Multi-agent Approach to Analysis Data from Social Media for Building Smart Cities

Abstract

With the objective of reducing costs and resource consumption in addition to more effectively and actively engaging with their citizens, smart cities can use multiple technologies to improve the performance of the business, health, transportation, energy, education, and electric and water services leading to higher levels of comfort of their citizens. One of the recent technologies that have a huge potential to enhance smart city services is social big data analytics. Also, one of the current main challenges in data mining related to big data problems is to find adequate approaches to analyzing huge amounts of data. As we know, a social media become an important part of everyday life of people and collected data has resulted in the accumulation of huge amounts of data that can be used in various beneficial application domains. Effective analysis and utilization of social big data is a key factor for success in many service domains of the smart cities. Thus, we think that for building smart cities, we have to hear what citizens talk in social media about parking, lighting, incidents, waste and many others. In this paper, we will review the utilization of social big data to build of smart cities. And, we will propose a smart model which permits to analyze huge data collected from the social networks to predict future events, as crime, incidents and public opinions for politic or business purposes. In addition, we will identify the requirements that support the implementation of big data applications for smart city services. Finally, we implement our smart model.