International Journal of Science, Engineering and TechnologyAuthors: Dr. Pankaj Malik, Ridima Sharma, Mansi Dubey, Manya Gautam, Vinayak Mishra
Abstract: Timely emergency medical care plays a crucial role in reducing mortality and improving patient outcomes. Conventional ambulance systems often suffer from delayed hospital communication, inefficient route selection, and limited patient monitoring during transportation. This paper presents an IoT-Enabled Smart Ambulance with Real-Time Hospital Communication Using Artificial Intelligence (AI) to enhance emergency healthcare services. The proposed system integrates IoT-based medical sensors, GPS tracking, cloud computing, and AI-driven analytics to continuously monitor patient vital parameters such as heart rate, blood pressure, oxygen saturation (SpO₂), and body temperature. These data are transmitted in real time to hospitals, enabling medical personnel to assess patient conditions and prepare appropriate treatment before arrival. The AI module performs patient severity classification, estimated time of arrival (ETA) prediction, hospital recommendation, and intelligent route optimization based on real-time traffic conditions. A cloud-based communication platform facilitates seamless information exchange between ambulance staff and healthcare providers. The system was evaluated using simulated emergency healthcare datasets and real-time traffic information. Experimental results demonstrate that the proposed framework reduces ambulance travel time by 28.4%, improves ETA prediction accuracy to 95.6%, and decreases hospital preparation delays by 41.7% compared with conventional ambulance systems. Furthermore, patient condition classification achieved an accuracy of 97.2%, enabling faster medical decision-making. The integrated IoT-AI architecture significantly improves emergency response efficiency, resource utilization, and patient survival probability. The proposed smart ambulance framework provides a scalable and intelligent solution for next-generation emergency healthcare systems and smart city applications.
DOI: http://doi.org/10.5281/zenodo.21028015
