Cloud assisted big data information retrieval system for critical data supervision in disaster regions

Abstract

Presently, the advancement of Cloud Assisted Big Data information retrieval system(CABDIRS) for heterogeneous data management plays a significant role in disaster management framework. In the recent past, facilitating disaster related activities such as Emergency information collection, sharing of exposed insights data about the region, and integration with local groups as well as global scale across various communities’ need assistance for precise and timely information retrieval framework concerning about disaster management. However, the available information retrieval system in the market has limited invariant integration model, whereas it provides improper sharing and collaboration capabilities in dynamic environment about the disaster areas. Hence, this research driving this exploration for powerful use of Cloud assisted big data system which uses Regression based information retrieval measurable computational model (RBIRMM) that offers to foresee the collection, sharing and integration of data in the disaster management regions. This paper features the integration of Cloud assisted IoT(CIoT)and Big data system for information retrieval system which assist the government in taking decisions during disaster conditions in an effective fasten manner. This paper feature the fundamental research that moves through experimental validation which has been conducted and reported with numerical data in a virtual environment. The RBIRMM achieves 98% of accuracy when compared to other traditional methods.