Data Offloading for Effective Rescue Operations During Fire Disaster Management
Kayiram Kavitha1, R.V.S.Lalitha2, J.Bhargavi Latha3, T.V.Suneetha4

1Dr. Kayiram Kavitha, Associate Professor, GRIET, Hyderabad, Telangana, India.
2Dr. R.V.S. Lalitha, Professor, Aditya College of Engineering, Kakinada, Andhra Pradesh, India.
2J. Bhargavi Latha, Assistant Professor, GRIET, Hyderabad, Telangana, India. T.V. Suneetha, Assistant Professor, GRIET, Hyderabad, Telangana, India.
Manuscript received on September 13, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 5319-5321 | Volume-9 Issue-1, October 2019 | Retrieval Number: A2965109119/2019©BEIESP | DOI: 10.35940/ijeat.A1347.109119
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Abstract: Disasters such as fire, earthquake and tsunami, etc. often result in precious loss of life as well as pose great economic challenge to developing countries like India. Of late, fires in moving vehicles such as trains and buses have become very common in India leading to loss of life and property. As we cannot predict or control the disaster, we can at least make efforts in minimising loss and some effective rescue operations post disaster. It is very important to perform post disaster analysis of the event to have better rescue operations and also to analyse the reason behind the occurrence of such disaster if possible. So that if it is man-made disaster preventive measures could be prescribed in future. Many Wireless Sensor Networks were proposed in the past for disaster management. But, fire leaves the network disconnected and important data is left unused in the damaged network. So, we propose Internet of Things (IoT) which is a promising technology that can be used to solve some of the problems mentioned above. To date, the application of IoT in post-disaster management is still an unexplored problem. In this paper, we propose data offloading mechanism for effective rescue operations post disaster from damaged network. The network is partially damaged in case of disaster and using fog computing we retrieve data and transfer to cloud for better data analytics. We propose a data flow framework built for effective post-disaster management.
Keywords: Disaster management, Fire, Wireless Sensor Networks, Fog computing, Crowd sourcing, data offloading.