Smart irrigation system for environmental sustainability in Africa: An Internet of Everything (IoE) approach

Adenugba, F.; Misra, Sanjay; Maskeliūnas, Rytis; Damaševičius, Robertas; Kazanavičius, Egidijus

doi:10.3934/mbe.2019273

Cited by 57 publications

(33 citation statements)

References 35 publications

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“…LAI, combined with other parameters, can be used to evaluate the amount of nitrogen in rice crops [ 58 ], determine the vigor of rice and maize [ 47 , 57 ] crops and detect diseases in sugarcane crops [ 129 ]. Moreover, UAV devices are used in [ 46 ] to optimize the application of pesticides and fertilizers in arable lands.…”

Section: Discussionmentioning

confidence: 99%

“…In this context, big data allows distributed storage and parallel data processing, enabling the extraction of information in the shortest possible time [ 43 ]. Such information are used as models by artificial intelligence (AI) systems—which, according to [ 44 ], can be understood as the ability of a system to operate as if it had the thinking capacity of a human being—and machine learning—that, according to [ 45 ] is a data processing technique to detect patterns and correlation among complex and unrelated data—for the development of decision support systems and automation of irrigation control systems [ 46 ], monitoring [ 47 ] and diseases detection in crops [ 48 ], for example.…”

Section: Conceptsmentioning

confidence: 99%

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A Systematic Review of IoT Solutions for Smart Farming

Navarro

Costa

Pereira

2020

Sensors

214

112

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The world population growth is increasing the demand for food production. Furthermore, the reduction of the workforce in rural areas and the increase in production costs are challenges for food production nowadays. Smart farming is a farm management concept that may use Internet of Things (IoT) to overcome the current challenges of food production. This work uses the preferred reporting items for systematic reviews (PRISMA) methodology to systematically review the existing literature on smart farming with IoT. The review aims to identify the main devices, platforms, network protocols, processing data technologies and the applicability of smart farming with IoT to agriculture. The review shows an evolution in the way data is processed in recent years. Traditional approaches mostly used data in a reactive manner. In more recent approaches, however, new technological developments allowed the use of data to prevent crop problems and to improve the accuracy of crop diagnosis.

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Section: Discussionmentioning

confidence: 99%

Section: Conceptsmentioning

confidence: 99%

A Systematic Review of IoT Solutions for Smart Farming

Navarro

Costa

Pereira

2020

Sensors

214

112

View full text Add to dashboard Cite

show abstract

“…There are also some possible improvements and alternatives for further research, such as tracking panels, automatic valves and the use of IoT [36].…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, utilising IoT monitoring and management could improve resource use and reduce costs, for example as demonstrated for irrigation in [36].…”

Section: Sensitivity Analysismentioning

confidence: 99%

Solar Desalination System Design for Irrigation/Drinking Water and Electricity Generation in Desert or Arid Areas

Izquierdo¹,

Blanchard²

2020

J Sustain Res

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Climate change and population growth are likely to be future challenges to obtaining water and growing crops in arid areas. Traditional hand pumps are available but give relatively low flows; they are time consuming and are limited by the depth of wells. In low latitudes, solar energy can be the main renewable energy source for water pumping and desalination. In this project, several ways to get irrigation water, drinking water and electricity have been evaluated in the country of Western Sahara. Solar pumps have been proven to be a reliable economic solution for irrigation, but drinkable water is also required in arid areas where the salinity of water wells can be high. There is an obvious synergy when using photovoltaic solar panels for pumping, desalination, and electricity generation, but the feasibility of a project involving all those uses depends on demand and finance. This paper uses resource, technology, and economic assessments to model scenarios that demonstrate the viability of this triple approach. A Net Present Value of €26,887, and an Internal Rate of Return of 10.41% was found where 7 m 3 of water was pumped per day.

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“…Additionally, Adenugba et al [11] described a solar-based energy harvesting WSN system that controls the irrigation through sensor values and a weather prediction. This prediction is based on historic and current data to determine through neural networks if it is going to rain on a certain day or not.…”

Section: State Of the Artmentioning

confidence: 99%

Autonomous Sensor Network for Rural Agriculture Environments, Low Cost, and Energy Self-Charge

et al. 2020

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Over the last years, existing technologies have been applied to agricultural environments, resulting in new precision agriculture systems. Some of the multiple profits of developing new agricultural technologies and applications include the cost reduction around the building and deployment of them, together with more energy-efficient consumption. Therefore, agricultural precision systems focus on developing better, easier, cheaper, and overall more efficient ways of handling agricultural monitoring and actuation. To achieve this vision, we use a set of technologies such as Wireless Sensor Networks, Sensors devices, Internet of Things, or data analysis. More specifically, in this study, we proposed a combination of all these technologies to design and develop a prototype of a precision agriculture system for medium and small agriculture plantations that highlights two major advantages: efficient energy management with self-charging capabilities and a low-cost policy. For the development of the project, several prototype nodes were built and deployed within a sensor network connected to the cloud as a self-powered system. The final target of this system is, therefore, to gather environment data, analyze it, and actuate by activating the watering installation. An analysis of the exposed agriculture monitoring system, in addition to results, is exposed in the paper.

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Smart irrigation system for environmental sustainability in Africa: An Internet of Everything (IoE) approach

Cited by 57 publications

References 35 publications

A Systematic Review of IoT Solutions for Smart Farming

A Systematic Review of IoT Solutions for Smart Farming

Solar Desalination System Design for Irrigation/Drinking Water and Electricity Generation in Desert or Arid Areas

Autonomous Sensor Network for Rural Agriculture Environments, Low Cost, and Energy Self-Charge

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