Big Data GIS Analytics Towards Efficient Waste Management in Stockholm

DOI

10.2991/ict4s-14.2014.17How to use a DOI?

Keywords

Big Data Analytics, GIS, Smart Cities, Transportation, Waste Management

Abstract

This paper presents preliminary findings from a big data analysis and GIS to identify the efficiency of waste management and transportation in the City of Stockholm. The aim of this paper is to identify inefficiencies in waste collection routes in the city of Stockholm, and to suggest potential improvements. Based on a large data set consisting of roughly half a million entries of waste fractions, weights, and locations, a series of new waste generation maps was developed. This was the outcome of an extensive data curation process, followed by batch geocoding of the curated entries. Thereafter, the maps were generated that describe what waste fraction comes from where and how it is collected. Finally, a preliminary analysis of the route efficiency was conducted. Maps of selected vehicle routes were constructed in detail and the efficiencies of the routes for the first half of July 2013 were assessed using the efficiency index (kg waste/km). It is concluded that substantial inefficiencies were revealed, and a number of intervention measures are discussed to increase the efficiency of waste management, including a shared waste collection vehicle fleet.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hossein Shahrokni
AU  - Bram Van der Heijde
AU  - David Lazarevic
AU  - Nils Brandt
PY  - 2014/08
DA  - 2014/08
TI  - Big Data GIS Analytics Towards Efficient Waste Management in Stockholm
BT  - Proceedings of the 2014 conference ICT for Sustainability
PB  - Atlantis Press
SP  - 140
EP  - 147
SN  - 2352-538X
UR  - https://doi.org/10.2991/ict4s-14.2014.17
DO  - 10.2991/ict4s-14.2014.17
ID  - Shahrokni2014/08
ER  -