Smart Ambulance: A Comprehensive IoT and Cloud-Based System Integrating Fingerprint Sensor with Medical Sensors for Real-time Patient Vital Signs Monitoring

Authors

  • Amreen Ayesha Presidency University,Bangalore-560064, INDIA
  • C. Komalavalli Presidency University,Bangalore-560064, INDIA

Keywords:

Smart Ambulance, Internet of Things (IoT), Cloud-Based Healthcare, Fingerprint Sensors, Medical Sensors, Real-time Monitoring, Emergency Medical Services, Patient Care

Abstract

In response to the evolving landscape of emergency medical services, this research introduces the concept of a "Smart Ambulance," a transformative solution leveraging cutting-edge technologies. The proposed system is a comprehensive integration of the Internet of Things (IoT) and cloud-based architecture, seamlessly combining advanced fingerprint sensors with state-of-the-art medical sensors. The primary objective is to enable real-time monitoring of patient vital signs during transit, thus optimizing the delivery of emergency care. The Smart Ambulance operates as a connected platform, orchestrating a network of IoT devices for the continuous collection of real-time health data. Fingerprint sensors are incorporated to ensure secure and accurate patient identification, mitigating the risk of errors in medical record-keeping. The medical sensor array, integrated into the system, facilitates the simultaneous monitoring of various vital signs, including heart rate, blood pressure, and oxygen saturation, providing a comprehensive and dynamic assessment of the patient's health status. A pivotal component of the proposed system is its cloud-based infrastructure, offering scalability, accessibility, and real-time data analysis. Utilizing big data techniques, the collected information undergoes advanced analytics, empowering healthcare professionals with timely insights. Real-time communication is emphasized, fostering seamless interaction between the Smart Ambulance, healthcare professionals, and hospital systems. The user-friendly interface enhances the interpretability of patient data, ensuring effective decision-making by emergency response teams. The research delves into the detailed exploration of the system's architecture, implementation challenges, and future directions, contributing to the advancement of connected healthcare solutions. Overall, the Smart Ambulance system represents a paradigm shift in emergency medical services, promising heightened efficiency and improved patient outcomes.

Downloads

Download data is not yet available.

References

Ling, T., & Karim, A. (2019). IoT and cloud computing in smart ambulance services. In 2019 5th International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) (pp. 1287-1291). IEEE

Akter, F., & Alam, M. M. (2021). IoT-based smart ambulance system for accident detection and patient monitoring. In Proceedings of the International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-5). IEEE.

Singh, S., Agarwal, S., & Singh, R. (2020). Accident detection and emergency notification system using IoT and cloud computing. In 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE

Kumar, N., Barthwal, A., Lohani, D., & Acharya, D. (2020, March). Modeling iot enabled automotive system for accident detection and classification. In 2020 IEEE Sensors Applications Symposium (SAS) (pp. 1-6). IEEE

Rani, S., Chauhan, M., Kataria, A., & Khang, A. (2023). IoT equipped intelligent distributed framework for smart healthcare systems. In Towards the Integration of IoT, Cloud and Big Data: Services, Applications and Standards (pp. 97-114). Singapore: Springer Nature Singapore

Omotosho, A., Adegbola, O., Adelakin, B., Adelakun, A., & Emuoyibofarhe, J. (2015). Exploiting multimodal biometrics in e-privacy scheme for electronic health records. arXiv preprint arXiv:1502.01233

Maneshti, H., Dadashi, M., & Rostami, K. (2023). IoT-Enabled Low-Cost Fog Computing System with Online Machine Learning for Accurate and Low-Latency Heart Monitoring in Rural Healthcare Settings. arXiv preprint arXiv:2302.14131.

Mohammadi, F. G., Shenavarmasouleh, F., & Arabnia, H. R. (2022). Applications of machine learning in healthcare and internet of things (IOT): a comprehensive review. arXiv preprint arXiv:2202.02868.

Zrelli, R., Yeddes, M., & Hadj-Alouane, N. B. (2018). Checking and Enforcing Security through Opacity in Healthcare Applications. In Service-Oriented Computing–ICSOC 2017 Workshops: ASOCA, ISyCC, WESOACS, and Satellite Events, Málaga, Spain, November 13–16, 2017, Revised Selected Papers (pp. 161-173). Springer International Publishing

Dumka, A., & Sah, A. (2019). Smart ambulance system using concept of big data and internet of things. In Healthcare data analytics and management (pp. 155-176). Academic Press.

Tunc, M. A., Gures, E., & Shayea, I. (2021). A survey on iot smart healthcare: Emerging technologies, applications, challenges, and future trends. arXiv preprint arXiv:2109.02042.

Almadani, B., Bin-Yahya, M., & Shakshuki, E. M. (2015). E-AMBULANCE: real-time integration platform for heterogeneous medical telemetry system. Procedia Computer Science, 63, 400-407.

Chen, M., & Leung, V. C. (2018). From cloud-based communications to cognition-based communications: A computing perspective. Computer Communications, 128, 74-79.

Mahalakshmi, S., Ragunthar, T., Veena, N., Sumukha, S., & Deshkulkarni, P. R. (2022). Adaptive ambulance monitoring system using IOT. Measurement: Sensors, 24, 100555

Sutherland, M., & Chakrabortty, R. K. (2023). An optimal ambulance routing model using simulation based on patient medical severity. Healthcare Analytics, 100256

Siriwardena, K. L., Weerawardane, T. L., & Uwanthika, G. A. I. (2021). Cloud-Based Realtime Emergency Medical Service Platform.

Chan, M., Estève, D., Fourniols, J. Y., Escriba, C., & Campo, E. (2012). Smart wearable systems: Current status and future challenges. Artificial intelligence in medicine, 56(3), 137-156.

Sreelakshmy, R., Sruthy, R., Rajeshwari, R., & Thyla, B. (2022, July). Patient health monitoring system using smart IoT devices for medical emergency services. In 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES) (pp. 1-10). IEEE.

Dumka, A., & Sah, A. (2019). Smart ambulance system using concept of big data and internet of things. In Healthcare data analytics and management (pp. 155-176). Academic Press.

Singh, S., & Jain, R. (2021). A systematic review of accident detection and smart ambulance systems using IoT and cloud computing. In 2021 8th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 598-603). IEEE

Ayesha, A. & Chakravarthi, K. (2023). Smart Ambulances for IoT Based Accident Detection, Tracking and Response. Journal of Computer Science, 19(6), 677-685. https://doi.org/10.3844/jcssp.2023.677.685

Downloads

Published

25.12.2023

How to Cite

Ayesha, A. ., & Komalavalli, C. . (2023). Smart Ambulance: A Comprehensive IoT and Cloud-Based System Integrating Fingerprint Sensor with Medical Sensors for Real-time Patient Vital Signs Monitoring. International Journal of Intelligent Systems and Applications in Engineering, 12(2), 555–567. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4299

Issue

Section

Research Article