Smart sensing with edge computing in precision agriculture for soil assessment and heavy metal monitoring: A review

Akhtar, M.N. and Shaikh, A.J. and Khan, A. and Awais, H. and Bakar, E.A. and Othman, A.R. (2021) Smart sensing with edge computing in precision agriculture for soil assessment and heavy metal monitoring: A review. Agriculture (Switzerland), 11 (6). ISSN 20770472

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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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Item Type: Article
Additional Information: cited By 26
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 10 Nov 2023 03:29
Last Modified: 10 Nov 2023 03:29
URI: https://khub.utp.edu.my/scholars/id/eprint/14870

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