Design and Implementation of an IoT-Based Intravenous Infusion Monitoring System Using Wireless Sensor Network
This research presents a Wireless Sensor Network (WSN) based infusion monitoring system that utilizes Internet of Things (IoT) technology to enhance infusion management in healthcare. Manual supervision often lacks the necessary accuracy and control, making automated solutions crucial. Our system employs optocoupler and load cell sensors to calculate the infusion drop rate per minute and assess the remaining fluid percentage. Tests conducted demonstrated that optocoupler sensors effectively measured the drop rate, while load cell sensors accurately determined fluid levels. Measurement results are easily monitored via smartphone, granting healthcare professionals rapid access to vital data. A key innovation of this system is its ability to enable remote monitoring through WSN, allowing a single nurse to oversee multiple infusions with just one smartphone. The test results indicate impressive accuracy, achieving an average precision rate of 97% for drop rate measurements and 93% for remaining fluid percentage measurements. Overall, this system offers an efficient and controlled approach to infusion fluid management, ensuring optimal care for patients. By integrating IoT and WSN technologies, this research lays the groundwork for developing more advanced and interconnected infusion monitoring systems, ultimately enhancing patient care in today's globalized healthcare environment.
Authors
- Yohandri Yohandri (ORCID: https://orcid.org/0000-0002-2884-3427)
- Yulkifli Yulkifli (ORCID: https://orcid.org/0000-0002-0909-6227)
- Aulia Asman (ORCID: https://orcid.org/0000-0001-5837-9306)
- Teguh Afrianda
Institutions
- State University of Malang (ID)
- State University of Padang (ID)
Publication Details
- Journal
- Applied Engineering, Innovation, and Technology
- Published
- 2024-10-06
- DOI
- https://doi.org/10.62777/aeit.v1i2.25
- Citations
- 2
- Primary Topic
- Fire Detection and Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.73