Applications of Big Data to smart cities are nearly limitless. However, challenges emerged with handling data with new magnitude of dimensionality, heterogeneity, required processing timeliness, and the lack of reported development experiences on how to turn Big Data into Smart Data may hinder the adoption of Big Data technologies in delivering smarter city services.This paper reports our experience in developing a Smart Big Data-centric software platform for tracking city performance. Here we examine how to design such a platform by exploiting architectural styles and open source technology for Big data management. We describe the actual development of an instance of it, the PELL Smart City Platform, for processing and managing urban data in the domain of public lighting. In particular, we focus on the formulation and evaluation of key performance indicators related to energy consumption to derive Smart Data from Big Data in the context of public street lighting.
(2021). From Big Data to Smart Data-centric Software Architectures for City Analytics: the case of the PELL Smart City Platform . Retrieved from http://hdl.handle.net/10446/202268
From Big Data to Smart Data-centric Software Architectures for City Analytics: the case of the PELL Smart City Platform
Ali, Mubashir;Scandurra, Patrizia;
2021-01-01
Abstract
Applications of Big Data to smart cities are nearly limitless. However, challenges emerged with handling data with new magnitude of dimensionality, heterogeneity, required processing timeliness, and the lack of reported development experiences on how to turn Big Data into Smart Data may hinder the adoption of Big Data technologies in delivering smarter city services.This paper reports our experience in developing a Smart Big Data-centric software platform for tracking city performance. Here we examine how to design such a platform by exploiting architectural styles and open source technology for Big data management. We describe the actual development of an instance of it, the PELL Smart City Platform, for processing and managing urban data in the domain of public lighting. In particular, we focus on the formulation and evaluation of key performance indicators related to energy consumption to derive Smart Data from Big Data in the context of public street lighting.File | Dimensione del file | Formato | |
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