CityFlow: Supporting Spatial-Temporal Edge Computing for Urban Machine Learning Applications

Makoto Kawano, Takuro Yonezawa, Tomoki Tanimura, Nam Ky Giang, Matthew Broadbent, Rodger Lea, Jin Nakazawa

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A growing trend in smart cities is the use of machine learning techniques to gather city data, formulate learning tasks and models, and use these to develop solutions to city problems. However, although these processes are sufficient for theoretical experiments, they often fail when they meet the reality of city data and processes, which by their very nature are highly distributed, heterogeneous, and exhibit high degrees of spatial and temporal variance. In order to address those problems, we have designed and implemented an integrated development environment called CityFlow that supports developing machine learning applications. With CityFlow, we can develop, deploy, and maintain machine learning applications easily by using an intuitive data flow model. To verify our approach, we conducted two case studies: deploying a road damage detection application to help monitor transport infrastructure and an automatic labeling application in support of a participatory sensing application. These applications show both the generic applicability of our approach, and its ease of use; both critical if we wish to deploy sophisticated ML based applications to smart cities.

Original languageEnglish
Title of host publicationEAI/Springer Innovations in Communication and Computing
PublisherSpringer Science and Business Media Deutschland GmbH
Pages3-15
Number of pages13
DOIs
Publication statusPublished - 2020

Publication series

NameEAI/Springer Innovations in Communication and Computing
ISSN (Print)2522-8595
ISSN (Electronic)2522-8609

Keywords

  • Edge processing
  • Participatory sensing
  • Road damage detection
  • Smart city
  • Urban computing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Electrical and Electronic Engineering
  • Health Informatics

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