Insights on Assistive Orientation and Mobility of People with Visual Impairment Based on Large-Scale Longitudinal Data

Assistive applications for orientation and mobility promote independence for people with visual impairment (PVI). While typical design and evaluation of such applications involves small-sample iterative studies, we analyze large-scale longitudinal data from a geographically diverse population. Our publicly released dataset from iMove, a mobile app supporting orientation of PVI, contains millions of interactions by thousands of users over a year. Our analysis (i) examines common functionalities, settings, assistive features, and movement modalities in iMove dataset and (ii) discovers user communities based on interaction patterns. We find that the most popular interaction mode is passive, where users receive more notifications, often verbose, while in motion and perform fewer actions. The use of built-in assistive features such as enlarged text indicate a high presence of users with residual sight. Users fall into three distinct groups: (C1) users interested in surrounding points of interest, (C2) users interacting in short bursts to inquire about current location, and (C3) users with long active sessions while in motion. iMove was designed with C3 in mind, and one strength of our contribution is providing meaningful semantics for unanticipated groups, C1 and C2. Our analysis reveals insights that can be generalized to other assistive orientation and mobility applications

Clique-aware mobile social clouds

The important role played by cliques in identifying cohesive subgroups of people has been theorized and explored by sociologists years ago, but only recently investigated in large-scale social networks. In this paper we focus on the interplay between cliques established by on-phone communications and the urban locations their members share each other. The results about co-located cliques has been achieved through the extensive analysis of a large anonymized dataset of Call Detail Records (CDR) relying on the phone activities of nearly 1 million people in the city of Milan. Taking the cue from the observation of cliques, the paper envisions and designs a novel clique-support service for mobile users by fully exploiting the current virtualization process that is radically transforming the core network of mobile operators. The approach we propose brings together a few important contributions: first, it concretely shows that the current NFV-enabled trend of placing cloud services at the edge of the operator's network is viable and may have a payoff in terms of traffic offloading and improved user's experience; secondly, it demonstrates for the first time that a few typical cloud-based services can effectively be directly performed inside the mobile network by simply leveraging the rich amount of data about users' location and mobility behavior