An effective approach to develop location-based augmented reality information support

Using location-based augmented reality (AR) for pedestrian navigation can greatly improve user action to reduce the travel time. Pedestrian navigation differs in many ways from the conventional navigation system used in a car or other vehicles. A major issue with using location-based AR for navigation to a specific landmark is their quality of usability, especially if the active screen is overcrowded with the augmented POI markers which were overlap each other at the same time. This paper describes the user journey map approach that led to new insights about how users were using location-based AR for navigation. These insights led to a deep understanding of challenges that user must face when using location-based AR application for pedestrian navigation purpose, and more generally, they helped the development team to appreciate the variety of user experience in software requirement specification phase. To prove our concept, a prototype of intuitive location-based AR was built to be compared with existing standard-location based AR. The user evaluation results reveal that the overall functional requirements which are gathered from user journey have same level of success rate criteria when compared with standard location-based AR. Nevertheless, the field study participants highlighted the extended features in our prototype could significantly enhance the user action on locating the right object in particular place when compared with standard location-based AR application (proved with the required time)

Comparative study of user experience on mobile pedestrian navigation between digital map interface and location-based augmented reality

Fast-paced mobile technology development has permitted augmented reality experiences to be delivered on mobile pedestrian navigation context. The fact that the more prevalent of this technology commonly will substituting the digital map visualization to present the geo-location information is still debatable. This paper comprises a report on a field study comparing about user experience when interacting with different modes of mobile electronic assistance in the context of pedestrian navigation interfaces which utilize location-based augmented reality (AR) and two-dimensional digital map to visualize the points of interest (POIs) location in the vicinity of the user. The study was conducted with two subsequent experiments in the Zhongli District, Taoyuan City, Taiwan. The study involved 10 participants aged between 22 and 28 years with different experiences in using smartphones and navigation systems. Navigation performance was measured based on a usability approach on pragmatic quality and hedonic quality like effectiveness (success rate of task completion), efficiency (task completion time) and satisfaction in real outdoor conditions. The evaluation findings have been cross-checked with the user’s personal comments. We aim at eliciting knowledge about user requirements related to mobile pedestrian interfaces and evaluating user experience from pragmatic and hedonic viewpoints. Results show that in the context of pedestrian navigation, digital map interfaces lead to significantly better navigation performance in pragmatic attributes in comparison to AR interfaces. Nevertheless, the study also reveals that location-based AR is more valued by participants in hedonic qualities and overall performance

Bus Arrival Prediction – to Ensure Users not to Miss the Bus

Predicting arrival times of buses is a key challenge in the context of building intelligent public transportation systems. The bus arrival time is the primary information for providing passengers with an accurate information system that can reduce passenger waiting times. In this paper, we used the normal distribution method to the random of travel times data in a bus line number 243 in Taipei area. In developing the models, data were collected from Taipei Bus Company. A normal distribution method used for predicting the bus arrival time in bus stop to ensure users not to miss the bus, and compare the result with the existing application. The result of our experiment showed that our proposed method has a better prediction than existing application, with the probability user not to miss the bus in peak time is 93% and in normal time is 85%, greater than from the existing application with the 65% probability in peak time, and 70% in normal time

Location-Based Augmented Reality Information for Bus Route Planning System

Bus Route Planner applications will unfold their full potential when bus passengers are enabled to get information about the shortest path route, make a travel plan and get the correct buses in order to reduce the travel time. However, all these information are provided in text based and map view. It is difficult to understand them for the person who does not know place in the map. This paper describes the android base application of Augmented Reality (AR) that has feature to support the action of a bus user in an innovative and dynamic ways by putting additional information layer on smart phone camera screen and give the instruction assistant that leading the user way to the nearest bus stop. The experimental results show that, the overall functional of proposed application can be run well in various type of Android smart phone. When compared with similar bus traveling applications, the proposed application works more efficient

Software Development of Automatic Data Collector for Bus Route Planning System

Public transportation is important issue in Taiwan. Recently, mobile application named Bus Route Planning was developed to help the user to get information about public transportation using bus. But, this application often gave the user inaccurate bus information and this application has less attractive GUI. To overcome those 2 problems, it needed 2 kinds of solutions. First, a more accurate time prediction algorithm is needed to predict the arrival time of bus. Second, augmented reality technology can be used to make a GUI improvement. In this research, Automatic Data Collector system was proposed to give support for those 2 solutions at once. This proposed system has 3 main functionalities. First, data collector function to provide some data sets that can be further analyzed as an base of time prediction algorithm. Second, data updater functions to provide the most updated bus information for used in augmented reality system. Third, data management function to gave the system better functionality to supported those 2 related systems. This proposed Automatic Data Collector system was developed using batch data processing scenario and SQL native query in Java programming language. The result of testing shown this data processing scenario was very effective to made database manipulation especially for large-sized data

Optimized Active Learning for User’s Behavior Modelling based on Non-Intrusive Smartphone

In order to protect the data in the smartphone, there is some protection mechanism that has been used. The current authentication uses PIN, password, and biometric-based method. These authentication methods are not sufficient due to convenience and security issue. Non-Intrusive authentication is more comfortable because it just collects user’s behavior to authenticate the user to the smartphone. Several non-intrusive authentication mechanisms were proposed but they do not care about the training sample that has a long data collection time. This paper propose a method to collect data more efficient using Optimized Active Learning. The Support Vector Machine (SVM) used to identify the effect of some small amount of training data. This proposed system has two main functionalities, to reduce the training data using optimized stop rule and maintain the Error Rate using modified model analysis to determine the training data that fit for each user. Finally, after we done the experiment, we conclude that our proposed system is better than Threshold-based Active Learning. The time required to collect the data can reduced to 41% from 17 to 10 minutes with the same Error Rate

An Object Transaction Service in Corba

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Detail Implementation of FT-SOAP

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