Digital twin framework for smart greenhouse management using next-gen mobile networks and machine learning

Future Generation Computer Systems, Journal Year: 2024, Volume and Issue: 156, P. 285 - 300

Published: March 13, 2024

Language: Английский

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Intelligent Environmental Control in Plant Factories: Integrating Sensors, Automation, and AI for Optimal Crop Production

Food and Energy Security, Journal Year: 2025, Volume and Issue: 14(1)

Published: Jan. 1, 2025

ABSTRACT The growing global challenges of environmental degradation and resource scarcity demand innovative agricultural solutions. Intelligent control systems integrating sensors, automation, artificial intelligence (AI) optimize crop production sustainability in vertical farming. This review explores the critical role these technologies monitoring adjusting key parameters, including light, temperature, humidity, nutrient delivery, CO₂ enrichment. use real‐time data from sensor networks to continuously maintain optimal conditions. Sensors measure changes environment, such as light intensity humidity levels. Automation enables tasks be performed without human intervention, ensuring consistent adjustments AI predicts plant responses proactive management strategies this context. also examines how integrate, highlighting successful case studies addressing like energy management, scalability, system harmonization. Looking ahead, AI's potential predictive maintenance emerging trends farming highlight transformative intelligent enhancing efficiency sustainability.

Language: Английский

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Automated Hydroponic System Measurement for Smart Greenhouses in Algeria

Solar Energy and Sustainable Development, Journal Year: 2025, Volume and Issue: 14(1), P. 111 - 130

Published: Feb. 5, 2025

Increasing food security and water shortages need creative agricultural methods, especially in dry places like Algeria. This research examines an Arduino-controlled smart greenhouse system for hydroponic barley growing, addressing the demand resource-efficient farming. The experiment at University of Tebessa (34°09'16"N, 8°07'44"E) used a semi-cylindrical (0.65m × 0.70m 0.65m) with DHT22 sensors temperature humidity monitoring, photoresistors lighting control, controlled watering systems. approach yielded 26% more (120g vs. 95g) 10 weeks instead 12 weeks. Compared to soil-based approaches, use efficiency reached 50 g/L, 70-90% decrease. Optimizing energy usage 150 kWh saved 9% over prior systems (165 kWh). To achieve 95% nutrient absorption efficiency, automated control maintained ideal growth conditions 20-25°C 60-80% relative humidity. conventional key performance indicators revealed significant improvements: average plant height grew by 18%, tiller count increased 33%, leaf area extended 1000 cm². A design spatial 20% reduced disease outbreaks 10%. These findings show that Arduino-based technology may boost production minimize resource usage, making it viable alternative sustainable agriculture locations.

Language: Английский

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Unmanned Aerial Vehicle-based Applications in Smart Farming: A Systematic Review

International Journal of Advanced Computer Science and Applications, Journal Year: 2023, Volume and Issue: 14(6)

Published: Jan. 1, 2023

On one hand, the emergence of cutting-edge technologies like AI, Cloud Computing, and IoT holds immense potential in Smart Farming Precision Agriculture. These enable real-time data collection, including high-resolution crop imagery, using Unmanned Aerial Vehicles (UAVs). Leveraging these advancements can revolutionize agriculture by facilitating faster decision-making, cost reduction, increased yields. Such progress aligns with precision principles, optimizing practices for right locations, times, quantities. other integrating UAVs faces obstacles related to technology selection deployment, particularly acquisition image processing. The relative novelty UAV utilization Agriculture contributes lack standardized workflows. Consequently, widespread adoption implementation farming are hindered. This paper addresses challenges conducting a comprehensive review recent applications It explores common applications, types, techniques, processing methods provide clear understanding each technology's advantages limitations. By gaining insights into associated UAV-based Agriculture, this study aims contribute development workflows improve technologies.

Language: Английский

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Advances in Solutions to Improve the Energy Performance of Agricultural Greenhouses: A Comprehensive Review

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(14), P. 6158 - 6158

Published: July 15, 2024

The increasing global population and the challenges faced by food production sector, including urbanization, reduction of arable land, climatic extremes, necessitate innovative solutions for sustainable agriculture. This comprehensive review examines advancements in improving energy performance agricultural greenhouses, highlighting innovations thermal efficiency, particularly heating cooling systems. methods include a systematic analysis current technologies their applications optimizing greenhouse design functionality. Key findings reveal significant progress materials techniques that enhance efficiency operational sustainability. identifies gaps knowledge, such as need more research on economic viability new development predictive models various conditions. conclusions emphasize importance integrating renewable advanced control systems to achieve energy-efficient practices.

Language: Английский

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Smart greenhouse construction and irrigation control system for optimal Brassica Juncea development

PLoS ONE, Journal Year: 2023, Volume and Issue: 18(10), P. e0292971 - e0292971

Published: Oct. 26, 2023

This paper contributes to smart greenhouses and IoT (Internet of Things) research. Our pioneering achievement centers on successfully designing, constructing, testing a 30m 2 greenhouse, explicitly focusing the cultivation development Brassica Juncea, mustard variety commonly grown in Vietnam. The construction phase entailed meticulous integration diverse technologies systems, culminating creation finely tuned environment meet unique needs Juncea cultivation. Notably, our research team has realized physical infrastructure developed implemented robust web interface. interface empowers users monitor remotely control greenhouse conveniently. It provides real-time visualization critical parameters, including temperature, humidity, soil moisture, light intensity, enabling precise monitoring supporting informed decision-making crop management. In addition interface, we have meticulously designed completed an Android mobile application, further enhancing accessibility convenience. app allows while move. is imperative underscore that this work marks significant milestone as first complete solution dedicated developing Juncea. accomplishments not only advance frontiers innovative but also contribute substantially progress intelligent agriculture.

Language: Английский

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Reliable Integration of Neural Network and Internet of Things for Forecasting, Controlling, and Monitoring of Experimental Building Management System

Sustainability, Journal Year: 2023, Volume and Issue: 15(3), P. 2168 - 2168

Published: Jan. 24, 2023

In this paper, Internet of Things (IoT) and artificial intelligence (AI) are employed to solve the issue energy consumption in a case study an education laboratory. IoT enables deployment AI approaches establish smart systems manage sensor signals between different equipment based on decisions. As result, paper introduces design investigation experimental building management system (BMS)-based approach monitor status sensors control operation loads reduce consumption. The proposed BMS is built integration programmable logic controller (PLC), Node MCU ESP8266, Arduino Mega 2560 perform roles transferring processing data as well decision-making. employs variety sensors, including DHT11 sensor, IR smoke ultrasonic sensor. collected from temperature used build neural network (ANN) model forecast inside platform created by ThingSpeak platform, Bylink dashboard, mobile application. results show that can publish platforms. addition, demonstrate air-conditioning, lighting, firefighting, ventilation could be optimally monitored managed for with architectural design. Furthermore, prove ANN distinct forecasting process data.

Language: Английский

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A Soft Sensor to Estimate the Opening of Greenhouse Vents Based on an LSTM-RNN Neural Network

Sensors, Journal Year: 2023, Volume and Issue: 23(3), P. 1250 - 1250

Published: Jan. 21, 2023

In greenhouses, sensors are needed to measure the variables of interest. They help farmers and allow automatic controllers determine control actions regulate environmental conditions that favor crop growth. This paper focuses on problem lack monitoring systems in traditional Mediterranean greenhouses. such most manually operate opening vents temperature during daytime. Therefore, state vent is not recorded because usually installed due economic reasons. The solution presented this consists developing a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) as soft sensor estimate using measurements different inside outside greenhouse climate input data. A dataset from located Almería (Spain) was used. data were processed analyzed study relationships between measured opening, both statistically (using correlation coefficients) graphically (with regression analysis). 81 days) then used train, validate, test set candidate LSTM-based networks for sensor. results show developed can actual with mean absolute error 4.45%, which encourages integrating part decision support it calculate other essential variables, ventilation rate.

Language: Английский

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Assessment of Smart Mechatronics Applications in Agriculture: A Review

Applied Sciences, Journal Year: 2023, Volume and Issue: 13(12), P. 7315 - 7315

Published: June 20, 2023

Smart mechatronics systems in agriculture can be traced back to the mid-1980s, when research into automated fruit harvesting began Japan, Europe, and United States. Impressive advances have been made since then developing for use modern agriculture. The aim of this study was review smart applications introduced date, different areas sector which they are being employed. Various literature search approaches were used obtain an overview current state-of-the-art, benefits, drawbacks systems. modules various networks applied processing agricultural products examined. Finally, relationships data retrieved tested using a one-way analysis variance on keywords sources. revealed limited sophisticated industry practice at time falling production rates dramatic decline reliability global food supply. could enterprises overcome these issues.

Language: Английский

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Network Architecture of a Fog–Cloud-Based Smart Farming System

IoT, Journal Year: 2025, Volume and Issue: 6(1), P. 17 - 17

Published: Feb. 20, 2025

With the rapid increase in human population and urbanization worldwide, demand for food production has played a significant role driving integration of technology into agriculture. Various Cloud-based systems, such as livestock tracking have been proposed. In those data were collected by sensors sent to Cloud processing. However, issues with systems noted, high bandwidth utilization security concerns, volume row traveling from collection devices (such sensors) through Internet. Additionally, long distance between makes it unsuitable latency-sensitive disease monitoring systems. Therefore, this paper proposes Fog–Cloud-based approach, where processing is conducted at Fog layer, closer devices, only result remote viewing. The proposed method aims reduce power consumption latency communication. To validate method, both scenarios are simulated using iFogSim (a novel simulation tool IoT computing), shows that there less than twice some time consumed system, depending on number sensors, five ten times lower. This study further supports point suitable latency-dependent farming

Language: Английский

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