Monitoring of Greenhouse Based on Internet of Things and Wireless Sensor Network

Touhami, Achouak; Benahmed, Khelifa; Bounaama, Fateh

doi:10.1007/978-3-030-21009-0_27

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…The application of advanced sensor systems in modern agriculture, particularly in greenhouses, marks a significant technological advance that streamlines agricultural processes. This system [ 68 ] uses a wireless sensor network, including the DHT11 humidity and temperature sensor, and an intelligent LoWPAN gateway that connects the Zigbee network to the Internet, enabling continuous data transfer and analysis. The DHT11 sensor excels at measuring temperature and humidity with speed, accuracy, and high resolution, making it a valuable asset in greenhouse environments.…”

Section: Types Of Smart Sensors In Precision Agriculturementioning

confidence: 99%

Smart Sensors and Smart Data for Precision Agriculture: A Review

Soussi,

Zero,

Sacile

et al. 2024

Sensors

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Precision agriculture, driven by the convergence of smart sensors and advanced technologies, has emerged as a transformative force in modern farming practices. The present review synthesizes insights from a multitude of research papers, exploring the dynamic landscape of precision agriculture. The main focus is on the integration of smart sensors, coupled with technologies such as the Internet of Things (IoT), big data analytics, and Artificial Intelligence (AI). This analysis is set in the context of optimizing crop management, using resources wisely, and promoting sustainability in the agricultural sector. This review aims to provide an in-depth understanding of emerging trends and key developments in the field of precision agriculture. By highlighting the benefits of integrating smart sensors and innovative technologies, it aspires to enlighten farming practitioners, researchers, and policymakers on best practices, current challenges, and prospects. It aims to foster a transition towards more sustainable, efficient, and intelligent farming practices while encouraging the continued adoption and adaptation of new technologies.

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Section: Types Of Smart Sensors In Precision Agriculturementioning

confidence: 99%

Smart Sensors and Smart Data for Precision Agriculture: A Review

Soussi,

Zero,

Sacile

et al. 2024

Sensors

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show abstract

“…In addition, certain studies focused on sensor fusion inside the greenhouse for environmental monitoring and control. Using a wireless sensor network, Touhami et al [31] suggested a polynomial algorithm for monitoring the microclimate of greenhouses automatically and a linear equations model for optimizing plant productivity. Changes in temperature, humidity, solar radiation, and soil pH were evaluated through simulation, and the execution time was 2.09 s. Wang and Wang [32] proposed a fuzzy-PID controller with a wireless monitoring system to control the environmental conditions of greenhouses and to monitor their microclimate.…”

Section: Introductionmentioning

confidence: 99%

Spatial, Temporal, and Vertical Variability of Ambient Environmental Conditions in Chinese Solar Greenhouses during Winter

Reza,

Islam,

Iqbal

et al. 2023

Applied Sciences

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The monitoring and control of environmental conditions are crucial as they influence crop quality and yield in Chinese solar greenhouses (CSGs). The objectives of this study were to assess the spatial, temporal, and vertical variability of major environmental parameters in CSGs during winter and to provide greenhouse climate/microclimate characteristics in order to facilitate the monitoring and control of greenhouse environmental conditions. A wireless sensor network (WSN) was deployed in two CSGs: one with crops and one without. Sensors were placed at different locations inside and outside the greenhouses, and the air temperature, humidity, CO2 concentration, light intensity, solar radiation, and wind conditions were measured and analyzed. Significant variability in the spatial, temporal, and vertical distribution of environmental factors was observed in both greenhouses. The average minimum and maximum temperatures and humidity inside the CSG with crops were 9.96 °C (4:00 h) and 24.5 °C (12:00 h), and 32.6% (12:00 h) and 92.1% (5:00 h), respectively. The temperature difference was 2.2 °C between layers in the CSG without crops and 1.4 °C between layers in the CSG with crops. The CO2 concentration in the different layers inside the CSG with crops was highest at night. The average maximum light intensity inside the CSG with crops was 32,660.19 lx, 36,618.12 lx, and 40,660.48 lx (12:00 h to 13:00 h) in the bottom, middle, and top layers, respectively. Sensor positioning in the greenhouse was evaluated by considering the sensors’ data variability. The findings of this study could aid in the development of a better monitoring and control system for CSG’s microclimate during winter. More research is needed on greenhouse microclimate control systems based on this variability analysis, which could improve crop quality and yield in greenhouses.

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“…The investigation of intelligent PV systems had practical implications on the optimization of PCE and plant growth factor and material properties. For example, Artificial Neural Network (ANN)-based IoT system for frost irrigation management required accurate sensors made using novel materials (Elfrink et al, 2019;Touhami et al, 2020;Gautam et al, 2021). The customization of material properties often involved a tradeoff between PCE, optical properties, plant growth factor, and sustainability (LCOE and transient heat loading).…”

Section: Introductionmentioning

confidence: 99%

Smart and Solar Greenhouse Covers: Recent Developments and Future Perspectives

et al. 2021

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The examination of recent developments and future perspectives on smart and solar greenhouse covers is significant for commercial agriculture given that traditional greenhouse relied on external energy sources and fossil fuels to facilitate lighting, heating and forced cooling. The aim of this review article was to examine smart and solar materials covering greenhouse. However, the scope was limited to intelligent PhotoVoltaic (PV) systems, optimization of some material properties including smart covers, heat loading and the use of Internet of Things (IoT) to reduce the cost of operating greenhouse. As such, the following thematic areas were expounded in the research; intelligent PV systems, optimization of the Power Conversion Efficiency (PCE), Panel Generator Factor (PGF) and other material properties, heat loading future outlook and perspectives. The intelligent PV section focused on next-generation IoT and Artificial Neural Networks (ANN) systems for greenhouse automation while the optimization of material parameters emphasized quantum dots, semi-transparent organic solar cells, Pb-based and Pb-based PVs and three dimensional (3D) printing. The evaluation translated to better understanding of the future outlook of the energy-independent greenhouse. Greenhouse fitted with transparent PV roofs are a sustainable alternative given that the energy generated was 100% renewable and economical. Conservative estimates further indicated that the replacement of conventional sources of energy with solar would translate to 40–60% energy cost savings. The economic savings were demonstrated by the Levelized cost of energy. A key constraint regarded the limited commercialization of emerging innovations, including transparent and semitransparent PV modules made of Pb-quantum dots, and amorphous tungsten oxide (WO3) films, with desirable electrochromic properties such as reversible color changes. In addition to intelligent energy harvesting, smart IoT-based materials embedded with thermal, humidity, and water sensors improved thermal regulation, frost mitigation and prevention, and the management of pests and disease. In turn, this translated to lower post-harvest losses and better yields and revenues.

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Monitoring of Greenhouse Based on Internet of Things and Wireless Sensor Network

Cited by 5 publications

References 10 publications

Smart Sensors and Smart Data for Precision Agriculture: A Review

Smart Sensors and Smart Data for Precision Agriculture: A Review

Spatial, Temporal, and Vertical Variability of Ambient Environmental Conditions in Chinese Solar Greenhouses during Winter

Smart and Solar Greenhouse Covers: Recent Developments and Future Perspectives

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