Integrating smart technologies in healthcare enhances efficiency, reduces manual effort, and improves patient safety. This study introduces a hybrid smart saline monitoring system that uses weight-based sensing and Internet of Things connectivity to automate intravenous (IV) fluid management. An Arduino microcontroller and a load sensor continuously measure the saline weight and translate it into a level display with percentages (High, Medium, Low). The proposed system has a Wi-Fi module that sends real-time notifications to a mobile application and an auditory alert mechanism that uses a buzzer to notify medical staff in the nursing station in order to improve responsiveness. In order to avoid issues like air embolism, the device also includes a motor-controlled shut-off mechanism that immediately stops the flow of saline at critical low levels. Experimental evaluation demonstrates an average detection accuracy of ±5%, alert response time of 2–6 s, and stable 48-h continuous operation. The system is suitable for both centralized and resource-constrained medical facilities due to its price, dependability, and simplicity of integration. In this work, a completely automated, Internet of Things-enabled solution that improves IV fluid management and patient safety in contemporary healthcare is presented.

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Real-Time Saline Level Monitoring and Automated Management with an Arduino-Powered Smart System

  • Gargi Roy,
  • Debodyuti Upadhaya,
  • Anagha Bhattacharya,
  • Suparna Pal,
  • Shankar Das,
  • Sayan Ghosh

摘要

Integrating smart technologies in healthcare enhances efficiency, reduces manual effort, and improves patient safety. This study introduces a hybrid smart saline monitoring system that uses weight-based sensing and Internet of Things connectivity to automate intravenous (IV) fluid management. An Arduino microcontroller and a load sensor continuously measure the saline weight and translate it into a level display with percentages (High, Medium, Low). The proposed system has a Wi-Fi module that sends real-time notifications to a mobile application and an auditory alert mechanism that uses a buzzer to notify medical staff in the nursing station in order to improve responsiveness. In order to avoid issues like air embolism, the device also includes a motor-controlled shut-off mechanism that immediately stops the flow of saline at critical low levels. Experimental evaluation demonstrates an average detection accuracy of ±5%, alert response time of 2–6 s, and stable 48-h continuous operation. The system is suitable for both centralized and resource-constrained medical facilities due to its price, dependability, and simplicity of integration. In this work, a completely automated, Internet of Things-enabled solution that improves IV fluid management and patient safety in contemporary healthcare is presented.