2023). BIG DATA AND METAVERSE REVOLUTIONIZING THE FUTURISTICFINTECH INDUSTRY,” International Journal of Computer Science & Information Technology(IJCSIT) Vol 15, No.1, 2023. DOI: 10.5121/ijcsit.2023.15101

Ahammad, D. S. H. ., & Yathiraju, D. . (2021). Maternity Risk Prediction Using IOT Module with Wearable Sensor and Deep Learning Based Feature Extraction and Classification Technique. Research Journal of Computer Systems and Engineering,2(1), 40:45

Arun Velu, P. W. (2021a). Impact of Covid Vaccination on the Globe using data analytics. International Journal of Sustainable Development in Computing Science, 3(2).

Bhatia, V., & Bhatia, G. (2013a). Room temperature based fan speed control system using pulse width modulation technique. International Journal of Computer Applications, 81(5).

Bhatia, V., & Whig, P. (2013b). A secured dual tune multi frequency based smart elevator control system. International Journal of Research in Engineering and Advanced Technology, 4(1), 1163–2319.

Chopra, G., & WHIG, P. (2022a). A clustering approach based on support vectors. International Journal of Machine Learning for Sustainable Development, 4(1), 21–30.

Chopra, G., & Whig, P. (2022a). Energy Efficient Scheduling for Internet of Vehicles. International Journal of Sustainable Development in Computing Science, 4(1).

Chopra, G., & WHIG, P. (2022b). Using machine learning algorithms classified depressed patients and normal people. International Journal of Machine Learning for Sustainable Development, 4(1), 31–40.

Jupalle, H., Kouser, S., Bhatia, A. B., Alam, N., Nadikattu, R. R., & Whig, P. (2022). Automation of human behaviors and its prediction using machine learning. Microsystem Technologies, 1–9.

Khera, Y., Whig, P., & Velu, A. (2021a). efficient effective and secured electronic billing system using AI. Vivekananda Journal of Research, 10, 53–60.

Lahade, S. v, & Hirekhan, S. R. (2015a). Intelligent and adaptive traffic light controller (IA-TLC) using FPGA. 2015 International Conference on Industrial Instrumentation and Control (ICIC), 618–623.

Mamza, E. S. (2021). Use of AIOT in Health System. International Journal of Sustainable Development in Computing Science, 3(4), 21–30.

Nadikattu, R. R. (2014a). Content analysis of American & Indian Comics on Instagram using Machine learning. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320–2882.

Nadikattu, R. R., Mohammad, S. M., & Whig, P. (2020a). Novel economical social distancing smart device for covid-19. International Journal of Electrical Engineering and Technology (IJEET).

Rupani, A., Whig, P., Sujediya, G., & Vyas, P. (2017a). A robust technique for image processing based on interfacing of Raspberry-Pi and FPGA using IoT. 2017 International Conference on Computer, Communications and Electronics (Comptelix), 350–353.

Sharma, A., Kumar, A., & Whig, P. (2015a). On the performance of CDTA based novel analog inverse low pass filter using 0.35 µm CMOS parameter. International Journal of Science, Technology & Management, 4(1), 594–601.

Tomar, U., Chakroborty, N., Sharma, H., & Whig, P. (2021). AI based Smart Agricuture System. Transactions on Latest Trends in Artificial Intelligence, 2(2).

Velu, A., & Whig, P. (2021a). Protect Personal Privacy And Wasting Time Using Nlp: A Comparative Approach Using Ai. Vivekananda Journal of Research, 10, 42–52.

Whig, P. (2019a). A Novel Multi-Center and Threshold Ternary Pattern. International Journal of Machine Learning for Sustainable Development, 1(2), 1–10.

Whig, P. (2019d). Exploration of Viral Diseases mortality risk using machine learning. International Journal of Machine Learning for Sustainable Development, 1(1), 11–20.

WHIG, P. (2022). More on Convolution Neural Network CNN. International Journal of Sustainable Development in Computing Science, 4(1).

Whig, P., & Ahmad, S. N. (2011a). On the performance of ISFET-based device for water quality monitoring. Int’l J. of Communications, Network and System Sciences, 4(11), 709.

Whig, P., & Ahmad, S. N. (2012a). A CMOS integrated CC-ISFET device for water quality monitoring. International Journal of Computer Science Issues, 9(4), 1694–1814.

Whig, P., & Ahmad, S. N. (2012f). Performance analysis of various readout circuits for monitoring quality of water using analog integrated circuits. International Journal of Intelligent Systems and Applications, 4(11), 103.

Whig, P., & Ahmad, S. N. (2013a). A novel pseudo-PMOS integrated ISFET device for water quality monitoring. Active and Passive Electronic Components, 2013.

Whig, P., & Ahmad, S. N. (2014a). Development of economical ASIC for PCS for water quality monitoring. Journal of Circuits, Systems and Computers, 23(06), 1450079.

Whig, P., & Ahmad, S. N. (2014c). Simulation of linear dynamic macro model of photo catalytic sensor in SPICE. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering.

Whig, P., Kouser, S., Velu, A., & Nadikattu, R. R. (2022). Fog-IoT-Assisted-Based Smart Agriculture Application. In Demystifying Federated Learning for Blockchain and Industrial Internet of Things (pp. 74–93). IGI Global.

Whig, P., Nadikattu, R. R., & Velu, A. (2022). COVID-19 pandemic analysis using application of AI. Healthcare Monitoring and Data Analysis Using IoT: Technologies and Applications, 1.

Whig, P., Velu, A., & Bhatia, A. B. (2022). Protect Nature and Reduce the Carbon Footprint With an Application of Blockchain for IIoT. In Demystifying Federated Learning for Blockchain and Industrial Internet of Things (pp. 123–142). IGI Global.

Whig, P., Velu, A., & Naddikatu, R. R. (2022). The Economic Impact of AI-Enabled Blockchain in 6G-Based Industry. In AI and Blockchain Technology in 6G Wireless Network (pp. 205–224). Springer, Singapore.

Whig, P., Velu, A., & Nadikattu, R. R. (2022). Blockchain Platform to Resolve Security Issues in IoT and Smart Networks. In AI-Enabled Agile Internet of Things for Sustainable FinTech Ecosystems (pp. 46–65). IGI Global.

Whig, P., Velu, A., & Ready, R. (2022). Demystifying Federated Learning in Artificial Intelligence With Human-Computer Interaction. In Demystifying Federated Learning for Blockchain and Industrial Internet of Things (pp. 94–122). IGI Global.

Whig, P., Velu, A., & Sharma, P. (2022). Demystifying Federated Learning for Blockchain: A Case Study. In Demystifying Federated Learning for Blockchain and Industrial Internet of Things (pp. 143–165). IGI Global.


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