IoT-based Automated Greenhouse for Deep Water Culture Hydroponic System

Moreno, Maria Cecilia Rey; Suárez, Oscar J.; Garcia, Alda Pardo

doi:10.1109/scla53004.2021.9540187

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…This neural network architecture could be very regular, because it can be implemented to many one-of-akind responsibilities. the primary time period, 'feed forward' designates how this neural network procedures and recalls patterns [2]. The term 'returned propagation' declares how this sort of neural network is educated.…”

Section: Feed Forward Back Propagation Methodsmentioning

confidence: 99%

An Intelligent IoT Based Hydrophonics for Smart Soilless Agriculture

Sivakumar¹,

Selvarasu²,

Selvi³

2022

ESP-JETA

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Agriculture plays a major function on improving the financial system of the United States. modern-day farming technique like Hydroponics is in rise which is soilless farming tradition and the flowers have been grown with the help of nutrient solutions. The Aquicultural device can be learned via a device mastering technique like artificial Neural Networks (ANN). net of things (IoT) allows device to device conversation and monitoring the hydroponic arrangement and intelligently. This painting is evolved an wise IoT based hydroponic device by applying ANN. The hydroponic system imparting a sensor like temperature, humidity, suitable manage over the sprinkler and water waft for the aquicultural atmosphere primarily based at the multiple input parameters collected from sensors.

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Section: Feed Forward Back Propagation Methodsmentioning

confidence: 99%

An Intelligent IoT Based Hydrophonics for Smart Soilless Agriculture

Sivakumar¹,

Selvarasu²,

Selvi³

2022

ESP-JETA

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“…Additionally, fast-moving technologies such as machine learning, the Internet of Things (IoT), wireless sensor networks (WSNs), and high-speed internet further accelerate technical advances in CEA by monitoring and controlling growth factors and production remotely. Recent studies [32][33][34][35][36][37] also feature automated greenhouse environments equipped with such technologies. Thus, the remote monitoring of the system using IoT is practicable, and the physiological data acquired remotely can be shared with other greenhouse farmers online [38].…”

Section: Introductionmentioning

confidence: 99%

An Application of System Dynamics to Characterize Crop Production for Autonomous Indoor Farming Platforms (AIFP)

Ryu,

Subah,

Baek

2023

Horticulturae

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Smart farming using technology-monitored controlled environment agriculture (CEA) has recently evolved to optimize crop growth while minimizing land use and environmental impacts, especially for climate-threatened regions. This study focuses on characterizing crop production using system dynamics (SD) modeling, which is a relatively new approach in CEA settings. Using tomatoes in a hydroponic growing system, we explore an alternative food resource potentially accessible to underserved areas in rural and/or urban settings under abrupt climate variability. The designed autonomous indoor farming platforms (AIFP) are equipped with the Internet of Things (IoT) to monitor the physiological parameters, including electrical conductivity (EC), pH, and water temperature (WT) associated with plant growth. Two varieties of tomato (Solanum lycopersicum) plants were used in this study with two different nutrient inputs (N-P-K ratios of 2-1-6 and 5-5-5) to assess the nutrient application impact on yield, especially focusing on the early stages of tomato to conceptualize and parametrize SD modes. Repeated measure analysis was conducted to investigate the effects of the environmental factors (EC, pH, and WT) in response to changing plant nutrients. The results show that different nutrient compositions (N-P-K ratios) have a noticeable effect on both pH and WT (p < 0.001) as opposed to EC. The study indicates that the proposed AIFP would be a promising solution to produce other crops for indoor farming in a changing climate. We anticipate that the proposed AIFP along with SD tools will be widely adopted to promote indoor farming in changing climates, ultimately contributing to community resilience against food insecurity in disadvantaged areas for years to come.

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