We have developed an indoor localization and path navigation system in museum environments by using wearable devices. We proposed a hybrid method for visitor localization by combining Inertial Measurement Unit (IMU), camera and Wi-Fi signals. Moreover, the server can collect and return all visitors’ localization through Wi-Fi communication. Finally, the system is able to figure out a personalized and optimized traveling route that avoids the crowded areas and at the same time considers the favorite of the visitor. We have successfully achieved a Context-Aware-Based guidance system.

We propose a positioning method that integrates multiple sensors by using IMU positioning technology, WiFi positioning technology, and camera sensor to infer user’s location via QR Codes. By this method, the effects of cumulative errors can be effectively corrected, noise can be reduced, and better positioning result can be obtained. And also proposed a user-aware path planning method for personal learning guidance based on the master-slave architecture, graph theory, and A*algorithm. By considering the preferences info. and crowd info., our system can recommend a user-preferred visiting route to users. The system is implemented by using wearable glasses as a platform. It can be applied to large-scale fields such as museum and art gallery for learning guidance in more efficient matter.

教學導覽不應只是單調地閱讀一個看板或者單純觀賞靜態的展品，也可以是具互動性、個人化、且可帶著走的知識饗宴，尤其是在藏量豐富的大型博物館，如何依據個人特性、程度、與喜好，配合當下的時間限制與博物館的熱門活動，以及當時館內參訪狀態，有效率地傳遞受用的訊息給使用者，一再凸顯互動式與個人化導覽的重要性。這項服務能幫助遊客快速了解展品的創作歷程、展品的重要性，透過好的導覽方式，將能為展品增添色彩，更能增加學習者參觀博物館的意願。同時，近年來穿戴式設備不斷推陳出新的情況下，可預期智慧穿戴科技將滲透到各生活應用領域，這樣的熱潮也直接延燒到教育界，並強調未來智慧穿戴與教育相互之重要性。因此我們提出整合於穿戴式智慧眼鏡之環境感知個人化教學導覽服務系統，不僅提供學習者個人化與適性化學習方式，也提高學習者參觀意願，更有利於展覽館安全的控管與展覽物件安排。