| Title |
Smart Waste Collection System Based on Location Intelligence |
| ID_Doc |
41853 |
| Authors |
Gutierrez, JM; Jensen, M; Henius, M; Riaz, T |
| Title |
Smart Waste Collection System Based on Location Intelligence |
| Year |
2015 |
| Published |
|
| DOI |
10.1016/j.procs.2015.09.170 |
| Abstract |
Cities around the world are on the run to become smarter. Some of these have seen an opportunity on deploying dedicated municipal access networks to support all types of city management and maintenance services requiring a data connection. This paper practically demonstrates how Internet of Things (IoT) integration with data access networks, Geographic Information Systems (GIS), combinatorial optimization, and electronic engineering can contribute to improve cities' management systems. We present a waste collection solution based on providing intelligence to trashcans, by using an IoT prototype embedded with sensors, which can read, collect, and transmit trash volume data over the Internet. This data put into a spatio-temporal context and processed by graph theory optimization algorithms can be used to dynamically and efficiently manage waste collection strategies. Experiments are carried out to investigate the benefits of such a system, in comparison to a traditional sectorial waste collection approaches, also including economic factors. A realistic scenario is set up by using Open Data from the city of Copenhagen, highlighting the opportunities created by this type of initiatives for third parties to contribute and develop Smart city solutions. (C) 2015 The Authors. Published by Elsevier B.V. |
| Author Keywords |
Location Intelligence; Smart City; Internet of Things; Graph Optimization; Dynamic Logistic Management |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000373845000017 |
| WoS Category |
Computer Science, Information Systems; Computer Science, Theory & Methods |
| Research Area |
Computer Science |
| PDF |
https://doi.org/10.1016/j.procs.2015.09.170
|