為解決蘭花溫室內感測器裝置的不足，無法實施溫式蘭花種植之全面性的監控，進而加強病害的防治，因此，本研究於蘭花溫室中建立LoRa物聯網(Internet of Things)系統，並將其所連結的感測器作為終端節點，獲取更多溫室內主要影響蘭花生長的三大要素-溫度、濕度以及光照度之資料，將其發送至閘道器進行存儲備分，並傳至伺服器，建立溫室氣候之資料庫。再運用循環神經網路進行訓練，藉以建立預測模型，用來預測未來一段時間後之溫度、濕度之變化趨勢，以及軟腐病害可能發生之嚴重性，提升蘭花栽培之產能。同時，將預測結果與過去接收資料一併顯示於本研究所建立之使用者互動介面，提供即時監控各項環境資訊，藉由提前預警輔助使用者判斷溫室環境之現況，可維持溫室環境之穩定並減少蘭花種植的損失。本研究所有蒐集的溫度、濕度以及光照度之數據皆取自合作廠商之蘭花培養溫室，確保其數據皆為實際產業中所應用之資料，將來此系統研發成功，可順利投入產線，提升生產品質與效率。

To improve the drawbacks for not able to be effectively monitored, this research establishes a LoRa Internet of Things system in orchids greenhouse, to collect three mainly features affecting the orchids growing, the data of temperature, humidity, and light strength, by the wireless sensor nodes embedded in the orchids greenhouse. The collected environmental data are sent to the gateway for storage, and then transmitted into the server to build a database. The data in the database will be used to train a prediction model by recurrent neural network in order to predict the trends of future temperature, humidity prediction and soft-rot diseases damage. In this research, a user interface is constructed to show the predicted results as well as the environment information in real time for easily and friendly provide process the proposed systems, such as displaying early warning and judging the current environmental situations. Finally, all collected data are obtained from the cooperated orchid growing greenhouse to ensure the future use for the proposed system in real situation.

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