Smart City Services Monitoring Framework using Fuzzy Logic Based Sentiment Analysis and Apache Spark

Abstract

Smart city technologies are reshaping our everyday life. New application and systems architectures appears to enhance information and communications technologies, allowing cities to harness their resources more intelligently, also to include citizens in the development of their environments by analyzing the tremendous amount of data generated by people, which cover wide diversity of domains, thus, providing valuable contribution to tackle environmental and socio-economic problems efficiently. The problem encountered under these circumstances is that continuously analyzing users content, especially text content to extract expressed sentiment in real-time is a challenging task that needs scalable and high performance distributed systems, also the opinion of a person concerning a particular city service, politic decision or even a street reputation may not be binary, e.g., positive or negative, due to the fuzzy character of our language. To this end we propose an architecture that will take advantage of distributed and streaming computing framework combined with applying fuzzy logic to classify expressed sentiments in real time, thus to offer insight to city governance and to expand citizen participation in the evolution of their cities.