人工智慧應用於農業生產創新之探討

人口成長、人口老化與氣候變遷等因素影響農業生產，推促產業要採取更創新的途徑去保護與促進農作物生長。人工智慧應用在農業領域，主要有四種類型，包括：第一，農業機器人：企業開發程式與自動化機器人處理基礎的農業工作，例如能比人類更高的產量與更快的速度收割作物。第二，農作物與土壤監測：利用電腦視覺與深度學習演算法處理由無人機或是軟體技術獲得的數據資料，以監測農作物與土壤的健康。第三，預測分析：開發機器學習模型去追蹤與預測天氣變化等各種環境對於農作物產量的影響。第四，區塊鏈技術導入農產品供應鏈：利用區塊鏈去中心化、分散式儲存或記錄、共享數據的特點。食物是人類生活中最基本的元素，除了在農業生產運用創新科技外，也需要讓社會大眾對於農業知識與生產有所參與，否則在生產面應用創新科技促進智慧農業，但在消費面沒有消費者的珍惜，再高明的科技仍無法解決糧食短缺的問題，因而人工智慧也可以與農業消費結合，讓消費者成為智慧農業的支持者。

關鍵字

人工智慧；智慧農業；大數據；農業；生產創新

並列摘要

Factors such as population growth, population aging and climate change affect agricultural production. Crop Growth. There are four main types of artificial intelligence applications in the agricultural field, including: first, agricultural robots: enterprise development programs and automation. Robots handle basic agricultural tasks, such as harvesting crops at higher yields and faster speeds than humans. Second, crop and soil monitoring: using computer vision and deep learning algorithms to process data obtained from drones or software technology. The first is the development of predictive analytics to monitor the health of crops and soils. Third, predictive analytics: Developing machine learning models to track and predict the impact of various environmental conditions, such as climate change, on crop yields. Fourth, the introduction of block chain technology into the agricultural supply chain: using the decentralized, decentralized storage or recording and data sharing features of the block chain. Food is the most essential element in human life. If not, the application of innovative technology to promote smart agriculture on the production side, but not on the consumption side where consumers value it. No amount of technology can solve the problem of food shortage.

並列關鍵字

artificial intelligence ； smart agriculture ； big data ； agriculture ； productive Innovation

主題瀏覽