Big Data Uses in Crowd Based Systems

Abstract

There are currently many trends in computer science, like Smart Cities, Internet of Things, and Wireless Sensor Networks. Many of these systems require or could dramatically benefit from having information about crowds. First of all, many of the systems are built to improve the life of people, and they require information about them to know when to activate their functionality in order to help them. Second, people represent a dynamic component of the entire systems, which is unpredictable. Measuring crowd dynamics is not an easy task. Each city consists of millions of individuals and their location needs to be known at all times. Furthermore, the other systems need to be able to extract the needed information for them to be able to function correctly while maintaining every individuals privacy. With crowd dynamic understood we open the way to the opportunity that is given by crowd sensing systems. Systems where data is gathered by sensors carried by individuals. Even more, crowd dynamic information can be supported by context, context that can be gathered from multiple sources, mostly available free on the Internet. With the vast amount of data on crowd dynamics and the context that surrounds them, the only option to extract information from these systems is given by Big Data. This is where Big Data meets crowd sensing. By having accurate, correct analysis of the crowd data and its context, the information extracted can be used by all other systems in order to be able to take smart decisions.