Spatial big data for disaster management

14th International Conference on Science, Engineering and Technology

自然科学;工业技术

Shalini, R.^1 ; Jayapratha, K.^1 ; Ayeshabanu, S.^1 ; Chemmalar Selvi, G.^1

School of Information Technology and Engineering, VIT University, Vellore

Tamil Nadu

632014, India^1

关键词: Classification and clustering;    Data mining algorithm;    Disaster management;    Geographic data;    Information protection;    Measure of information;    Sensor informations;    Time information;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/263/4/042008/pdf
DOI  :  10.1088/1757-899X/263/4/042008

来源: IOP

【 摘 要 】

Big data is an idea of informational collections that depicts huge measure of information and complex that conventional information preparing application program is lacking to manage them. Presently, big data is a widely known domain used in research, academic, and industries. It is utilized to store substantial measure of information in a solitary brought together one. Challenges integrate capture, allocation, analysis, information precise, visualization, distribution, interchange, delegation, inquiring, updating and information protection. In this digital world, to put away the information and recovering the data is enormous errand for the huge organizations and some time information ought to be misfortune due to circulated information putting away. For this issue the organization individuals are chosen to actualize the huge information to put away every one of the information identified with the organization they are put away in one enormous database that is known as large information. Remote sensor is a science getting data used to distinguish the items or break down the range from a separation. It is anything but difficult to discover the question effortlessly with the sensor. It makes geographic data from satellite and sensor information so in this paper dissect what are the structures are utilized for remote sensor in huge information and how the engineering is vary from each other and how they are identify with our investigations. This paper depicts how the calamity happens and figuring consequence of informational collection. And applied a seismic informational collection to compute the tremor calamity in view of classification and clustering strategy. The classical data mining algorithms for classification used are k-nearest, naive bayes and decision table and clustering used are hierarchical, make density based and simple k-means using XLMINER and WEKA tool. This paper also helps to predicts the spatial dataset by applying the XLMINER AND WEKA tool and thus the big spatial data can be well suited to this paper.