The use of IoT in healthcare has revolutionized monitoring, notably in the delivery of intravenous fluids. Conventional IV systems are essential, prone to human mistake, and require regular expert supervision. IoT-enabled IV drips provide a completely automated framework that improves safety and efficiency by leveraging sensor data. This research investigates improvements in IoT IV monitoring, focusing on technical innovations and their significance in patient care. Alert systems and flow regulation are among the enhancements that improve accuracy. Prioritizing the integration of vital sign monitoring improves safety and expedites medical action. However, data security and sensor reliability remain major problems, preventing smooth application in medical settings. This study seeks to give a complete evaluation of IoT-integrated IV monitoring, assessing its influence on healthcare services and proposing prospective areas for further research.
Introduction
The Internet of Things (IoT) has significantly transformed healthcare by enabling real-time, automated monitoring of IV drip administration, which traditionally relies on manual oversight prone to human error. IoT-based IV monitoring systems use sensors (like load cells, pressure, and flow sensors), microcontrollers, and communication modules to continuously track fluid levels and infusion rates, sending data to cloud platforms for remote healthcare supervision. These systems improve precision, operational efficiency, and patient safety by providing timely alerts for issues such as low fluid levels, blockages, or air bubbles, reducing the need for constant manual monitoring.
IoT integration also facilitates the monitoring of vital signs (pulse, blood pressure, oxygen levels) alongside IV fluids, offering a comprehensive patient management approach. Advanced IoT solutions incorporate machine learning for predictive analytics, enabling early detection of health risks and preventive interventions.
Despite their advantages, IoT-based IV monitoring devices face challenges, including data security concerns due to sensitive patient information transmission, the need for high-accuracy sensors to avoid errors, and the requirement for seamless interoperability between devices. Encryption, standardized protocols, and emerging technologies like blockchain are crucial for ensuring data security and system reliability.
Overall, IoT-enabled IV monitoring improves healthcare efficiency, safety, and resource management in medical facilities. Ongoing innovation aims to enhance sensor accuracy, security, and predictive capabilities, driving the future of smart, automated healthcare.
Conclusion
The use of IoT in IV drip monitoring has altered healthcare by increasing safety, providing real-time data access, and automating fluid management. This system uses sensors, microcontrollers, and cloud platforms to provide precise and continuous IV fluid level monitoring, allowing healthcare practitioners to respond quickly. Key developments include automatic alarms, predictive analytics, and interoperability with patient health monitoring equipment, which improve knowledge of patient situations. Although worries about data security and sensor reliability remain, IoT-based technologies are expected to increase efficiency and patient outcomes. Future advancements will most likely prioritize device compatibility and further investigate blockchain technology for improved data security. Notably, IoT-based IV monitoring offers a viable answer to traditional healthcare issues, opening the door for a more intelligent and adaptable medical environment.
References
[1] M. G. Vinodh Arrun, G. Srinesh, G. Sridhar, B. Santhosh Kumar, and V. Tamil Selvan, \"IV bag monitoring with patient monitoring system using IoT,\" Int. J. Creative Res. Thoughts (IJCRT), 2023.
[2] E. L. Mathew, J. K. James, A. Radhakrishnan, and B. Sebastian, \"The novel intravenous fluid level indicator for smart IV system,\" Int. Res. J. Eng. Technol. (IRJET), 2020.
[3] G. Sunil, S. Aluvala, G. R. Reddy, V. Sreeharika, P. Sindhu, and S. Keerthana, \"IoT-based saline level monitoring system,\" J. Pharm. Negative Results, 2020.
[4] C. P. S, G. Ganishka, A. M. S. Shane, and G. S., \"IoT-based automatic monitoring and control system,\" J. Phys.: Conf. Ser., 2022.
[5] A. J., G. H. B., L. R. B., A. J. B., and K. J., \"IoT-based smart electrolytic bottle monitoring,\" Adv. Parallel Comput. Technol. Appl., 2021.
[6] M. Tilak, D. Bhor, A. More, and G. Nagare, \"IoT-based smart saline bottle for healthcare,\" Int. Res. J. Eng. Technol. (IRJET), 2021.
[7] C. S. Murugesan, R. Chitralekha, and R. Ramya, \"IoT-based saline monitoring system,\" J. Pharm. Negative Results, 2022.
[8] A. Ajayan, V. S. Kumari, F. A. Rahim, and S. S., \"Smart drip using Arduino microcontroller,\" Int. J. Comput. Sci. Eng., 2019.
[9] S. Mathi V, S. M. B, S. K, and N. D, \"Intravenous drip monitoring system using IoT,\" Int. J. Adv. Eng. Manag. (IJAEM), 2021.
[10] J.-K. Lee, K.-C. Yoon, and K. G. Kim, \"Design of a remote monitoring system based on optical sensors to prevent medical accidents during fluid treatment,\" Appl. Sci. Acad. J., 2021.
[11] M. R. Rosdi and A. Huong, \"A smart infusion pump system for remote management and monitoring of intravenous (IV) drips,\" in 11th IEEE Symp. Comput. Appl. Ind. Electron. (ISCAIE), 2021.
[12] S. Tanwar, D. K, R. Maniktalia, and R. Billa, \"IoT-based drip monitoring,\" in Commun. Netw. Technol. (ICCCNT), 2023.
[13] S. Joseph, N. Francis, A. John, B. Farha, and A. Baby, \"Intravenous drip monitoring system for smart hospital using IoT,\" in 2nd Int. Conf. Intell. Comput., Instrum. Control Technol. (ICICICT), 2020.
[14] A. Shetty, P. G., and A. Balasubramanyam, \"Smart IV bag monitoring and alert system,\" in 2023 Int. Conf. Recent Adv. Sci. Eng. Technol. (ICRASET), 2023.
[15] N. R. V., A. T., H. S. M., K. M., and S. H. M., \"Automatic saline reversal control system using IoT,\" in 2024 3rd Int. Conf. Intell. Techn. Control, Optim. Signal Process. (INCOS), 2024.
[16] M. Arfan, M. Srinivasan, A. G. Baragur, and V. Naveen, \"Design and development of IoT-enabled IV infusion rate monitoring and control device for precision care and portability,\" in 2020 4th Int. Conf. Electron., Commun. Aerosp. Technol. (ICECA), 2020.
[17] N. Sonkar, N. Pal, H. Gupta, and J. K. Dhanoa, \"Smart intravenous drip monitoring system with bubble detection indicator using IoT,\" in 2022 2nd Int. Conf. Intell. Technol. (CONIT), 2022.
[18] J. R. Arunkumar, R. Raman, S. Sivakumar, and R. Pavithra, \"Wearable devices for patient monitoring system using IoT,\" in 2023 8th Int. Conf. Commun. Electron. Syst. (ICCES), 2023.
[19] R. Kiruthika, E. Ramya, R. Prabha, M. Harinarayanan, S. Divakaran, and R. Iswariya, \"IoT-based patient monitoring system,\" in 2022 8th Int. Conf. Adv. Comput. Commun. Syst. (ICACCS), 2022.
[20] P. Anirudh, G. A. E. S. Kumar, R. P. Vidyadhar, G. Pranav, and B. A. Aumar, \"Automatic patient monitoring and alerting system based on IoT,\" in 2023 8th Int. Conf. Commun. Electron. Syst. (ICCES), 2023.
[21] M. S. Uddin, J. B. Alam, and S. Banu, \"Real-time patient monitoring system based on Internet of Things,\" in 2017 4th Int. Conf. Adv. Electr. Eng. (ICAEE), 2017.
[22] S. Amune, S. Chavanke, S. Joshi, S. Kuttarmare, and S. Kathane, \"Integrated healthcare system for saline monitoring, patient communication, and heart disease prediction using IoT and machine learning algorithms,\" in 2024 Int. Conf. Emerg. Smart Comput. Inform. (ESCI), 2024.
[23] M. R. K. K, M. N. M, R. Zidan, I. Alsarraj, and B. Hasan, \"IoT-based wireless patient monitor using ESP32 microcontroller,\" in 2023 24th Int. Arab Conf. Inf. Technol. (ACIT), 2023.
[24] D. G. V, D. Joshi, S. K. C, M. R. G, S. D, and M. Habeeb, \"Impact of IoT on remote patient monitoring and advancements in telemedicine,\" in 2024 2nd Int. Conf. Intell. Cyber Phys. Syst. Internet Things (ICoICI), 2024.
[25] A. A. Gnanadas, K. Indhumathi, M. Boopal, and R. S. Saranya, \"Internet of Things-based development of continuous saline monitoring and control system,\" in 2022 6th Int. Conf. Electron., Commun., Aerosp. Technol., 2022.
[26] Sharma, R., & Banoudha, A.. Implementation of N-Bit Divider using VHDL. International Journal of Research and Development in Applied Science and Engineering, 3(1).2013
[27] Srivastava, A., & Banoudha, A. Techniques of Visualization of Web Navigation System. . International Journal of Research and Development in Applied Science and Engineering, 6(1).2014