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When mobile crowd sensing meets smart agriculture: poster

Published: 17 May 2019 Publication History

Abstract

A new paradigm of mobile crowd sensing towards smart agriculture is termed Agricultural Mobile Crowd Sensing (AMCS). The AMCS is intended to improve the existing agricultural data collection system and facilitate the realization of smart agriculture. The comparative analysis between Space-Air-Ground Integrated Network and the AMCS is presented, regarding the cost, range of data collection, scalability, data granularity and flexibility. Finally, the conclusions and prospects are discussed.

References

[1]
Raghu K. Ganti, Fan Ye, and Hui Lei. 2011. Mobile Crowd Sensing: Current State and Future Challenges. IEEE Communications Magazine 49, 11 (Nov. 2011), 32--39.
[2]
Shu Lei, Yuanfang Chen, Zhiqiang Huo, Neil Bergmann, and Wang Lei. 2017. When Mobile Crowd Sensing Meets Traditional Industr. IEEE Access 5 (May 2017), 15300--15307.
[3]
Jiajia Liu, Yongpeng Shi, Zubair Md. Fadlullah, and Nei Kato. 2018. Space-Air-Ground Integrated Network: A Survey. IEEE Communications Surveys & Tutorials 20, 4 (May 2018), 2714--2741.
[4]
Sjaak Wolfert, Lan Ge, Cor Verdouw, and Marc Jeroen Bogaardt. 2017. Big Data in Smart Farming C A review. Agricultural Systems 153 (Feb. 2017), 69--80.

Cited By

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  • (2023)Data Quality in Human-Centric Sensing-Based Next-Generation IoT Systems: A Comprehensive Survey of Models, Issues, and ChallengesIEEE Open Journal of the Communications Society10.1109/OJCOMS.2023.33161184(2286-2317)Online publication date: 2023
  • (2022)On Enabling Mobile Crowd Sensing for Data Collection in Smart Agriculture: A VisionIEEE Systems Journal10.1109/JSYST.2021.310410716:1(132-143)Online publication date: Mar-2022
  • (2021)Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging TechnologiesIEEE/CAA Journal of Automatica Sinica10.1109/JAS.2021.10039258:4(718-752)Online publication date: Apr-2021
  • Show More Cited By

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ACM TURC '19: Proceedings of the ACM Turing Celebration Conference - China
May 2019
963 pages
ISBN:9781450371582
DOI:10.1145/3321408
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 May 2019

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Author Tags

  1. data collecting
  2. mobile crowd sensing
  3. smart agriculture

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View all
  • (2023)Data Quality in Human-Centric Sensing-Based Next-Generation IoT Systems: A Comprehensive Survey of Models, Issues, and ChallengesIEEE Open Journal of the Communications Society10.1109/OJCOMS.2023.33161184(2286-2317)Online publication date: 2023
  • (2022)On Enabling Mobile Crowd Sensing for Data Collection in Smart Agriculture: A VisionIEEE Systems Journal10.1109/JSYST.2021.310410716:1(132-143)Online publication date: Mar-2022
  • (2021)Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging TechnologiesIEEE/CAA Journal of Automatica Sinica10.1109/JAS.2021.10039258:4(718-752)Online publication date: Apr-2021
  • (2021)A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy ChallengesIEEE/CAA Journal of Automatica Sinica10.1109/JAS.2020.10035368:2(273-302)Online publication date: Feb-2021

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