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A Real-Time Plants Growth Monitoring System in Intelligent Agriculture Based on Petri Nets
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  • Cheng-Ying Yang ,
  • Yi-Nan Lin ,
  • Victor R.L. Shen ,
  • Yang-Cheng Lin ,
  • Frank H.C. Shen
Cheng-Ying Yang
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Yi-Nan Lin
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Victor R.L. Shen
National Taipei University

Corresponding Author:[email protected]

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Yang-Cheng Lin
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Frank H.C. Shen
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Abstract

As the current agricultural industry is facing several challenges, including climate changes and lack of qualified farmers, it is extremely necessary to ensure sustainable agriculture and food supply by smart farming (SF). This can assist farmers and associated stakeholders in making correct decision that improves the yield and quality of agricultural product. Thus, an SF system based on low-cost Raspberry Pi and Internet of Things (IoT) technologies has been successfully implemented. Through the data items detected by sensors to deeply manage the planting process, the IoT-Enabled communication protocol under ISO standards of Message Queuing Telemetry Transport (MQTT) was used. The bar charts of real-time environmental parameters are presented on ThingsBoard to achieve the goal of data visualization. Meanwhile, a web server is built for the customized requirements, and the historical datasets are stored in the SQLite database system. Furthermore, a Petri net (PN) model is employed to detect all possible abnormal processes and to verify the feasibility and soundness of IoT-Enabled system by using a software tool, WoPeD. Finally, the experimental results show that the plants cultivated by the proposed IoT-Enabled system are superior to those cultivated by the traditional methods in many perspectives, especially a promising precision, 93.6%.