16,561 research outputs found
MobilitApp: Analysing mobility data of citizens in the metropolitan area of Barcelona
MobilitApp is a platform designed to provide smart mobility services in urban
areas. It is designed to help citizens and transport authorities alike.
Citizens will be able to access the MobilitApp mobile application and decide
their optimal transportation strategy by visualising their usual routes, their
carbon footprint, receiving tips, analytics and general mobility information,
such as traffic and incident alerts. Transport authorities and service
providers will be able to access information about the mobility pattern of
citizens to o er their best services, improve costs and planning. The
MobilitApp client runs on Android devices and records synchronously, while
running in the background, periodic location updates from its users. The
information obtained is processed and analysed to understand the mobility
patterns of our users in the city of Barcelona, Spain
IoT Notifications: from disruption to benefit - Architectures for the future of notifications in the IoT
The growing number of mobile and IoT devices able to generate and show incoming notifications is fostering the spread of notifications in people lives.
Nonetheless, although users are getting used to them, their presence is not always perceived as a benefit by recipients.
With the aim of improving user experience with notifications, two different approaches are presented in this dissertation.
The former acts at the distribution level, i.e., notifications are intercepted and then a system decides if, when, and how to show them; while the latter acts at the design level, i.e., notifications and their distribution strategies are designed with the aim of reducing user disruption and exploiting all the benefits that the availability of multiple devices could bring.
An IoT architecture is proposed for each approach: the Smart Notification System that relies on machine learning algorithms to adequately manage incoming notifications, and the XDN (Cross-Device Notification) framework that assists developers in creating cross-device notifications by scripting.
The modular nature of both architectures allowed the simultaneous development and test of different independent but compatible subsystems and their exploitation in preliminary deployment sessions. The results, feedbacks and lessons learned from such sessions can foster the development of future solutions in the IoT notifications field and related domains
PocketCare: Tracking the Flu with Mobile Phones using Partial Observations of Proximity and Symptoms
Mobile phones provide a powerful sensing platform that researchers may adopt
to understand proximity interactions among people and the diffusion, through
these interactions, of diseases, behaviors, and opinions. However, it remains a
challenge to track the proximity-based interactions of a whole community and
then model the social diffusion of diseases and behaviors starting from the
observations of a small fraction of the volunteer population. In this paper, we
propose a novel approach that tries to connect together these sparse
observations using a model of how individuals interact with each other and how
social interactions happen in terms of a sequence of proximity interactions. We
apply our approach to track the spreading of flu in the spatial-proximity
network of a 3000-people university campus by mobilizing 300 volunteers from
this population to monitor nearby mobile phones through Bluetooth scanning and
to daily report flu symptoms about and around them. Our aim is to predict the
likelihood for an individual to get flu based on how often her/his daily
routine intersects with those of the volunteers. Thus, we use the daily
routines of the volunteers to build a model of the volunteers as well as of the
non-volunteers. Our results show that we can predict flu infection two weeks
ahead of time with an average precision from 0.24 to 0.35 depending on the
amount of information. This precision is six to nine times higher than with a
random guess model. At the population level, we can predict infectious
population in a two-week window with an r-squared value of 0.95 (a random-guess
model obtains an r-squared value of 0.2). These results point to an innovative
approach for tracking individuals who have interacted with people showing
symptoms, allowing us to warn those in danger of infection and to inform health
researchers about the progression of contact-induced diseases
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Context-awareness for mobile sensing: a survey and future directions
The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions
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