Distributed and Heterogeneous Data Analysis for Smart Urban Planning

Abstract

Abstract. Over the past decade, 'smart' cities have capitalized on new technologies and insights to transform their systems, operations and services. The rationale behind the use of these technologies is that an evidence-based, analytical approach to decision-making will lead to more robust and sustainable outcomes. However, harvesting high-quality data from the dense network of sensors embedded in the urban infrastructure, and combining this data with social network data, poses many challenges. In this paper, we investigate the use of an intelligent middleware -Device Nimbus -to support data capture and analysis techniques to inform urban planning and design. We report results from a 'Living Campus' experiment at the University of Melbourne, Australia focused on a public learning space case study. Local perspectives, collected via crowd sourcing, are combined with distributed and heterogeneous environmental sensor data. Our analysis shows that Device Nimbus' data integration and intelligent modules provide highquality support for decision-making and planning.

Smart Campuses: Extensive Review of the Last Decade of Research and Current Challenges

“…They stressed the necessity of implementing a complete smart campus decision support system based on the actual situation of each department of the university to ensure a more convenient learning and working environment for teachers and students. Oliveira et al [167] reported the result of a living campus experiment at the University of Melbourne (Australia), in which an intelligent middleware platform supports capture of distributed and heterogeneous environmental sensor data in outdoor public learning spaces. The up-to-date information reporting the use those spaces and users' routine combined to local perspectives offers new opportunities for better management and improved tools for planning and policymaking.…”