ANN Based Alarming of Multi Model Urban Emergency Events In Crowdsourcing to Social Media

Abstract

An urban emergency event is a sudden, urgent, usually unexpected incident or occurrence that requires an immediate reaction or assistance for emergency situations faced by social group or the recipients of public assistance . For example, the urban resident may face fires, storms, traffic jams and so on. The objective is to Alarming of urban emergency event in crowdsourcing to social media. Recently, social media feeds are rapidly emerging as a novel platform for providing and dissemination of information and they are interactive Web 2.0 internet-based application. It would be of great value given the fact that at least 50% some countries are unaware of their condition and will remain unaware until complications appear. In order to describe the real time urban emergency event, the 5W (What, Where, When, Who, and Why) model is proposed. The description of detected events is posted to social media. The proposed system is to fuse Artificial Neural Network (ANN) for filtering irrelevant information, alarming of event efficiently and for better accuracy .The consequence of this system to develop alarming of Multimodel (e.g.,text, image, videos) urban emergency events in crowdsourcing to social media.

Keywords: Crowdsourcing, bigdata, social media ,artificial neural network