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Research Article Open access CC BY 4.0

Application of Internet of Things (IoT) in Protected Cultivation: A Review

Siddharam, L. Aiswarya, J. B. Kambale, G. M. Rajesh

International Journal of Environment and Climate Change · pp. 1518–1529 · Published 20 Jul 2023

10.9734/ijecc/2023/v13i92384

Abstract

In step with the Food and Agriculture Organization of United Nations report food production is predicted to extend about 70 per cent in 2050 to fulfil the demand of food because the world’s population will exceed nine billion by that time. In agriculture, improving crop yield is crucial to fulfil the swiftly growing demand of food for population intensification. There are a lot of factors to manage for crop yield, including temperature, humidity, light intensity, moisture and carbon dioxide concentration. Greenhouse farming is an ‘all season garden’ method of providing favourable environmental conditions to plants by growing them under a framed structure covered with a transparent material. These protected agriculture uses artificial techniques to create environmental conditions suitable for the growth plants, with automated controls. With the development of agricultural sensor, wireless communication, cloud computing, and machine learning, IoT technology has emerged and is gradually being promoted and applied in the protected agriculture field. The major components in internet of things (IoT) include sensors, gateway, connectivity, cloud, analytics and user interface. Among these, sensors are the key component used for the continuous monitoring of greenhouse environment. There are different type of sensors used for monitoring each environmental factors. The physical layer, software, and sensors layer under data acquisition are linked wirelessly through standard communication protocols for transmitting data to a central base station for real-time or offline processing. Due to the importance of greenhouse climatic conditions and their effect on quantitative and qualitative crop yield, greenhouse climate simulation models are used, which includes climate modelling and crop growth models.

Greenhouse internet of thing sensors climate simulation crop growth model

References (24)

  1. 1 An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges [DOI]
  2. 2 Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk [DOI]
  3. 3 Reducing Postharvest Losses during Storage of Grain Crops to Strengthen Food Security in Developing Countries [DOI]
  4. 4 Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture [DOI]
  5. 5 IoT based low cost and intelligent module for smart irrigation system [DOI]
  6. 6 State-of-the-Art Internet of Things in Protected Agriculture [DOI]
  7. 7 Fuzzy Logic based Smart Irrigation System using Internet of Things [DOI]
  8. 8 Internet of Things (IoT): A vision, architectural elements, and security issues [DOI]
  9. 9 Cherry Tomato Production in Intelligent Greenhouses—Sensors and AI for Control of Climate, Irrigation, Crop Yield, and Quality [DOI]
  10. 10 Wireless sensor networks for greenhouse climate and plant condition assessment [DOI]
  11. 11 IoT-based monitoring and data-driven modelling of drip irrigation system for mustard leaf cultivation experiment [DOI]
  12. 12 Greenhouse environment modeling and simulation for microclimate control [DOI]
  13. 13 Model-based evaluation of greenhouse microclimate using IoT-Sensor data fusion for energy efficient crop production [DOI]
  14. 14 IOT based greenhouse environment monitoring and controlling system using Arduino platform [DOI]
  15. 15 Internet of Things: State-of-the-art, Challenges, Applications, and Open Issues [DOI]
  16. 16 Calibration of the 10HS Soil Moisture Sensor for Southwest Florida Agricultural Soils [DOI]
  17. 17 Computational botany: advancing plant science through functional–structural plant modelling [DOI]
  18. 18 Application of dynamic model to predict some inside environment variables in a semi-solar greenhouse [DOI]
  19. 19 An Integrated Yield Prediction Model for Greenhouse Tomato [DOI]
  20. 20 Wireless sensor network in precision farming for forecasting and monitoring of apple disease: a survey [DOI]
  21. 21 A model-based methodology for the early warning detection of cucumber downy mildew in greenhouses: An experimental evaluation [DOI]
  22. 22 Membership function model for defining optimality of vapor pressure deficit in closed-field cultivation of tomato [DOI]
  23. 23 Design and Development of IoT based System for Retrieval of Agrometeorological Parameters [DOI]
  24. 24 Greenhouse climate : from physical processes to a dynamic model [DOI]

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