應用無線感測器網路於植物工廠立體式栽植環境之監測分析

Abstract

本研究旨在應用無線感測器網路於植物工廠的環境監測，利用其感測器節點無線化的優點，且能量測環境中的溫度、濕度及照度等多項環境參數，因此在使用上能更加貼近植物的生長環境，同時可以大幅提升佈建時的便利性與彈性。管理者在實際應用上可以大量設置感測節點，進而提升監測系統的準確性及感測範圍，彌補傳統有線監測系統的不足。在環控室內部作物的生長區域，是以現地即時方式量測作物生長狀況，且每個感測點會依據閘道器的控制輪流進行資料回傳。閘道器將資料收集後，會再透過網際網路將感測資料寫入資料庫中。本系統的後端監控介面是以LabVIEW程式撰寫，管理者能由後端監控平台查詢無線感測器所量測的資訊進行後續分析。根據實驗結果顯示，在每一個栽培區內量測實際植物所受到溫度、濕度及照度均有所差異，且有部分栽培區溫溼度差異甚鉅，這充分改變了普遍認為溫室裡的溫度不會有大幅度變化的說法，同時搭配模擬植物工廠內部環境以進行栽培架中風扇裝置的架設，藉由風扇循環系統改善栽培區空氣溫場分佈情形。因此，本團隊所研發之無線感測器網路確實能有效掌握植物工廠內每一個栽植區的溫度和濕度變化情形，且能夠即時提供管理人員更精確的資訊以掌握植物生長的環境。

This thesis attempts to deploy wireless sensor nodes to monitor the environment of vertical plant factories. Through wireless sensor networks and measurement of environmental parameters in temperature, humidity and illumination, this application covers a wide range of plants and improve the convenience and flexibility of the monitoring system. Furthermore, the supervisor can set up a great number of sensor nodes to increase the level of accuracy and the range of monitoring, overcoming the drawbacks of wired monitoring systems. In an environmentally controlled chamber where plants grow, the condition of each plant is monitored with a real-time system, and every sensor node sends back the sensing data by turns according to the control of the gateways, which store the data in a database after collecting the data through network. The back-end monitor interface is programmed by LabVIEW, and the supervisor can look up the data by the back-end monitor platform in order to conduct more analyses. As the result of my experiment shows, the temperature, the humidity and the illumination that influence the plants in every growing area vary, and in some of the growing areas significant differences in temperature and moisture are found fully explaining a common idea that there is no considerable change in temperature in greenhouses. We install fan equipment depend on the simulation of the plant factory and improve the temperature field distribution. We install fan equipment depending on the simulation results of the plant factory and make the temperature in the plant factory more evenly distributed. Therefore, the wireless sensor network developed by our team is more efficient to monitor the changes in temperature and moisture in every growing area in the plant factory, providing more accurate data of the growth of plants for the supervisor.