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      Designing and modeling an IoT-based software system for land suitability assessment use case

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          Abstract

          Assessing the quality of land is a very important step that precedes the planning of land use and taking management decisions; for example, in the agricultural field, it can be used to evaluate the suitability of the land for planting crops, determine the suitable irrigation system type, or adjust the agricultural inputs such as fertilizers and pesticides according to the requirements of each zone in the land. The spatial–temporal dynamic nature of land characteristics entails also updated evaluation process and updated management plan. The present paper tries to exploit the advances in information and communication technologies to develop a conceptual design of a dynamic system that accommodates the spatial–temporal dynamics of the agricultural soil characteristics to realize a land suitability assessment (LSA) based on a factor analysis method. The proposed design combines IoT technologies, web development, database, and digital mapping and tries to consolidate the system with other functionalities useful for decision support and suitable for different cases. The paper conducted a survey and made comparisons to select the best technologies that fit the current use case implementation and presents its reproducible conceptual modeling by developing the static and dynamic views through schemas, diagrams, message sequence charts, IoT messaging topic tree, pseudocode, etc. The functionality of the design was validated with a simple implementation of the system model. To our knowledge, there is no previous significant contribution that has addressed a LSA IoT use case. The proposed design automates the LSA process for more accurate decision-making, saving cost, time, and effort consumed in repeated field trips. It is characterized by flexibility and centralization in its offered services of spatial analysis, detection, visualizations, and status monitoring. The design also allows for remote control of field machinery.

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          Most cited references27

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          IoT Middleware: A Survey on Issues and Enabling technologies

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            Connecting Intelligent Things in Smart Hospitals Using NB-IoT

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              Sensors Driven AI-Based Agriculture Recommendation Model for Assessing Land Suitability

              The world population is expected to grow by another two billion in 2050, according to the survey taken by the Food and Agriculture Organization, while the arable area is likely to grow only by 5%. Therefore, smart and efficient farming techniques are necessary to improve agriculture productivity. Agriculture land suitability assessment is one of the essential tools for agriculture development. Several new technologies and innovations are being implemented in agriculture as an alternative to collect and process farm information. The rapid development of wireless sensor networks has triggered the design of low-cost and small sensor devices with the Internet of Things (IoT) empowered as a feasible tool for automating and decision-making in the domain of agriculture. This research proposes an expert system by integrating sensor networks with Artificial Intelligence systems such as neural networks and Multi-Layer Perceptron (MLP) for the assessment of agriculture land suitability. This proposed system will help the farmers to assess the agriculture land for cultivation in terms of four decision classes, namely more suitable, suitable, moderately suitable, and unsuitable. This assessment is determined based on the input collected from the various sensor devices, which are used for training the system. The results obtained using MLP with four hidden layers is found to be effective for the multiclass classification system when compared to the other existing model. This trained model will be used for evaluating future assessments and classifying the land after every cultivation.
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                Author and article information

                Contributors
                bbasioni@eri.sci.eg
                Journal
                Environ Monit Assess
                Environ Monit Assess
                Environmental Monitoring and Assessment
                Springer International Publishing (Cham )
                0167-6369
                1573-2959
                19 March 2024
                19 March 2024
                2024
                : 196
                : 4
                : 380
                Affiliations
                Computers and Systems Dept, Electronics Research Institute (ERI), ( https://ror.org/0532wcf75) El-Bahth El-Elmy St. From Joseph Tito St., Huckstep, El-Nozha El-Gadeda, P.O. Box: 11843, Cairo, Egypt
                Article
                12483
                10.1007/s10661-024-12483-8
                10951016
                38502286
                e827334c-77b6-449d-97d2-6cc14c94ffe7
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 24 March 2023
                : 17 February 2024
                Funding
                Funded by: Electronics Research Institute
                Categories
                Research
                Custom metadata
                © Springer Nature Switzerland AG 2024

                General environmental science
                iot,land suitability assessment,web development,spatial–temporal dynamic

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