Author
Listed:
- Tai Wei Cheng
(School Of Mechanical Engineering, Engineering Campus, University Sains Malaysia, 14300, Nibong Tebal, Pulau Pinang, Malaysia)
- Ahmad Syazwan Ahmad Kamal
(School Of Mechanical Engineering, Engineering Campus, University Sains Malaysia, 14300, Nibong Tebal, Pulau Pinang, Malaysia)
- Law Kim Sooi
(Division Of Nursing Services, Pusat Perubatan Usm Bertam, University Sains Malaysia, Kepala Batas, 13200 Pulau Pinang, Malaysia)
- Syamimi Shamsuddin
(Department Of Community Health, Advanced Medical and Dental Institute, University Sains Malaysia, Kepala Batas, 13200 Pulau Pinang, Malaysia)
Abstract
The healthcare industry continues to struggle with manpower shortages, a challenge that is particularly severe in Malaysia, where only 5% of public hospitals have adequate staffing. To address this issue, researchers have explored the use of the Internet of Things (IoT) in healthcare to improve patient monitoring efficiency, yielding promising results. This study aims to design and develop an IoT-based smart intravenous (IV) therapy monitoring system to help mitigate the manpower shortage in Malaysia’s healthcare sector. The system provides real-time monitoring of IV therapy status and sends alerts to nurses remotely, reducing the need for frequent bedside visits. The study follows a machine design approach, encompassing the development of mechanical components, electrical circuits, and firmware. A three-layer cloud-based architecture, supported by the Blynk IoT platform, was implemented, with the ESP32 microcontroller enabling wireless connectivity. Cost-effective sensors and components were integrated to ensure economic feasibility. The prototype successfully streams real-time transfusion data to remote devices via the Blynk IoT platform and notifies users when intervention is needed, such as when the fluid level drops below a set threshold. In conclusion, this study successfully developed a low cost, IoT-enabled smart IV therapy monitoring system that enhances patient monitoring efficiency while reducing the burden on healthcare staff. Future work will focus on improving system reliability, adding more features, and testing it in hospitals.
Suggested Citation
Tai Wei Cheng & Ahmad Syazwan Ahmad Kamal & Law Kim Sooi & Syamimi Shamsuddin, 2025.
"Iot-Based Smart Intravenous Therapy System,"
International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(2), pages 2535-2547, February.
Handle:
RePEc:bcp:journl:v:9:y:2025:issue-2:p:2535-2547
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