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Consejo Nacional de Ciencia y Tecnología, CONACYT: 236188
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funding vehicle for: Design and deployment of a practical IoT-based monitoring system for protected cultivations

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Computer Communications
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publication venue for: Design and deployment of a practical IoT-based monitoring system for protected cultivations
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RDF description of Design and deployment of a practical IoT-based monitoring system for protected cultivations - http://orbis.uaslp.mx/vivo/individual/scopus10060
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date: 2026-08-25T13:51:36
publisher: vivo
type: Document

Article
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Information Content Entity
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Design and deployment of a practical IoT-based monitoring system for protected cultivations
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page end: 64
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date time value: article date 10061
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page start: 51
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doi: 10.1016/j.comcom.2022.01.009
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origen: scopus
estado: published
freetext keyword: Greenhouse micro-climate; Internet of Things; LPWAN; Monitoring; Prediction model; Sensors; Smart agriculture Climate change; Climate models; Cultivation; Food supply; Forecasting; Greenhouses; Internet of things; Population statistics; Productivity; Food production; Greenhouse micro-climate; LPWAN; Micro-climate; Monitoring system; Prediction modelling; Rapid population growth; Smart agricultures; United Nations; World population; Monitoring
abstract: According to the United Nations’ latest forecast, the world population will reach 8.5 billion people by 2030. This rapid population growth imposes severe requirements in food production to meet demand. Moreover, the rise of temperatures and climate changes are also adversely affecting food supplies. In this paper, we design a scalable IoT-based monitoring system with prediction capabilities for agricultural applications. It provides an effective four-layered architecture that consist of sensing, networking, processing, and applications with low deployment and management costs. Hence, to demonstrate its feasibility, the proposed IoT system was constructed, experimentally tested, and validated by monitoring the temperature and humidity of a commercial-size greenhouse in Mexico for six months. Additionally, we integrated a data-driven predictive model for greenhouse microclimate conditions. Temperature predictions were accurately performed 24-hour in advance within an error of 1 °C. The obtained results confirm that the proposed IoT framework would facilitate farmers to monitor crops and enable productivity gains by increasing the level of technology progressively. © 2022 Elsevier B.V.
has funding vehicle: Consejo Nacional de Ciencia y Tecnología, CONACYT: 236188
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volume: 186
most specific type: Document
has publication venue: Computer Communications