在設備與設計需求之後 ,在這裡介紹目前實作成果所使用之工具與環境,圖 25 延伸了之前提 到之資料流程圖 (圖 20) ,加上各個區塊的實作語言與環境 。 本論文的資料收集端實作在筆記
型電腦上,大部分以C/C++編寫而成 ,在展示中將會以視窗程式的操作流程為主 ,實作了基
於COM port連線概念的藍芽資料收集與使用者介面,另外配合 FTP協議將收集到的資訊上
傳至伺服器端。 在伺服器方面,主要的資料處理程式亦以C/C++編寫,另在資料儲存方面選
擇了 MYSQL 資料庫,並使用 php 進行動態網頁之編輯 ,最後在使用者端透過網頁瀏覽器看
到的便是資料經過處理之後之揮桿成果頁面 。
系統於使用者端執行與呈現之畫面如圖 26 ,圖中以紅圈標記之小型 USB 裝置即為藍芽接 收器,感測裝置模組上之資訊將由此裝置進行接收 ,目前開發的成果包括使用者端的帳號管理 及感測網路的資料收集與傳輸 ,另外在網頁介面如圖27上呈現圖形化的揮桿軌跡、 揮桿過程中
BSN
iGolf System
Provide swing data
View result
Raw data Processed data
Processed data DB
Web server
Gateway app
Expert System
Raw data Processed data
C/C++
C++/JAVA FTP protocol UI on device
C/C++
Data processing API
C/C++
Golf learner
圖25: 本系統之實作環境與使用工具
圖26: 資料收集端程式之運作畫面
圖 27: 揮桿資料顯示在網頁介面上之畫面
作為學員分段動作學習依據的關鍵點 、 揮桿節奏等特徵值數據、 合適的揮桿建議等資訊 ,並提 供揮桿歷史紀錄的查詢的功能。
九 、 結論
本論文提出一個基於體感測網路與雲端服務的高爾夫球揮桿學習系統 ,陸續介紹了揮桿軌跡重 現 、 揮桿分解 、 特徵值擷取等可以從揮桿感測讀值取得在訓練上對學員有益的資訊的方法,最 後將完成實作的系統實際展示出來 。 實際上 ,高爾夫球運動更加地複雜而精密,在本論文中提 出各種演算法亦做為拋磚引玉之用,在未來更期待能夠透過更完整的資料收集與資料統計方式 ,做為一個學習系統 ,強化其在訓練成效上的特色 。
Acknowledgement
感謝雙溪高爾夫球場教練陳彥吉先生實際教導我們進行揮桿學習,並不吝配合實驗,提供專業
知識及寶貴意見 。
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