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Stream/Area:
-
Subject:
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Paper ID:
IJSREM62317
Volume:
10 |
5 |
May 2026
Pages:
1-14
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Artificial Intelligence and Data Science
United Institute of Technology
Artificial Intelligence and Data Science
United Institute of Technology
Artificial Intelligence and Data Science
United Institute of Technology
Artificial Intelligence and Data Science
United Institute of Technology
Artificial Intelligence and Data Science
United Institute of Technology
In modern healthcare facilities, intravenous (IV) fluid administration is a standard procedure that requires vigilant monitoring. Traditional manual supervision of saline levels by nursing staff is labor-intensive and susceptible to human error, potentially leading to critical risks such as vascular air embolism or blood backflow into the IV tube. This paper presents the design and implementation of a cost-effective, real-time "Smart Saline Level Detection System" utilizing a strain-gauge load cell and the ESP8266 microcontroller. The system leverages the principle of gravimetric analysis; a 24-bit HX711 analog-to-digital converter (ADC) interfaces with the load cell to convert weight-induced millivolt signals into digital data with high precision. The ESP8266 processes this data to calculate the remaining saline percentage, which is displayed locally on a 16x2 I2C LCD. A dual-threshold alert mechanism is implemented: a pre-warning beep at 20% and a continuous audible alarm at 10% to ensure timely intervention. Experimental results demonstrate a measurement accuracy of ± 2.0 g and a linear response (R^2≈0.99), confirming the system's reliability in a clinical environment. By automating the monitoring process, the proposed solution minimizes the workload of healthcare professionals and significantly enhances patient safety through real-time feedback and IoT-ready architecture.
KEYWORDS
Compared to Infrared (IR) based drip-rate monitors, our gravimetric system proved more reliable as it does not suffer from "drop-count errors" caused by condensation inside the drip chamber or fluctuations in fluid viscosity. By measuring the total mass, the system provides a more holistic view of the remaining treatment time.
[1] S. R. Jino Ramson and S. Vishnu, "A review on pervasive healthcare monitoring system," 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, India, 2017, pp. 244-249. [2] M. S. J. Devi and G. S. Karthick, "Smart Nursing: IoT Based Saline Level Monitoring System," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 5, no. 2, pp. 112-116, 2019. [3] R. Kumar and M. Pallikonda Rajasekaran, "IoT Based Low Cost Automated Saline Level Monitoring System," Journal of Physics: Conference Series, vol. 1716, no. 1, 2020. [4] S. Pradeep and R. S. Sandhya Devi, "Weight based saline level monitoring system using Load cell and ESP8266," International Journal of Engineering Research & Technology (IJERT), vol. 8, no. 6, 2019. [5] K. S. Shaji and A. Sebastian, "Automated Intravenous Fluid Monitoring System: A Review," International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, vol. 6, no. 3, pp. 45-49, 2018. [6] Avinash Singh, et al., "Implementation of a Smart Healthcare System for Saline Level Monitoring," IEEE Xplore - 2nd International Conference on Computing and Communications Technologies, 2021. [7] HX711 Datasheet, "24-Bit Analog-to-Digital Converter (ADC) for Weigh Scales," Avia Semiconductor, [Online]. Available: http://www.aviaic.com. [8] ESP8266EX Datasheet, "Highly Integrated Wi-Fi SoC," Espressif Systems, [Online]. Available: https://www.espressif.com.
Publication Date
5/2/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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