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Towards Understanding Latent Relationships Among Uncollectible Garbage and City Demographics

Authors:
Koh Takeuchi
Takuro Yonezawa
Tomotaka Ito
Yasue Kishino
Yoshinari Shirai
Jin Nakazawa
Futoshi Naya
Naonori Ueda

Keywords: Participatory sensing, Data mining

Abstract:
We propose a preliminary work of a GIS-based participatory sensing system for collecting city information which works with a real-time collaboration of local government employees. With garbage management data collected by our application, we provide the running results of spatio-temporal data analysis that uncover the latent relationships among the spacial distributions of uncollectible garbage and city demographics. To discover such relationships, we conducted simple experiments that predicted the amount of uncollectible garbage from demographic and housing statistics by regularized linear regression methods and show that utilizing both population and housing statistics improved the predictive performance. We also report that the features of population and housing statistics, which are related to the lifestyles of citizens, greatly affect the amount of uncollectible garbage.

Pages: 11 to 15

Copyright: Copyright (c) IARIA, 2017

Publication date: June 25, 2017

Published in: conference

ISSN: 2519-8440

ISBN: 978-1-61208-569-2

Location: Venice, Italy

Dates: from June 25, 2017 to June 29, 2017