Spatiotemporal correlation-based environmental monitoring system in energy harvesting internet of things (IoT)

Haneul Ko, Sangheon Pack, Victor C.M. Leung

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

To provide an accurate environmental map (EM) while avoiding unnecessary transmissions of Internet of Things (IoT) devices, we propose a spatiotemporal correlation-based environmental monitoring system (ST-EMS). In ST-EMS, IoT devices decide whether to transmit the sensed data to an IoT gateway (GW) or not by considering the temporal correlation in the sensed data and energy level. Through a Markov decision process (MDP) formulation, the optimal policy is obtained and it is proved that the optimal policy of MDP has an implementation-friendly threshold structure by using the submodularity concept. Also, the IoT GW in ST-EMS restores EM and improves its accuracy by exploiting the spatial correlation among sensed data using probabilistic matrix factorization. Evaluation results demonstrate that ST-EMS can improve the expected total reward significantly compared with other schemes and achieve low mean square error of 1% in EM restoration.

Original languageEnglish
Article number8588359
Pages (from-to)2958-2968
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Volume15
Issue number5
DOIs
Publication statusPublished - 2019 May

Bibliographical note

Funding Information:
Manuscript received July 19, 2018; revised November 12, 2018; accepted December 17, 2018. Date of publication December 25, 2018; date of current version May 2, 2019. This work was supported in part by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center Support Program under Grant IITP-2018-2017-0-01633 supervised by the Institute for Information and Communications Technology Promotion and in part by the National Research Foundation of Korea funded by the Korean Government (MSIP) under Grant 2017R1E1A1A01073742. Paper no. TII-18-1877. (Corresponding author: Sangheon Pack.) H. Ko is with the Department of Computer Convergence Software, Korea University, Sejong 30019, South Korea (e-mail:, st_basket@ korea.ac.kr).

Funding Information:
This work was supported in part by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center Support Program under Grant IITP-2018-2017-0-01633 supervised by the Institute for Information and Communications Technology Promotion and in part by the National Research Foundation of Korea funded by the Korean Government (MSIP) under Grant 2017R1E1A1A01073742.

Publisher Copyright:
© 2018 IEEE.

Keywords

  • Energy harvesting
  • Internet of Things (IoT)
  • Markov decision process (MDP)
  • monitoring service
  • probabilistic matrix factorization (PMF)
  • spatiotemporal correlation

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

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