Cruisers: An automotive sensing platform for smart cities using door-to-door garbage collecting trucks

Yin Chen, Jin Nakazawa, Takuro Yonezawa, Hideyuki Tokuda

Research output: Contribution to journalArticle

Abstract

Due to the advance in information and communication technologies, smart cities have become an increasingly appealing vision. One indispensable basis in the research, development and implementation of smart cities is urban sensing technology. Automotive sensing is a novel urban sensing technology that equips sensors to vehicles, like buses, taxi cabs or garbage trucks and utilizes their mobility to help to conduct urban sensing tasks. In this paper, we present Cruisers, an automotive sensing platform for smart cities, based on the following ideas: a) Garbage collecting trucks are used to host sensors, b) Cellular communication network is used to deliver sensed data to servers, and c) Proxy server(s) are adopted to convert the format of sensed data to required ones, such as sampling rate, spatial interval or pub/sub protocol. To validate the feasibility of Cruisers, we implement a real system that consists of 66 customized sensing modulars integrating typical environmental and mobility sensors and deploy them into the garbage collecting trucks at Fujisawa, a medium-sized city in Japan. Performance evaluation is conducted to investigate the performance of Cruisers in terms of scalability, data publishing delay and spatial coverage.

LanguageEnglish
Pages32-45
Number of pages14
JournalAd Hoc Networks
Volume85
DOIs
Publication statusPublished - 2019 Mar 15

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Trucks
Garbage trucks
Cabs (truck)
Sensors
Servers
Cellular radio systems
Telecommunication networks
Scalability
Sampling
Network protocols
Communication
Smart city

Keywords

  • Automotive sensing
  • Smart cities
  • Urban sensing

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Cruisers : An automotive sensing platform for smart cities using door-to-door garbage collecting trucks. / Chen, Yin; Nakazawa, Jin; Yonezawa, Takuro; Tokuda, Hideyuki.

In: Ad Hoc Networks, Vol. 85, 15.03.2019, p. 32-45.

Research output: Contribution to journalArticle

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