在現代日趨便利的生活中，資訊取得的速度變為關鍵，越來越多人不計代價希望能取得最快的訊息處理技術。其中現有的無線頻段可以提供此解決方案，特別是無線射頻識別（RFID）並不像其他技術複雜且昂貴。本研究方向以獲得最快的信息為訴求，因此利用無線射頻識別系統與雲端運算系統做整合以加快系統處理的效能與彈性。在不久的未來無線射頻辨識將完全取代傳統技術，且大量的運用在我們的日常生活上。由於無線射頻辨識技術具有識別、追蹤和監控的特性，因此非常適合應用於物流產業。本研究目前使用的情境應用於超級市場的物流環境，透過本研究的發展，未來將可預見擴大延伸應用於教育領域上。
目前無線射頻辨識技術最常見的應用為博物館的導覽使用，一旦無線射頻讀取器讀取到標籤上的EPC碼時，系統可自動化運作來取得目標物的詳細資訊。由於標籤的晶片只有有限的記憶體，無法儲存大量的資料，本研究將透過雲端系統將額外資料儲存於Google所建立的雲端系統上。此基本概念是透過雲端系統，以減低硬體的購置成本和維護大量電子設備所需要的花費。透過本研究建立此項服務，於本地端只需要有一台個人主機進行使用操作。當確認使用界面和應用程序符合使用者的需求後，將可直接將服務部署到Google的設施上。另外在同一個時間點有可能讀取到許多的標籤，在此情況下將有可能發生訊號碰撞情形。此為標籤碰撞或是讀取器的碰撞問題。
本研究僅用一個移動式讀取器實驗，我們將忽略讀取器可能發生的碰撞問題，然而標籤的碰撞問題仍然存在。當發生碰撞時，將有可能造成讀取器無法讀取到標籤，或是讀取到一錯誤的訊息。因此，本研究透過解決如何避免標籤碰撞，提升讀取的正確率與系統穩定度。 經由本研究過程中發現若是要將防碰撞機制加入到所提出的運作環境中，需要修改硬體的設備，然而此項修改已超出本研究範圍。因此，我們透過使用MATLAB電腦模擬，進行防碰撞的效能驗證與比較。

The speed of information has become very crucial in everyday lives. People seek their demand in the fastest Information Technology (IT) even though it would likely spend very high cost for the system’s usage. One of the technologies that are not as expensive as the other sophisticated devices is using the radio frequencies. This research intends to gain the fastest information by applying the Radio Frequency Identification (RFID) technology which is integrated with the cloud computing system. It has been forecasted that the RFID will soon take over very important features in our lives. Starting from the ability to identify, track and monitor logistics. Other than that, many researchers in this field have a high passion to shift the orientation from supply management to commercial use. If we assumed that this research used the scenario in the supermarket for logistic use, we could also anticipate the function of this proposed system to be used in education area as well. For example in contribution at the education field is applying the book management in libraries, student absent systems, anti cheating application, etc.
The most promising application is to identify the object in museums and exhibitions. Once the reader retrieve the EPC code from the tags, the reader may operate an automated operation to retrieve detail information about the object being scanned. Since the RFID microchips only have very limited memory, the database of the proposed system we used is on the Google’s private cloud. The basic idea for using the cloud computing is to minimize cost of purchasing and maintaining a large number of electronic devices. To set up an application for the database, we only need a personal computer as the local host. When the interface and the usage of the application suit your demand, we can deploy it directly to the Google’s infrastructure.
When detecting numerous tags at the same time, there is always a possibility for collisions to occur. There is the tag’s collision problem and also the readers collision problem. Since we used only one mobile reader for the experiments, we may neglect the possibility of the reader’s collision problem. However, the tag’s collision problem still exists. The collision may result in undetected tags ID or misinterpretation of a different code. The implementation of the anti-collision at the mobile reader is to solve the problem. Another breakthrough in this research is the implementation of the Tag’s Anti-Collision scheme embedded in the mobile reader. Ever since the RFID is used for logistic matter, the anti collisions were always operated at the middleware or at the static reader of the system.
As the research conducted, the mobile RFID reader that we used cannot be implemented with the tags anti-collision algorithm. We need to modify the hardware to continue the implementation of the tag anti-collision algorithm into the mRFID reader. To cover this limitation, we did a computer simulation using MATLAB to distinguish the performance of the RFID readings. The performance of the proposed method was compared to the Slotted ALOHA algorithm. Although the system works according to expectations, we still need more time to modify the mRFID reader to continue this research.

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