Wireless Configuration for Smart Greenhouse Automation: An Economical and Efficient Approach

Authors

1 Graduate University of Advanced Technology, Kerman, Iran

2 Assistant Professor, Department of Electrical and Computer Engineering, Graduate University of Advanced Technology, Kerman, Iran.

3 Associate Professor, Department of Electrical and Computer Engineering, Graduate University of Advanced Technology, Kerman, Iran

4 Assistant Professor, Institute of Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran

Abstract
The integration of advanced technologies, such as smart automation systems and the Internet of Things (IoT), has revolutionized modern greenhouses by enhancing product quality, precise plant growth control, disease and pest reduction, chemical and toxin minimization, waste reduction, and overall operational efficiency. This study focuses on the development of a wireless configuration to transform conventional greenhouses into smart ones with minimal expenses and modifications. The proposed system employs a comprehensive range of sensors to monitor crucial environmental parameters, including temperature, air humidity, light intensity, soil moisture, and CO2 concentration. WiFi and ZigBee protocols are evaluated to establish seamless communication between these sensors and the central monitoring station. WiFi protocol is deemed cost-effective in greenhouses where no interference occurs within the 2.4 GHz frequency range. However, in cases where frequency interference is present, utilizing ZigBee modules operating at sub-one gigahertz frequency (900 MHz) or using the WiFi in the 5 GHz band is recommended. This wireless configuration minimizes installation and setup time and costs and enables remote monitoring and control of greenhouse conditions, empowering users with real-time access to intelligent control system information anytime and anywhere. The proposed solution contributes to the advancement of smart greenhouse automation, offering an economical and efficient approach for the widespread adoption of intelligent systems in the agricultural sector.

Keywords


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  • Receive Date 07 July 2023
  • Revise Date 21 August 2023
  • Accept Date 29 August 2023
  • First Publish Date 29 August 2023
  • Publish Date 22 June 2023