Introduction to agricultural IoT

Colizzi, Lucio; Caivano, Danilo; Ardito, Carmelo; Desolda, Giuseppe; Castrignanò, Annamaria; Matera, Maristella; Khosla, Raj; Moshou, Dimitrios; Hou, K.M.; Pinet, François; Chanet, Jean-Pierre; Gao, Hui; Shi, Hongling

doi:10.1016/b978-0-12-818373-1.00001-9

Cited by 27 publications

(13 citation statements)

References 12 publications

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“…System Developing a system to improve water levels in the field by consuming energy in the field Useful for irrigation systems. Joaquín Gutiérrez et al [2] showed an automatic irrigation system that more effectively reduces water resources when we consider the period of water shortage. They found that they incorporated solar energy systems to minimize water consumption and reduce energy consumption.…”

Section: Literature Reviewmentioning

confidence: 99%

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Development of Raspberry-Pi Based IoT Agricultural System using Fuzzy Techniques

Sridhar¹,

Sindhu²,

Ragasudha³

et al. 2020

IJSCE

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In India, agriculture plays an important role in national development. Agricultural problems have always hindered the country's development. The only solution to this is smart farming by modernizing traditional farming methods today. The Internet of Things (IOT) allows a variety of applications such as monitoring and selecting crop development, supporting irrigation decisions, etc. The result of this work is the monitoring of soil moisture, temperature, humidity, pH, reproduction and water level . Field Using a sensor network that collects data from different types of sensors and then sends it to the main server using Raspberry pi, it uses vague logic in real time to make decisions based on the decisions made by the system.

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Section: Literature Reviewmentioning

confidence: 99%

“…It determines when the irrigation should begin based upon the information from soil sensors. It can also learn the irrigation schedules by itself during on-line control process [2]. Literature points out that there are a lot of papers in which fuzzy logic has been applied.…”

Section: Fuzzy Techniques Implementationmentioning

confidence: 99%

Development of Raspberry-Pi Based IoT Agricultural System using Fuzzy Techniques

Sridhar¹,

Sindhu²,

Ragasudha³

et al. 2020

IJSCE

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“…Predictive analytics, along with Internet of Things (IoT) technologies, has been extensively applied to the agricultural domain in recent years [4][5][6][7][8][9]. This has enabled the development of the concepts of smart agriculture/farming and precision agriculture/farming.…”

Section: Introductionmentioning

confidence: 99%

Internet of Things-Driven Data Mining for Smart Crop Production Prediction in the Peasant Farming Domain

et al. 2022

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Internet of Things (IoT) technologies can greatly benefit from machine-learning techniques and artificial neural networks for data mining and vice versa. In the agricultural field, this convergence could result in the development of smart farming systems suitable for use as decision support systems by peasant farmers. This work presents the design of a smart farming system for crop production, which is based on low-cost IoT sensors and popular data storage services and data analytics services on the cloud. Moreover, a new data-mining method exploiting climate data along with crop-production data is proposed for the prediction of production volume from heterogeneous data sources. This method was initially validated using traditional machine-learning techniques and open historical data of the northeast region of the state of Puebla, Mexico, which were collected from data sources from the National Water Commission and the Agri-food Information Service of the Mexican Government.

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“…The 4.0 technologies applied in the agricultural sector are Big Data [12] , [13] , Cloud Computing [14] , [15] , Cyber-Physical System [16] , [17] , Internet of Things (IoT) [18] , [19] , and Artificial Intelligence (AI) [20] , [21] . The interpretation of information with Machine Learning (ML) techniques allows the development of mathematical models with high estimation accuracy [22] .…”

Section: Introductionmentioning

confidence: 99%

“…Peru has an area of 197,837 hectares which are used for agriculture [4], and is one of the main suppliers of this product in the American market [5], accounting for approximately 3% of the world's organic banana production. As with other organic products, one of the main problems to be faced is the poor management of pests and diseases as-The 4.0 technologies applied in the agricultural sector are Big Data [12,13], Cloud Computing [14,15], Cyber-Physical System [16,17], Internet of Things (IoT) [18,19], and Artificial Intelligence (AI) [20,21]. The interpretation of information with Machine Learning (ML) techniques allows the development of mathematical models with high estimation accuracy [22].…”

Section: Introductionmentioning

confidence: 99%