RF-Triggered Motorized Stretcher Dispatch with in-Transit Vital-Sign Telemetry for Shortening Ambulance-to-ICU Hand-Off
Keywords:
Ambulance monitoring, Automated stretcher, Emergency medical services, Internet of Things, Radio-frequency communicationAbstract
A road medical emergency is governed by two separate delays: how long the ambulance takes to reach the hospital, and how long the patient then spends being handed over from the ambulance to the intensive care unit (ICU). This paper targets the second of these by building and bench-testing a low-cost Internet of Things (IoT) system that pairs an ambulance-side patient-monitoring kit with an automated, radio-triggered stretcher. An Arduino UNO-based acquisition unit reads a patient's heart rate, blood-oxygen saturation (SpO2), and body temperature throughout transit and pushes the readings to a ThingSpeak cloud dashboard over an ESP8266/ESP01 Wi-Fi link, letting ward staff see the incoming patient's condition before the vehicle arrives. Separately, a 433 MHz radio-frequency (RF) link between the ambulance kit and a NodeMCU-controlled motorized stretcher detects ambulance proximity and releases the stretcher toward the drop-off point, removing the need for staff to fetch it manually. A working prototype of both units was built; ten consecutive vital-sign samples logged at 10-second intervals confirm sensor consistency, and the RF-triggered drive actuated reliably across bench trials. The design is then discussed against 2023–2026 developments in acoustic and AI-based ambulance detection, connected-vehicle signal preemption, and autonomous in-hospital patient-transport robots, closing with a roadmap toward obstacle-aware navigation and city-scale green-corridor integration.
References
W. R. Salem Jeyaseelan, R. Krishnan, M. Arunkumar, and P. Alagarsamy, “Efficient intelligent smart ambulance transportation system using Internet of Things,” Tehnički Vjesnik, vol. 31, no. 1, pp. 171-177, 2024.
C. Selvan, B. H. Anwar, S. Naveen, and S. T. Bhanu, “Ambulance route optimization in a mobile ambulance dispatch system using deep neural network (DNN),” Scientific Reports, vol. 15, Art. no. 14232, Apr. 2025.
R. Narasimhan, S. Krishnan, S. S. Sivaprakasam, and S. Madheswaran, “Smart ambulance and health monitoring system based on IoT for smart city,” in Advances in Intelligent Systems and Computing, vol. 843. Singapore: Springer, 2019, pp. 151-159.
M. A. R. Abdeen, M. H. Ahmed, H. Seliem, T. R. Sheltami, T. M. Alghamdi, and M. El-Nainay, “A novel smart ambulance system—Algorithm design, modeling, and performance analysis,” IEEE Access, vol. 10, pp. 42656-42672, 2022.
J. K. Patra, P. S. Satsangi, and N. V. Rao, “An intelligent ambulance system for emergency medical services using IoT and fog computing,” in Proceedings 2020 4th International Conference on Inventive Computation Technologies (ICICT), Coimbatore, India, 2020, pp. 1-5.
D. Pramanick, H. Ansar, H. Kumar, S. Pranav, R. Tengshe, and B. Fatimah, “Deep learning based urban sound classification and ambulance siren detector using spectrogram,” in Proceedings 12th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Kharagpur, India, 2021, pp. 1-6.
Y. Kavitha, P. Satyanarayana, and S. S. Mirza, “Sensor based traffic signal pre-emption for emergency vehicles using efficient short-range communication network,” Measurement: Sensors, vol. 28, Aug. 2023.
S. Krishnaraju et al., “Automated signal pre-emption system for emergency vehicles using internet of things,” IAES International Journal Artificial Intelligence (IJ-AI), vol. 13, no. 1, pp. 899-908, Mar. 2024.
Y.-Y. Chen, J.-Y. Wang, S.-C. Lo, and W.-T. Sung, “An emergency vehicle traffic signal preemption system considering queue spillbacks along routes and negative impacts on non-priority traffic,” IET Intelligent Transport Systems, vol. 18, no. 8, pp. 1385-1395, Aug. 2024.
Government Fleet, “Smarter traffic signals: Reducing response times and improving transit reliability,” Government Fleet, Feb. 2025.
A. Mishra et al., “Revolutionising health monitoring: IoT-based system with machine learning classification,” Health Systems (Basingstoke), vol. 14, no. 4, pp. 291-306, May 2025.
A. Tripathi, “Photos: US firm claims ‘world’s first’ autonomous in-hospital patient transport robot,” Interesting Engineering, May 23, 2026.
B. Wang, S. Chen, and G. Xiao, “Advancing healthcare through mobile collaboration: a survey of intelligent nursing robots research,” Frontiers in Public Health, vol. 12, Nov. 2024.
H. Shin et al., “A Comprehensive Review of Autonomous Mobile Robots in Healthcare: Implications for Patient-Transporting Human-Following Robots,” Robotics, vol. 14, no. 12, p. 179, Nov. 2025.
A. R. Baltazar, M. R. Petry, M. F. Silva, and A. P. Moreira, “Autonomous wheelchair for patient's transportation on healthcare institutions,” SN Applied Science, vol. 3, Feb. 2021.
