A Real-Time Plants Growth Monitoring System in Intelligent Agriculture
Based on Petri Nets
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%.