An Intelligent IoT-Based System Design for Controlling and Monitoring Greenhouse Temperature

The Kingdom of Saudi Arabia is known for its extreme climate where temperatures can exceed 50 °C, especially in summer. Improving agricultural production can only be achieved using innovative environmentally suitable solutions and modern agricultural technologies. Using Internet of Things (IoT) tech...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.125488-125500
Main Authors: Subahi, Ahmad F., Bouazza, Kheir Eddine
Format: Article
Language:English
Subjects:
Agricultural production
Agriculture
Air pollution
Crop growth
Crop production
Data models
Energy consumption
Environmental monitoring
graph database
Green products
Intelligent greenhouse agriculture
Internet of Things
model transformations
model-driven architecture (MDA)
Petri nets
Petri nets (PNs)
Systems design
Temperature
temperature control system
Temperature sensors
the~Internet of Things (IoT)
Unstructured data
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Summary:The Kingdom of Saudi Arabia is known for its extreme climate where temperatures can exceed 50 °C, especially in summer. Improving agricultural production can only be achieved using innovative environmentally suitable solutions and modern agricultural technologies. Using Internet of Things (IoT) technologies in greenhouse farming allows reduction of the immediate impact of external climatic conditions. In this paper, a highly scalable intelligent system controlling, and monitoring greenhouse temperature using IoT technologies is introduced. The first objective of this system is to monitor the greenhouse environment and control the internal temperature to reduce consumed energy while maintaining good conditions that improve productivity. A Petri Nets (PN) model is used to achieve both monitoring of the greenhouse environment and generating the suitable reference temperature which is sent later to a temperature regulation block. The second objective is to provide an Energy-Efficient (EE) scalable system design that handles massive amounts of IoT big data captured from sensors using a dynamic graph data model to be used for future analysis and prediction of production, crop growth rate, energy consumption and other related issues. The design tries to organize various possible unstructured formats of raw data, collected from different kinds of IoT devices, unified and technology-independent fashion using the benefit of model transformations and model-driven architecture to transform data in structured form.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.3007955