Towards automating irrigation: a fuzzy logic-based water irrigation system using IoT and deep learning

Patel, Poojan; Patel, Yugma; Patel, Utsav; Patel, Vrukshal; Patel, Nitya; Oza, Parita; Patel, Usha

doi:10.1007/s40808-022-01452-0

Cited by 7 publications

(2 citation statements)

References 15 publications

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“…Table 3 presents four popular algorithms -Decision Tree, Artificial Neural Network, Fuzzy Logic, and Support Vector Machine. It describes capabilities and limitations of these algorithm [45][46][47][48].…”

Section: Algorithms For Smart Irrigation Systemsmentioning

confidence: 99%

Smart Irrigation for Sustainable Farming: Low- Cost IoT Solution

Akhtar,

Sinha,

Kumar

et al. 2024

Preprint

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This article presents a low-cost irrigation system that harnesses the power of IoT technologies to revolutionize water management practices and enhance agricultural productivity. The system uses soil moisture sensors, climate sensors, and temperature sensors that communicate with a central controlling mechanism. The data collected from the sensors is handled with the help of machine learning algorithms to make automated decisions about irrigation. This system is useful for small-scale farmers who lack access to expensive irrigation technology. The system has undergone field trials and has shown encouraging results. The soil moisture sensors have an average error rate of below 5%, saying that the system can precisely recognize soil moisture levels. The crops grown with the smart irrigation system had a 10% greater yield than the control group, and the system was able to limit water usage by up to 30% in comparison to tradition irrigation techniques. The potential effects of the low-cost smart irrigation system on food security and agriculture in developing countries must be taken into consideration. As water resources become more expensive and scarcer, technology can change irrigation practices and enhance the development of sustainable agriculture. To adapt the system to the unique requirements of small farmers in various regions and to examine the practicality of scaling it up for wider application, more research and development are needed. All things could be done with the low-cost smart irrigation system.

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Section: Algorithms For Smart Irrigation Systemsmentioning

confidence: 99%

Smart Irrigation for Sustainable Farming: Low- Cost IoT Solution

Akhtar,

Sinha,

Kumar

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The IoT transforms physical objects into network devices that can share their resources with other participants or even other objects (Brandão et al 2021 ). The IoT has been operationalized extensively in many areas, such as healthcare (Yesmin et al 2022 ), farming (Patel et al 2022 ; Xu et al 2022 ), home automation (Almusaylim and Zaman 2019 ), smart cities (Bellini et al 2022 ), and weather monitoring systems. Accurate weather information also benefits various fields, including electricity generation, agriculture, and transportation.…”

Section: Related Researchmentioning

confidence: 99%

Modeling and implementation of a low-cost IoT-smart weather monitoring station and air quality assessment based on fuzzy inference model and MQTT protocol

Fahim

Mhouti

Boudaa

et al. 2023

Model. Earth Syst. Environ.

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The automatic weather system serves to inform farmers, tourists, planners, and others with precise information to help them take the appropriate action. Today, with the advancement of smart technologies, the system has evolved into many sensing methods to gather real-time climate data. This article investigates the modeling and implementation of a low-cost weather station device that also functions to measure air quality. The proposed system based on the Internet of Things (IoT) allows access to real-time climate data for a given area. This system monitors environmental conditions such as ambient temperature, humidity, atmospheric pressure, altitude, and levels of harmful atmospheric gases like CO 2 and NO 2 . This real-time telemetry device uses MQ-135, DHT-11 and BMP280 sensors to gather data. The ESP32 board processes the obtained data from all sensors. Additionally, we present a model for a fuzzy inference system (FIS) that performs parameter categorization using a reasoning procedure and incorporates the results into an air quality index (AQI) that describes the levels of pollution for Al Hoceima city. The FIS takes CO 2 and NO 2 values as input and returns the AQI. The AQI for Al Hoceima city is categorized into six levels: Excellent , Good , Regular , Bad , Dangerous , and Very Dangerous . Furthermore, the suggested system's block hardware employs the Message Queuing Telemetry Transport (MQTT) protocol to broadcast collected data to a mobile and web application via the Internet. The suggested IoT-embedded device was tested in real life, and the results were promising.

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