Towards Smart Agriculture Monitoring Using Fuzzy Systems

Abdullah, Nusratuddin; Durani, Noor Aerina Binti; Shari, Mohamad Farid Bin; Siong, King Soon; Hau, Vicky Kong Wei; Siong, Wong Ngei; Ahmad, K. A.

doi:10.1109/access.2020.3041597

Cited by 37 publications

(19 citation statements)

References 21 publications

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“…The challenge faced while designing a SF irrigation system is the limited amount of water available in some fields. Research explored methods to minimize water consumption, including reusing wastewater (recycling) [196,202,203] to overcome this challenge. Other water conservation approach is to adopt water management schemes to minimize unnecessary watering of the crops [101,200].…”

Section: ) Challengesmentioning

confidence: 99%

“…To deal with the limited processing and storing capabilities, most literature chooses to send data to a central cloud designed to manage a huge amount of data. Thing speak [89,134,137,[203][204][205][206], Ubidots [94], Blynk [207,208], OneNet [209], Amazon web services [100], GoogleColab [210,211]are examples of free IoT cloud services. The advantage of using those cloud services is the ease of integration.…”

Section: Managing Big Datamentioning

confidence: 99%

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Technologies Driving the Shift to Smart Farming: A Review

Elbeheiry

Balog

2023

IEEE Sensors J.

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As today's agriculture industry is facing numerous challenges, including climate changes, encroachment of the urban environment and lack of qualified farmers, there is a need for new practices to ensure sustainable agriculture and food supply. Consequently, there is an emphasis on upgrading the farming practices by shifting towards Smart Farming (SF) -utilizing advanced information and communication technologies to improve the quantity and quality of the crop with minimal labor interference. SF has gained lots of interest in recent years utilizing a variety of technological innovations in the field, which imposes a challenge on farmers and technology integrators to identify the suitable technologies and best practices for a particular application. This paper provides a survey of the most recent SF scientific literature to identify common practices toward technology integration, challenges, and solutions. The survey was conducted on 588 papers published on the IEEE database following Cochrane methods to ensure appropriate analysis and interpretation of results. The papers' contributions were analyzed to identify necessary technologies that constitute SF, and consequently, research themes were identified. The identified themes are sensors, communication, big data, actuators and machines, and data analysis. Besides presenting an in-depth analysis of each identified theme, the paper discusses integrating more than one technology in systems to achieve independency. The most common SF systems are remote monitoring, autonomous, and intelligent decision-making systems.

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Section: ) Challengesmentioning

confidence: 99%

Section: Managing Big Datamentioning

confidence: 99%

Technologies Driving the Shift to Smart Farming: A Review

Elbeheiry

Balog

2023

IEEE Sensors J.

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“…O controlador recebe as condições da horta e o valor do saldo decide por quanto tempo deve acionar a bomba de irrigação. Algumas soluções propostas na literatura aplicando a lógica fuzzy consideram a temperatura do ambiente e a umidade do ar [12] [13]. A planta escolhida para este trabalho foi o orégano, a fim de ajustar o sistema para tomar decisões mais precisas.…”

Section: Proposta E Implementação Da Hortaunclassified

Horta Compartilhada com IOTA e Fuzzy - Um Projeto de Economia das Coisas para IoT

Teixeira¹,

Alberti²,

Boas³

2021

Anais Do XXXIX Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo -Utilizando um cenário de uma horta comunitária urbana, este artigo apresenta a aplicação da Internet das Coisas em um caso de Economia Compartilhada, fazendo uso da criptomoeda IOTA, seu protocolo de registros distribuídos e da lógica fuzzy, de forma a se ter o controle das funcionalidades da horta, seus pagamentos, a distribuição de produtos, e o monitoramento do desenvolvimento das plantas. A horta pode ser acomodada em um edifício, garagem e até mesmo em um terreno baldio, de forma a otimizar e a escalar o aproveitamento dos recursos utilizados e produtos oferecidos.

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“…In [7], a fuzzy-stranded-neural network model detected downy mildew in viticulture early and successfully. In [23], the FL technique was used to monitor and set the duration for which the water pump would be turned on. Another example can be found in [24], where the authors proposed an FL controller and compared its performance with manual and drip irrigation methods.…”

Section: Introductionmentioning

confidence: 99%

Smart IoT Irrigation System Based on Fuzzy Logic, LoRa, and Cloud Integration

Artetxe,

Barambones,

Martín Toral

et al. 2024

Electronics

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Natural resources must be administered efficiently to reduce the human footprint and ensure the sustainability of the planet. Water is one of the most essential resources in agriculture. Modern information technologies are being introduced in agriculture to improve the performance of agricultural processes while optimizing water usage. In this scenario, artificial intelligence techniques may become a very powerful tool to improve efficiency. The introduction of the edge/fog/cloud paradigms, already adopted in other domains, may help to organize the services involved in complex agricultural applications. This article proposes the combination of several modern technologies to improve the management of hydrological resources and reduce water waste. The selected technologies are (1) fuzzy logic, used for control tasks since it adapts very well to the nonlinear nature of the agricultural processes, and (2) long range (LoRa) technology, suitable for establishing large distance links among the field devices (sensors and actuators) and the process controllers, executed in a centralized way. The presented approach has been validated in the laboratory by means of a control scheme aimed at achieving an adequate moisture level in the soil. The control algorithm, based on fuzzy logic, can use the weather forecast, obtained as a cloud service, to reduce water consumption. For testing purposes, the dynamics of the water balance model of the soil were implemented as hardware in the loop, executed in a dSPACE DS1104. Experiments proved the viability of the presented approach since the continuous space state output controller achieved a water loss reduction of 23.1% over a 4-day experiment length compared to a traditional on/off controller. The introduction of cloud services for weather forecasting improved the water reduction by achieving an additional reduction of 4.07% in water usage.

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Towards Smart Agriculture Monitoring Using Fuzzy Systems

Cited by 37 publications

References 21 publications

Technologies Driving the Shift to Smart Farming: A Review

Technologies Driving the Shift to Smart Farming: A Review

Horta Compartilhada com IOTA e Fuzzy - Um Projeto de Economia das Coisas para IoT

Smart IoT Irrigation System Based on Fuzzy Logic, LoRa, and Cloud Integration

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