Approach to Develop an Assistant Application for Controlling Trace Accuracy in Travel Timelines

Accurate location information collected during a trip is crucial for many post-travel activities. In the digitalized world, many of these activities (such as annotating pictures) are supported by different location-aware applications. Since these applications are also used in non-travel related scenarios, the applications cannot “know” in advance, what the appropriate location accuracy level is. In this paper, we analyze a couple of general purpose Google ecosystem applications in the context of post-travel activities with the use of real data collected during a one week trip. We examine the possible scenarios where location accuracy is not high enough to fulfill the user requirements, and propose a novel approach, which allows the location-aware application receiving more accurate location data according to policies set by the user. In our model (which is naturally applicable not only to Google ecosystem applications), we combine a general-purpose application with an assistant application aimed at managing location data quality. We describe the implementation of a prototype companion application and demonstrate that this application allows travelers to continue using regular applications (such as Google Timeline) with achieving the desired level of location accuracy. Keywords–Mobile application; Intelligent assistant; User behavior modeling; Location data; Accuracy; Human-centered design.