Decision Support System for Smart Farming With Hydroponic Style

Belhekar, Priyanka; Thakare, Anuradha; Budhe, Payal; Shinde, U. S.; Waghmode, Vaishnavi

doi:10.26483/ijarcs.v9i1.5292

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…The development of precise sensors enables the capture of data with higher accuracy, thus enabling better quality analysis and decision making [14]. Decision support systems can guide the farmer with operational decisions about choice of crop, frequency of fertilizer use, better utilization of resources, and more [69]. Autonomous vehicles take care of labor-intensive tasks, thus freeing up farmers for other important tasks [77].…”

Section: Discussionmentioning

confidence: 99%

“…The system can be accessed through mobile devices to increase adoptability amongst farmers, and supports the farmer throughout the cultivation process. Thakare et al [69] provide a DSS for remote monitoring that integrates smart sensing and smart irrigation systems to monitor parameters such as temperature, moisture content, and efficient water use. The study emphasizes the importance of smart farming with hydroponics, which allows farming in unsuitable soil and water conditions.…”

Section: Decision Support Systems (Dss)mentioning

confidence: 99%

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Disruptive Technologies in Smart Farming: An Expanded View with Sentiment Analysis

Yadav

Kaushik

Sharma³

et al. 2022

AgriEngineering

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Smart Farming (SF) is an emerging technology in the current agricultural landscape. The aim of Smart Farming is to provide tools for various agricultural and farming operations to improve yield by reducing cost, waste, and required manpower. SF is a data-driven approach that can mitigate losses that occur due to extreme weather conditions and calamities. The influx of data from various sensors, and the introduction of information communication technologies (ICTs) in the field of farming has accelerated the implementation of disruptive technologies (DTs) such as machine learning and big data. Application of these predictive and innovative tools in agriculture is crucial for handling unprecedented conditions such as climate change and the increasing global population. In this study, we review the recent advancements in the field of Smart Farming, which include novel use cases and projects around the globe. An overview of the challenges associated with the adoption of such technologies in their respective regions is also provided. A brief analysis of the general sentiment towards Smart Farming technologies is also performed by manually annotating YouTube comments and making use of the pattern library. Preliminary findings of our study indicate that, though there are several barriers to the implementation of SF tools, further research and innovation can alleviate such risks and ensure sustainability of the food supply. The exploratory sentiment analysis also suggests that most digital users are not well-informed about such technologies.

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Section: Discussionmentioning

confidence: 99%

Section: Decision Support Systems (Dss)mentioning

confidence: 99%

Disruptive Technologies in Smart Farming: An Expanded View with Sentiment Analysis

Yadav

Kaushik

Sharma³

et al. 2022

AgriEngineering

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“…Hidrokultur adalah sumber hidroponik (Mohammed & Sookoo, 2016) (Belhekar, Thakare, Budhe, Shinde, & Waghmode, 2018). Ini adalah teknik untuk menumbuhkan dan merawat tanaman di lingkungan yang tidak dinodai dengan mencampurkan larutan nutrisi ke dalam air karena tanaman hanya dapat tumbuh jika akarnya terkena larutan mineral (Beckles, 2012).…”

Section: Pendahuluanunclassified

“…Namun, Larutan nutrisi harus diganti seminggu sekali atau ketika konsentrasi larutan turun di bawah nilai nominal (Lakkireddy, Kondapalli, & Sambasiva Rao, 2012). Berbagai cara telah dilakukan oleh para peneliti agar proses penggantian larutan nutrisi dapat dilakukan secara otomatis dengan memasang sensor pada sistem tersebut (Charumathi et al, 2017) (Belhekar et al, 2018) (Wedashwara, Ahmadi, & Arimbawa, 2019).…”

Section: Pendahuluanunclassified

Sistem Pintar IoT Berbasis Arduino dan Android untuk Pengontrolan Kondisi pH dan TDS pada Pengairan Hidroponik

Hermala

Ismail

Hendrasto³

et al. 2022

JRST

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IoT merupakan salah satu kemajuan yang signifikan dalam bidang informasi dan teknologi dan terus dapat dikembangkan untuk kemudahan aktivitas manusia. Pada penelitian ini, Sistem pintar IoT berbasis arduino dan android untuk pengukuran keasaman dan nutrisi air pada hidroponik. Arduino digunakan sebagai prosesor data yang masuk dari sensor untuk ditampilkan pada layar dan direspon memlaui relay untuk menghidupkan pompa jika nilai TDS dibawah nilai yang ditentukan. Data dari arduino dikirim ke cloud firebase sehingga bisa diakses melalui perangkat android. Perangkat lunak prosesor Arduino menggunkan bahasa C yang diedit pada IDE arduino. Android didesain menggunakan XML dan Kotlin untuk membantu proses control aplikasi yang dibuat menggunakan aplikasi android studio. Alat ukur arduino dikalibrasi dengan menggunakan data tegangan dan data PH serta data TDS yang seharusnya pada cairan kalibrasi. Kemudian didapatkan model linier untuk PH dan model polynomial pangkat tiga untuk TDS. Model tersebut diimplementasikan pada arduino dan didapatkan nilai pengukuran mendekati nilai kalibrasi dengan kesalahan 5.86% untuk PH dan 11.1% untuk TDS. Sistem IoT diamati dengan mencoba tampilan data serta otomasi dan control manual melalui android. Hasil tampilan, otomasi dan kontrol manual bekerja secara efektif sesuai fungsi sebagai IoT.

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“…Belhekar, Thakare [ 33 ] employed an onsite method of measuring nitrogen (N), K, and Ca using custom built ISE probes. The system was designed for greenhouse management and the performance of the system was measured through a real-world application of growing one year old paprika over 16 days.…”

Section: Introductionmentioning

confidence: 99%

A low-cost spectroscopic nutrient management system for Microscale Smart Hydroponic system

Stevens,

Murray,

Diepeveen

et al. 2024

PLoS ONE

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Hydroponics offers a promising approach to help alleviate pressure on food security for urban residents. It requires minimal space and uses less resources, but management can be complex. Microscale Smart Hydroponics (MSH) systems leverage IoT systems to simplify hydroponics management for home users. Previous work in nutrient management has produced systems that use expensive sensing methods or utilized lower cost methods at the expense of accuracy. This study presents a novel inexpensive nutrient management system for MSH applications that utilises a novel waterproofed, IoT spectroscopy sensor (AS7265x) in a transflective application. The sensor is submerged in a hydroponic solution to monitor the nutrients and MSH system predicts the of nutrients in the hydroponic solution and recommends an adjustment quantity in mL. A three-phase model building process was carried out resulting in significant MLR models for predicting the mL, with an R2 of 0.997. An experiment evaluated the system’s performance using the trained models with a 30-day grow of lettuce in a real-world setting, comparing the results of the management system to a control group. The sensor system successfully adjusted and maintained nutrient levels, resulting in plant growth that outperformed the control group. The results of the models in actual deployment showed a strong, significant correlation of 0.77 with the traditional method of measuring the electrical conductivity of nutrients. This novel nutrient management system has the potential to transform the way nutrients are monitored in hydroponics. By simplifying nutrient management, this system can encourage the adoption of hydroponics, contributing to food security and environmental sustainability.

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Decision Support System for Smart Farming With Hydroponic Style

Cited by 9 publications

References 5 publications

Disruptive Technologies in Smart Farming: An Expanded View with Sentiment Analysis

Disruptive Technologies in Smart Farming: An Expanded View with Sentiment Analysis

Sistem Pintar IoT Berbasis Arduino dan Android untuk Pengontrolan Kondisi pH dan TDS pada Pengairan Hidroponik

A low-cost spectroscopic nutrient management system for Microscale Smart Hydroponic system

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