Low-cost Edge Computing devices and novel user interfaces for monitoring pivot irrigation systems based on Internet of Things and LoRaWAN technologies
Open accessAbstract
The increase in irrigated crop areas, especially in countries such as Spain and Italy, has led to an increase in technological solutions for monitoring the irrigation. Furthermore, the centre pivot irrigation systems used in these crops have facilitated the daily work of farmers in recent years, however, the monitoring of these systems and the reporting of problems in their operation has become a key aspect during the growing season. For this reason, different monitoring solutions have been proposed from the area of Precision Agriculture and Information and Communication Technologies (ICTs). Nevertheless, it is necessary that these solutions take into account the digital divide their potential users may suffer and be low-cost solutions in order to be attractive to the end-users. This paper presents several low-cost solutions using novel user interfaces and wireless communication technologies for the monitoring of this type of irrigation systems. This paper presents the results obtained after the deployment of the proposed systems on a real environment and the main conclusions drawn after their use in irrigated maize crops.
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The model in [126] scored an accuracy of 97% on validation sets, and 96% on test set, with 151 trainable parameters.
“The model scored an accuracy of 97% on the validation sets, and 96% on test set, with a number of 151 trainable parameters.”
From A Comprehensive Survey on TinyML (2023) · cites this paper as [126]
Section 5.3 reports accuracy of 88.1% for the normal model and 88% for the microcontroller model, contrary to the claimed 96% test accuracy. Section 4.3.1 identifies a validation split but does not report 97% validation accuracy or 151 trainable parameters. Page numbers are unavailable in our copy. (LLM, conf=0.87)
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Experimental — accuracy not yet measuredAuthors in [126] developed a multi-label TinyML model based on MLP architecture for micro-climate control of a strawberry agricultural greenhouse.
“The authors in [126] developed a multi-label TinyML model based on Multi-Layer Perceptron(MLP) architecture for micro-climate control of a strawberry agricultural greenhouse.”
From A Comprehensive Survey on TinyML (2023) · cites this paper as [126]
Section 4.3.1 describes a microcontroller model for reading numerical water meters, not for controlling the micro-climate of a strawberry greenhouse. It says AutoKeras was used to find the network architecture; it does not identify the model as an MLP. (LLM, conf=0.88)
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- Authors
- Mateos Matilla, D., Lozano Murciego, Á., Jiménez-Bravo, D. M., Sales Mendes, A., & Leithardt, V. R. Q.
- Affiliations
- Universidad de Salamanca (ES)
- Universidade Politécnica de Portalegre (PT)
- Venue
- Biosystems Engineering
- Publisher
- Elsevier BV
- Published
- 2022-11
- Volume
- 223
- Pages
- 14-29
- ISSN
- 1537-5110 (ISSN-L)
- OpenAlex
- W3184280692
- Cited by
- 43
- References
- 20
- Citations by year
- 2026: 8 · 2025: 6 · 2024: 12 · 2023: 11 · 2022: 5 · 2021: 1
- FWCI
- 4.36
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Biosystems Engineering (publishedVersion, cc-by-nc-nd)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
- Gredos (University of Salamanca) (submittedVersion, cc-by-nc-nd)
- Gredos (University of Salamanca) (submittedVersion, cc-by-sa)
- Hispana (submittedVersion, cc-by-nc-nd)
- Funders
- Agencia Estatal de Investigación
- Junta de Castilla y León
- European Social Fund
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Life Sciences › Agricultural and Biological Sciences › Aquatic Science › Engineering and Agricultural Innovations
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Arduino and IoT Applications
- Keywords
- center pivot irrigation, irrigation monitoring, edge computing, low-cost equipment, user interface, LoRaWAN, Internet of Things, precision agriculture, digital divide, maize, wireless communication
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