A smart medical measurement system based on LoRa Mesh was designed to address the need for synchronized monitoring of physiological parameters and environmental factors in chronic disease management. The system employs the RadioHead protocol stack to achieve self-organized multi-hop mesh communication and is deployed within an endocrinology ward, integrating environmental sensing with patient health monitoring. Data from wearable terminals and environmental nodes are transmitted via LoRa modules to a central gateway and uploaded to a cloud server for storage and visualization. By extending the LoRaMeshSim simulation platform, the system was tested in a hospital scenario with 74 nodes distributed across 18 rooms and corridors, under varying payload lengths (30, 90, and 150 bytes) and transmission rates (1 to 26 packets per hour). Simulation results showed that the delivery rate remained above 99.5% when the packet generation rate was 1 packet per hour, but dropped to approximately 83.2% at 26 packets per hour. Moreover, increasing the packet length significantly elevated collision occurrences, with 150-byte packets encountering approximately 2.1 times more collisions than 30-byte packets. The analysis demonstrates that the proposed system maintains good stability and scalability under moderate to low data loads, while signal collisions and transceiver contention become critical challenges at higher loads. Future work will focus on introducing adaptive spreading factor adjustments and intelligent routing algorithms to further enhance the system’s reliability and energy efficiency. In addition, a small-scale LoRa Mesh network was physically deployed in a laboratory setting to experimentally validate the system’s communication reliability and practical applicability.