臺灣博碩士論文加值系統

在這網路發達的年代，除了網際網路 (Internet) 帶給人類生活與工作更便利的各種應用外，近年發展物聯網 (IoT) 技術更為工業應用帶來快速發展。這些物聯網應用最重要的關鍵技術就是能夠有效以無線通訊的方式進行傳輸，人類使用的智慧型手機扮演了重要的監控平台角色。手機本身內建許多無線通訊技術，除了4G與5G規格外還包含全球定位系統 (GPS)、Wi-Fi和Bluetooth等當前的主流技術。目前手機所使用的定位應用，多是以GPS結合Wi-Fi的混合式定位，使用越多技術的混和式定位，相對的架構也越複雜。對於不需要精準定位的應用，如人員管制、出缺席紀錄等，等於提高了許多不必要的成本。因此本研究主要想利用基於低功耗藍芽技術 (BLE) 的iBeacon來建構低成本與簡單架構的人員軌跡與時間紀錄系統，並使用智慧型手機開啟藍芽並下載專屬APP進行定位。首先，在實際環境中建構系統的iBeacon裝置擺放布置 (Layout)。藉由測量發射機與接收機在不同距離時RSSI值的變化，評估iBeacon定位的最佳使用範圍，藉此計算實驗環境所需發射機數量和發射機間擺設位置的間距。並進一步探討發送信標訊號次數快慢 (頻率) 對接收品質 (成功接收次數) 的影響。根據此結果本文將規劃適當的指紋定位方法 (Fingerprinting)，以確保定位所使用的發射機皆在有效範圍內，達到定位需求與節能的平衡。於整體iBeacon定位軌跡紀錄系統之環境與定位方法建構後，將提出三種低複雜度方法並套用於此系統環境。首先比對指紋的方法是使用K-Nearest Neighbor Classification，其模型簡單、準確度高、善於多分類問題，以此提升定位效率與精準度。另外提出定位修正方法，以設門檻值方式排除不合理定位點，藉此改善定位軌跡符合人體移動之合理性。最後軌跡優化方法藉由Kalman Filter將整體移動軌跡平滑化，使定位資訊及移動走勢更加明確。希望能提供有人員低成本與低複雜度的定位方法，於不同地點駐留時間與空間移動等較低定位準確度需求之應用。

In the new age of Internet, the rapid development of the Internet of Things (IoT) has been brought the wide applications in the industrial areas, in addition to the popular applications of the Internet bringing human life much convenience. The most important key technology for IoT applications is the ability of effective transmission in the various environments by means of wireless communications. Meanwhile, the smartphone is to play an important role as the monitoring platform for users. There are many wireless communication technologies built in smartphones. It includes the current mainstream technologies such as the Global Positioning System (GPS), Wi-Fi, and Bluetooth, in addition to the basic 4G/5G functions. In the current positioning applications of mobile phones, they are mostly used by the hybrid positioning methods of GPS and Wi-Fi. When the hybrid positioning technologies are used more, the more complexity of the relative architectures needs to be considered. In some environments, the considered applications do not require the high precise positioning since it will be increasing a lot of additional costs, such as the number control of member in a place and the attendance records of students or staff. Therefore, we focus on using iBeacon that it is based on Bluetooth Low Energy technology (BLE) to install a simple with low-cost structure of tracking and time recording system that needs to open the Bluetooth function of a smartphone and download our designed APP for positioning. We first construct the layout of the iBeacon equipment located in the actual environment. By measuring the various RSSI values of transmitters and receivers at different distances, the best coverage area of iBeacon positioning will be evaluated. Therefore, we can decide the required number of transmitters and their distances among the transmitters in the environment. Furthermore, we will explore the results of the successful received times of each receiver when the beacon signals are sent with different times per second by the transmitters. According to the results, we will configure an appropriate fingerprint positioning method to ensure that the transmitters used within the operative range to achieve a balance between positioning requirements and energy saving. After the overall of system environment and positioning method are created, three low-complexity methods will be proposed and applied to our system. First, the provided method of comparing fingerprints (MCF) is considered to use K-Nearest Neighbor (KNN) Classification, which has a simple model, high accuracy, and is good performance at multi-classification problems to promote the positioning efficiency and accuracy. Therefore, the provided method of positioning correction (MPC) is considered to eliminate the unreasonable positioning points by setting threshold values, thereby improving the consistency of moving trajectories with human. Finally, the provided method of trajectory optimization (MTO) is considered to use Kalman Filter (KF) to smooth the whole moving trajectory in which it will make the positioning information and moving trend more clearly. In this paper, we propose a low-cost and low-complexity positioning methods to meet the requirements of low positioning accuracy such as member’s residence time duration and large-scale spatial movement among the different locations in a building.

摘要......i
Abstract......ii
誌謝......iv
目錄......v
表目錄......vi
圖目錄......vii
第一章 緒論......1
第二章 相關研究......4
2.1 設備資訊......4
2.2 演算法......7
第三章 低複雜度iBeacon定位軌跡記錄系統......11
3.1 系統架構與環境建立......11
3.2 指紋定位方法......18
第四章 方法及實驗結果......24
4.1 定位誤差計算及三種低複雜度方法......24
4.2 實際行走結果分析......33
第五章 結論......37
參考文獻......38
Extended Abstract......41

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