<![CDATA[The rapid advancement of digital technology in the healthcare sector has created an urgent need for faster, more precise, and more efficient patient care systems, particularly in managing intravenous (IV) therapy for hospitalized patients. A persistent challenge faced by many hospitals is the continued reliance on manual IV fluid monitoring by nursing staff, a practice that carries inherent risks of delayed fluid replacement and compromised patient safety. In response to this challenge, the present study undertakes the design and development of a smart IV monitoring system integrated with a nurse call feature, constructed upon the Internet of Things (IoT) paradigm and powered by Long Range (LoRa) wireless communication technology (Samsiana et al., 2024; Priyandoko, 2021).The architecture of the developed system comprises a patient-side node equipped with a load cell sensor for real-time IV fluid weight measurement and an infrared (IR) sensor for drip flow detection, complemented by a physical nurse call button enabling direct communication between patients and nursing personnel. Data acquired by each node is transmitted wirelessly via a LoRa module to an ESP32-based gateway, which processes the incoming data stream, converts it into JSON format, and relays it to a web server for visualization on a centralized monitoring dashboard. The study adopts a Research and Development (R&D) methodology with an experimental approach encompassing the phases of system design, hardware and software implementation, functional testing, and comprehensive performance evaluation (Pratama et al., 2021).Empirical testing conducted under both indoor and outdoor conditions confirms that the system operates reliably and stably across varying distances. The average response time recorded for IV status monitoring falls within the range of 9 to 12 seconds, while the nurse call feature demonstrates a considerably faster response time of approximately 1 to 5 seconds. LoRa-based communication proved robust for real-time data transmission, with latency increasing proportionally with distance. The findings substantiate that the proposed system holds significant potential to enhance IV monitoring efficiency, accelerate nursing staff response, and ultimately contribute to improved quality of care in hospital settings (Rohman et al., 2023; Rahmanto et al., 2025).]]>
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