基於感測技術實現特定植栽智慧化與用電功耗分析系統平台開發運用

Abstract

在全球農業向智慧化和可持續發展轉型的背景下，電氣化技術逐漸成為提升農業生產效率和產品品質的核心手段。針對高經濟價值植栽（如藥用植物、觀賞植物及經濟作物）的生長條件對產量與品質的關鍵性影響，本研究運用機器人學中的智能系統與自動化技術，提出了基於電氣優化的高效生長策略。 本研究整合環境感測器模組與嵌入式控制系統，針對光照強度、光譜分布、溫濕度等環境參數進行精準感測和動態調控。通過多模感測器的數據收集，結合數據驅動模型與多目標優化演算法，研究開發了一個能動態適應環境變化的智能調控系統，實現植栽最佳生長環境的辨識與管理。機器人學的核心技術，如無線數據傳輸與嵌入式計算，確保了數據的穩定傳輸、實時處理以及設備的精確控制。 本系統還進一步探討了光譜組合（如藍光與紅光比例）的優化設計及其對植栽生長的影響，並結合精準灌溉技術與資源管理措施，大幅降低生產過程中的水資源與能源消耗，實現高效、環保的生產模式。針對電氣設備（如照明、溫濕度調控與灌溉裝置），研究詳細測算其能耗，並設計了直觀的人機介面和數據可視化功能，便於用戶監控環境參數並進行即時調整。

In the context of the global transition of agriculture towards intelligence and sustainable development, electrification technology has gradually become a core means of improving agricultural production efficiency and product quality. Focusing on the critical impact of growth conditions on the yield and quality of high-value crops (such as medicinal plants, ornamental plants, and cash crops), this study leverages intelligent systems and automation technology in robotics to propose an electrification-optimized, high-efficiency growth strategy. This research integrates environmental sensor modules and embedded control systems to achieve precise sensing and dynamic regulation of environmental parameters such as light intensity, spectral distribution, temperature, and humidity. Through data collection from multi-modal sensors, combined with data-driven models and multi-objective optimization algorithms, an intelligent regulation system capable of dynamically adapting to environmental changes has been developed, enabling the identification and management of optimal growth environments for crops. Core robotics technologies, such as wireless data transmission and embedded computing, ensure stable data transmission, real-time processing, and precise control of equipment. The system further explores the optimized design of spectral combinations (e.g., the ratio of blue to red light) and their effects on crop growth. Combined with precision irrigation techniques and resource management measures, it significantly reduces water and energy consumption during the production process, achieving an efficient and environmentally friendly production model. For electrical equipment (such as lighting, temperature and humidity control, and irrigation devices), the study provides detailed energy consumption calculations and designs an intuitive human-machine interface and data visualization functionality to facilitate user monitoring of environmental parameters and real-time adjustments.