Programs
- M. Tech. in Automotive Engineering -Postgraduate
- Building Disaster Resilience and Social Responsibility through Experiential Learning: Integrating AI, GIS, and Remote Sensing -Certificate
Publication Type : Conference Paper
Publisher : IEEE
Source : 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA)
Url : https://doi.org/10.1109/icirca48905.2020.9183223
Campus : Mysuru
School : School of Computing
Year : 2020
Abstract : Natural calamities and disasters are incidents that lead to emergency healthcare situations. The healthcare data dissemination in such cases is a herculean task due to the absence of proper network and infrastructure. One of the popular solutions for data dissemination is to use an ad-hoc network. In this research work an ad-hoc network based on flying Unmanned Aerial Vehicles (UAVs) is considered which enhances the communication between remote locations and it makes an efficient data transmission. A communication is created between the Vehicular ad-hoc network (VANET), flying ad-hoc network (FANET), Mobile ad-hoc network (MANET) or mobile node using various intermediate nodes and one specific destination node. The receiver node is treated as an authorized hospital. The main purpose for this work is to improve the performance of data transmission when the distance between vehicular node (Ambulance) and the mobile node (Hospital) is high and vehicular node is not able to move because of traffic or natural calamities. The hospital works as mobile node because it is static, it is not moving like vehicles. Through this scenario the doctor will get the patient vitals through Wi-Fi in his mobile phone. To analyze the performance the scenario has been tested base on various metrics like Packet Delivery Ratio, Throughput, and Delay.
Cite this Research Publication : Adwitiya Mukhopadhyay, Dipan Ganguly, FANET based Emergency Healthcare Data Dissemination, 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA), IEEE, 2020, https://doi.org/10.1109/icirca48905.2020.9183223