Abstract
Creating technology enhanced optimized strategies to handle the subsequent healthcare issues emerged from natural calamities and disaster has now become more tranquil with the latest advancements in networking and low power electronics. Proposed system addresses an immediate action plan in accordance with the various adverse medical affronts during and post disaster events. The study focuses on developing strategies for disaster management in India, where flooding of rivers is one of the frequently occurring drastic event around the years in various regions resulting many people died due to unavailability of medical facilities. There are many studies conducted which proves that managing medical emergencies like cardiac seizure during such disasters where doctors unable to reach in these remotely affected areas due to damaged transportation systems by flood and they are struggling to provide prompt delivery of medical as well as relief to the remotely affected areas. Thus, it is gaining significant attention by disaster management organizations. Therefore, this study proposes a classic solution for handling various medical emergencies that occurs during and post disaster events. The system uses the drones to carry a weight of 1.5 kg to 2 kg medical kits to the affected areas. Miniaturized IoT based medical devices are designed with various Wireless Body Area Sensors (WBAS) and actuators. Along with a defibrillator unit and ECG analyzer. These medical kits are placed in a connected drone and this will drive to the affected areas aerially. All the devices are IoT enabled and are connected through the central cloud infrastructure of hospital by which medical experts can access the required medical parameters and convey the instructions through drone to a caretaker in real time to perform related events which may possibly postpone casualties.
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Aski, V., Raghavendra, S., Sharma, A.K. (2019). An Efficient Remote Disaster Management Technique Using IoT for Expeditious Medical Supplies to Affected Area: An Architectural Study and Implementation. In: Chertov, O., Mylovanov, T., Kondratenko, Y., Kacprzyk, J., Kreinovich, V., Stefanuk, V. (eds) Recent Developments in Data Science and Intelligent Analysis of Information. ICDSIAI 2018. Advances in Intelligent Systems and Computing, vol 836. Springer, Cham. https://doi.org/10.1007/978-3-319-97885-7_16
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