Iot-based Saline Volume Monitoring and Alert System

Abstract: This project presents a comprehensive study on the design and implementationof an Internet of Things (IoT)-based system for monitoring and alerting salinevolumes in healthcare environments.Background: In healthcare settings, the accurate monitoring of saline volumesin Intravenous (IV) drip systems is crucial for ensuring patient safety and effectivetreatment. Traditional monitoring methods are labour-intensive and prone to human error. The IoT offers promising solutions for automating and enhancing themonitoring process.Objectives: This thesis aims to develop an IoT-based saline volume monitoring and alert system using NodeMCU, a load sensor, an amplifier, the ThingSpeakcloud platform, and the Massachusets Insitute of Technology (MIT) App Inventor.The system is designed to improve the accuracy and efficiency of saline volumemonitoring while reducing the burden on healthcare professionals.Methods: The proposal system employs a Node MicroController Unit (NodeMCU)microcontroller for data processing and communication, a load sensor for monitoring the saline volume, and a buzzer alarm and amplifier for alerting healthcareprofessionals when the saline volume reaches a critical threshold. The system connects to the ThingSpeak cloud platform for data storage and analysis, facilitatingremote monitoring and control through a custom mobile application developedusing MIT App Inventor.Results: The implementation and testing of the system showed accurate and reliable monitoring of saline volumes in real-time, with efficient alerting mechanisms.The user-friendly mobile application enabled healthcare professionals to monitormultiple IV drip systems simultaneously, receiving timely alerts when interventionwas required.Conclusions: The IoT-based saline volume monitoring and alert system demonstrates the potential to improve patient safety and healthcare efficiency. Furtherresearch and development can explore the integration of additional sensors, the refinement of the alert system, and the assessment of the system’s impact on clinicaloutcomes..