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Smart Sensing with Edge Computing in Precision Agriculture for Soil Assessment and Heavy Metal Monitoring: A Review

Author

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  • Mohammad Nishat Akhtar

    (School of Aerospace Engineering, Universiti Sains Malaysia, Nibong Tebal 14300, Malaysia)

  • Abdurrahman Javid Shaikh

    (Department of Electrical Engineering, NED University of Engineering and Technology, Karachi 75270, Pakistan)

  • Ambareen Khan

    (School of Aerospace Engineering, Universiti Sains Malaysia, Nibong Tebal 14300, Malaysia)

  • Habib Awais

    (Department of Textile Engineering, National Textile University, Faisalabad 37610, Pakistan)

  • Elmi Abu Bakar

    (School of Aerospace Engineering, Universiti Sains Malaysia, Nibong Tebal 14300, Malaysia)

  • Abdul Rahim Othman

    (Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Malaysia)

Abstract

With the implementation of the Internet of Things, the agricultural domain has become data-driven, allowing for well-timed and cost-effective farm management while remaining environmentally sustainable. Thus, the incorporation of Internet of Things in the agricultural domain is the need of the hour for developing countries whose gross domestic product primarily depends on the farming sector. It is worth highlighting that developing nations lack the infrastructure for precision agriculture; therefore, it has become necessary to come up with a methodological paradigm which can accommodate a complete model to connect ground sensors to the compute nodes in a cost-effective way by keeping the data processing limitations and constraints in consideration. In this regard, this review puts forward an overview of the state-of-the-art technologies deployed in precision agriculture for soil assessment and pollutant monitoring with respect to heavy metal in agricultural soil using various sensors. Secondly, this manuscript illustrates the processing of data generated from the sensors. In this regard, an optimized method of data processing derived from cloud computing has been shown, which is called edge computing. In addition to this, a new model of high-performance-based edge computing is also shown for efficient offloading of data with smooth workflow optimization. In a nutshell, this manuscript aims to open a new corridor for the farming sector in developing nations by tackling challenges and providing substantial consideration.

Suggested Citation

  • Mohammad Nishat Akhtar & Abdurrahman Javid Shaikh & Ambareen Khan & Habib Awais & Elmi Abu Bakar & Abdul Rahim Othman, 2021. "Smart Sensing with Edge Computing in Precision Agriculture for Soil Assessment and Heavy Metal Monitoring: A Review," Agriculture, MDPI, vol. 11(6), pages 1-37, May.
  • Handle: RePEc:gam:jagris:v:11:y:2021:i:6:p:475-:d:559824
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    References listed on IDEAS

    as
    1. Stočes, Michal & Vaněk, Jiří & Masner, Jan & Pavlík, J., 2016. "Internet of Things (IoT) in Agriculture - Selected Aspects," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 8(1), pages 1-6, March.
    2. Heena Panchasara & Nahidul Hoque Samrat & Nahina Islam, 2021. "Greenhouse Gas Emissions Trends and Mitigation Measures in Australian Agriculture Sector—A Review," Agriculture, MDPI, vol. 11(2), pages 1-16, January.
    3. Marinela Ilie, 2018. "Internet of things in agriculture," International Conference on Competitiveness of Agro-food and Environmental Economy Proceedings, The Bucharest University of Economic Studies, vol. 7, pages 157-166.
    4. Bifeng Hu & Songchao Chen & Jie Hu & Fang Xia & Junfeng Xu & Yan Li & Zhou Shi, 2017. "Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
    5. Nicholson, Charles F. & Stephens, Emma C. & Kopainsky, Birgit & Thornton, Philip K. & Jones, Andrew D. & Parsons, David & Garrett, James, 2021. "Food security outcomes in agricultural systems models: Case examples and priority information needs," Agricultural Systems, Elsevier, vol. 188(C).
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    Cited by:

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    2. Johan J. Estrada-López & Javier Vázquez-Castillo & Andrea Castillo-Atoche & Edith Osorio-de-la-Rosa & Julio Heredia-Lozano & Alejandro Castillo-Atoche, 2023. "A Sustainable Forage-Grass-Power Fuel Cell Solution for Edge-Computing Wireless Sensing Processing in Agriculture 4.0 Applications," Energies, MDPI, vol. 16(7), pages 1-17, March.

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