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In Pervasive Computing research, substantial work has been directed towards radio-based sensing of human movement patterns. This research has, however, mainly been focused on movements of individuals. This paper addresses the joint identification of the movement indoors of multiple persons forming a cohesive whole - specifically flocks - with clustering approaches operating on three different feature...
In this paper, we present an integrated framework, named NaviComf, which constructs pedestrian navigation systems for comfort in varying environments by using multi-modal sensing technologies. With NaviComf we aim to systematically provide solutions to three key problems: (1) how to build the environmental data warehouse (EDW) which works as an infrastructure providing comprehensive and predictive...
Participatory sensing applications rely on individuals to share local and personal data with others to produce aggregated models and knowledge. In this setting, privacy is an important consideration, and lack of privacy could discourage widespread adoption of many exciting applications. We present a privacy-preserving participatory sensing scheme for multidimensional data which uses negative surveys...
Transient use of displays by mobile users was prophesied two decades ago. Today, convergence of a range of technologies enable the realization of this vision. For researchers in this space, one key question is where to physically locate the application for which the display has been appropriated. The emergence of cloud and cloudlet computing has increased the range of possible locations. In this paper...
We present GymSkill, a personal trainer for ubiquitous monitoring and assessment of physical activity using standard fitness equipment. The system records and analyzes exercises using the sensors of a personal smartphone attached to the gym equipment. Novel fine-grained activity recognition techniques based on pyramidal Principal Component Breakdown Analysis (PCBA) provide a quantitative analysis...
Localization plays an essential role in many ubiquitous computing applications. While the outdoor location-aware services based on GPS are becoming increasingly popular, their proliferation to indoor environments is limited due to the lack of widely available indoor localization systems. The de-facto standard for indoor positioning is based on Wi-Fi and while other localization alternatives exist,...
With the advance of sensor enabled smart phones simple context awareness has become a mainstream feature. Commercial apps routinely use location knowledge for the delivery of customized information or fostering social interaction. There are also scores of apps that analyse modes of locomotion for purposes such as calories calorie expenditure assessment or exercise support. On the other hand, more...
Pervasive services may have to rely on multimodal classification to implement situation-recognition. However, the effectiveness of current multimodal classifiers is often not satisfactory. In this paper, we describe a novel approach to multimodal classification based on integrating a vision sensor with a commonsense knowledge base. Specifically, our approach is based on extracting the individual objects...
Mobile phone localization plays a key role in the fast-growing Location Based Applications domain. Most of the existing localization schemes rely on infrastructure support such as GSM, WiFi or GPS. In this paper, we present FTrack, a novel floor localization system to identify the floor level in a multi-floor building on which a mobile user is located. FTrack uses the mobile phone's accelerometer...
Formal specification and runtime detection of temporal properties for pervasive context is one of the primary approaches to achieving context-awareness. Though temporal logics have been widely used in specification of temporal properties, they are faced with severe challenges in Pervasive Computing (PvC) scenarios. First, temporal logics are traditionally defined over infinite traces of possible system...
The Wi-Fi fingerprinting (WF) technique normally suffers from the RSS (Received Signal Strength) variance problem caused by environmental changes that are inherent in both the training and localization phases. Several calibration algorithms have been proposed but they only focus on the hardware variance problem. Moreover, smartphones were not evaluated and these are now widely used in WF systems....
Flattening household electricity demand reduces generation costs, since costs are disproportionately affected by peak demands. While the vast majority of household electrical loads are interactive and have little scheduling flexibility (TVs, microwaves, etc.), a substantial fraction of home energy use derives from background loads with some, albeit limited, flexibility. Examples of such devices include...
The “Computing for the Future of the Planet” project is aimed at the intersection of computing and sustainability. An update on progress in the four main areas will be given: an optimal digital infrastructure, sensing and optimising with a global world model, reliably predicting and reacting to the environment, and digital alternatives to physical activities. Practical industrial examples will be...
Location-based applications such as Facebook Places, Foursquare, or Loopt attract millions of users by implementing point of interest finders, friend finders, geosocial networking, etc. Typically, these applications act as clients to a location service such as Google Latitude or Yahoo Fire Eagle, which manage mobile object positions and ensure the scalability to provide various clients with mobile...
Existing context recognition applications for personal mobile devices are usually fine-tuned to recognize the set of characteristics required to support a particular user task. Outside of a laboratory environment, however, users are often involved in multiple tasks at a time which requires the simultaneous execution of several applications. Yet, due to the energy constraints of most personal mobile...
The worldwide adoption of smart meters that measure and communicate residential electricity consumption gives rise to the development of new energy efficiency services. Several particularly promising applications involve the disaggregation of individual appliances within a particular household in terms of their energy demand. In this paper we present an infrastructure and a set of algorithms that...
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