MyGreen: An IoT-Enabled Smart Greenhouse for Sustainable Agriculture

Tripathy, Pradyumna Kumar; Tripathy, Ajaya Kumar; Agarwal, Aditi; Mohanty, Saraju P.

doi:10.1109/mce.2021.3055930

Cited by 66 publications

(23 citation statements)

References 7 publications

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“…Another linear regression model for soil moisture analysis has been designed in Sengupta et al 19 It is observed that the incorporation of neural network models can provide better results in terms of accuracy with a higher rate of optimization. The work 20 developed a soil analysis model using artificial neural networks (ANN) for predicting the soil quality based on meteorological factors based on real‐time data.…”

Section: Related Workmentioning

confidence: 99%

Retracted: Soil monitoring and evaluation system using EDL‐ASQE: Enhanced deep learning model for IoT smart agriculture network

Sumathi¹,

Subramanian²,

Karthikeyan³

et al. 2021

Int J Communication

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The enormous growth of the Internet of Things (IoT) network provides abundant support to agriculture and development, which states the future scope of IoT-based agriculture. In a recent scenario, agriculture IoT can be integrated with sensors, communication protocols, and microcontrollers for automated process executions to increase productivity. Moreover, deep learning effectiveness produces appropriate results and solves several real-time issues related to agriculture-based advancements. The proposed system presents the design of an IoT network communication system to estimate the soil conditions. Soil quality is an important factor in modernized agriculture, productivity enhancement, and hydrological cycles. By the soil quality analysis, the accurate prediction is very significant for sensible usage of resources. An enhanced deep learning model for IoT network-based automated soil quality evaluation observes the complex soil features and meteorological factors with those concerns. Here, the real-time samples are collected from the local area sensor network for analysis. The deep learning model is developed with big data fitting ability for soil quality prediction. The weight factors (W.F.) are derived for measuring the soil quality accurately. The proposed IoT network-based agriculture structure allows a flexible approach to different types of crops and implementation in agricultural areas. Experimental results obtained in the laboratory and onsite confirmed the performance and reliability of the system. The result evaluations are carried out based on precision, accuracy, and processing time, and results show that the model achieves better results than compared models. K E Y W O R D S agriculture IoT network, enhanced deep learning, soil moisture, soil quality, weight factor | INTRODUCTIONIn the present scenario, the combination of the Internet of Things, cloud computing, and big data processing offers a great agricultural data growth platform. 1 For enhancing the agriculture yield with minimal resources and efforts, several innovations are made. However, the increasing population never makes the necessities and supplies all the time.

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Section: Related Workmentioning

confidence: 99%

Retracted: Soil monitoring and evaluation system using EDL‐ASQE: Enhanced deep learning model for IoT smart agriculture network

Sumathi¹,

Subramanian²,

Karthikeyan³

et al. 2021

Int J Communication

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show abstract

“…Tripathy et al [13] focused to implement IoT-based automated greenhouse farming. In Tripathy et al [13], the authors used so many sensors like temperature, humidity, UV light, pH measuring, CO2 level, EC value, and measurement of insecticides or pesticides and they developed a system called Decision Support System (DSS) which controls all the activity related to the system. In this work, they center around rose cultivation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Tripathy et al [13] developed "MyGreen" which is costeffective and accurate. They implemented eight different types of sensors in their model.…”

Section: Literature Reviewmentioning

confidence: 99%

Applications of the Internet of Things (IoT) for Developing Sustainable Agriculture: A Review

Sizan

Dey

Mia

2022

GUB JOURNAL OF SCIENCE AND ENGINEERING

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By natural process, the world population will in-crease day by day. In rhythm, the tendency of the food will also be rising. So, it is a great challenge to supply food and increase its availability for the huge amount of people of the world, which helps to fulfill their fundamental civil rights. Nowadays, many agriculturedependent countries are fully dependent on the orthodox agriculture process. To develop such types of conditions, people should attract to modern cultivation practices. In the modern era, the Internet of things (IoT) is an optimal solution for preventing such types of challenges. IoT can connect with neoteric agriculture technology. Byusing this technique, farmers can directly connect themselves and control their felds and monitor their feld environmental conditions from anywhere around the world. By the use of unique forms of sensors, models, strategies, and technologies farmers can collect much real-time information and it helps a bearer to increase his productivity of farming. The goal of this paper is to reconsider some very recent works on smart and prompt agriculture processes. In this review paper, we have spoken about the techniques, and methodologies and summarized the state-of-the-art literature. We also made a comprehensive discussion and profound analysis of those recent works. Finally, we have given some future suggestions about smart farming techniques based on our discussion and analysis. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 8, Dec 2021 P 7-16

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“…The smart irrigation systems are important to collect and work environmental data [83]. The IoT allows to implement automated operations with reduced supervision [84] in the whole food chain [85] and agricultural production [86], including in greenhouse agriculture [87] control [88] and in diverse farming systems [89]. The water management is critical, where the IoT may contribute significantly for a more balanced use [90], as well as in the soil health assessment [91] and fertilization management [92], in a perspective of a more competitive agriculture [93].…”

Section: New Technologies and Approachesmentioning

confidence: 99%

Integrated-Smart Agriculture: Contexts and Assumptions for a Broader Concept

Martinho

Guiné

2021

Agronomy

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The innovative technologies developed in the different fields of science (nanotechnology, artificial intelligence, genetic modification, etc.) opened new and infinite possibilities for the several stakeholders that carry out their activities in the different economic sectors. For agriculture, these new approaches are particularly relevant and may bring interesting contributions, considering the specificities of the sector, often dealing with contexts of land abandonment and narrow profit margins. Nonetheless, the question in these unstopped evolutions is about the interlinkages with sustainability. In this context, the objectives of this study are to highlight the main insights from the available scientific literature about the interrelationships between the new trends in the agriculture and the sustainability. To achieve these aims, a search on the Web of Science Core Collection (WoS) and Scopus databases was carried out, on 15 May 2021, for the topics ‘smart agriculture’ and ‘sustainability’. A total of 231 documents (102 from WoS and 129 from Scopus) were obtained, remaining 155 documents after removing the duplicated, which were surveyed through systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach. As main insights, the concerns of the researchers with the impacts on the sustainability from the transformations in the farming organization are highlighted. On the other hand, it was shown the relevance and the new opportunities, including in terms of food supply, arising from the precision agriculture, agricultural intelligence, vertical/urban farming, circular economy, internet of things, and crowdfarming. We suggest the new and wider concept of ‘integrated-smart agriculture’, better than ‘climate-smart agriculture’.

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MyGreen: An IoT-Enabled Smart Greenhouse for Sustainable Agriculture

Cited by 66 publications

References 7 publications

Retracted: Soil monitoring and evaluation system using EDL‐ASQE: Enhanced deep learning model for IoT smart agriculture network

Retracted: Soil monitoring and evaluation system using EDL‐ASQE: Enhanced deep learning model for IoT smart agriculture network

Applications of the Internet of Things (IoT) for Developing Sustainable Agriculture: A Review

Integrated-Smart Agriculture: Contexts and Assumptions for a Broader Concept

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