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Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Chronic diseases are major causes of deaths in Australia and throughout the world. This necessitates the need for a self-care, preventive, predictive and protective assisted living system where a patient can be monitored continuously using wearable and wireless sensors. In real-time home monitoring system, various biological signals of a patient are obtained continuously using a mobile device (smart...
Mobile computing is one of the largest untapped reservoirs in today's pervasive computing world as it has the potential to enable a variety of in-situ, real-time applications. Yet, this computing paradigm suffers when the available resources — such as device battery, CPU cycles, memory, I/O data rate — are limited. In this paper, the new paradigm of approximate computing is proposed to harness such...
We are presenting PanoVC — a mobile telepresence system based on continuously updated panoramic images. We are showing that the experience of telepresence, i.e. the sense of "being there together" at a distant location can be achieved with standard state-of-the-art mobile phones. Because mobile phones are always on hand users can share their environments with others in a pervasive way. Our...
Spatial Crowdsourcing (SC) is a novel platform that engages individuals in the act of collecting various types of spatial data. This method of data collection can significantly reduce cost and turnover time, and is particularly useful in environmental sensing, where traditional means fail to provide fine-grained field data. In this study, we introduce hyperlocal spatial crowdsourcing, where all workers...
Residential buildings account for a significant proportion of overall energy consumption across the world. Decentralized room level Air Conditioners (ACs) are a commonplace in developing countries such as India, contributing a major share (34% in India) of the total residential energy consumption. Option to independently control each AC presents a prime opportunity for an energy saving system. Thus,...
Numerous methods have been proposed to address different aspects of human activity recognition. However, most of the previous approaches are static in terms of the data sources used for the recognition task. As sensors can be added or can fail and be replaced by different types of sensors, creating an activity recognition model that is able to leverage dynamically available sensors becomes important...
In this paper we demonstrate a novel approach to the use of spatio-temporally aggregated cell phone data to learn features of urban ecology (i.e., spatial distributions of distinct social and economic entities and their associated activities). Specifically, our technique involves four stages: (i) decomposing the aggregated cell phone activity within local areal units using spectral methods; (ii) learning...
We present a wearable textile sensor system for monitoring muscle activity, leveraging surface pressure changes between the skin and an elastic sport support band. The sensor is based on an 8×16 element fabric resistive pressure sensing matrix of 1cm spatial resolution, which can be read out with 50fps refresh rate. We evaluate the system by monitoring leg muscles during leg workouts in a gym out...
With the advent of powerful and inexpensive sensing technology the ability to study human behaviour and activity at large scale and for long periods is becoming a firm reality. Wearables and mobile devices further allow the continuous physical colocation with the users. This reality generates new challenges but also opens the door to potentially innovative ways of understanding our daily lives. In...
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
Monitoring group mobility and structure is crucial for public safety management and emergency evacuation. In this paper, we propose a fine-grained mobility classification and structure recognition approach for social groups based on hybrid sensing using mobile devices. First, we present a method which classifies group mobility into four levels, including stationary, strolling, walking and running...
We investigate the possibility of using a combination of a smartphone and a smartwatch, carried by a shopper, to get insights into the shopper's behavior inside a retail store. The proposed IRIS framework uses standard locomotive and gestural micro-activities as building blocks to define novel composite features that help classify different facets of a shopper's interaction/experience with individual...
Mobile participatory sensing systems allow people with mobile devices to collect, interpret, and share data from their respective environments. One of the main obstacles for long-term participation in such systems is the users' privacy concerns. Due to the nature of these systems, users have to agree to provide some personalized information. Typically, however, people are reluctant to share any information,...
Acquiring local context information and sharing it among co-located devices is critical for emerging pervasive computing applications. The devices belonging to a group of co-located people may need to detect a shared activity (e.g., a meeting) to adapt their devices to support the activity. Today's devices are almost universally equipped with device-to-device communication that easily enables direct...
We present a method for recognizing a video that is playing on a TV screen by sampling the ambient light sensor of a user's smartphone. This improves situation awareness in pervasive systems because the phone can determine what the user is currently watching on TV. Our method works even if the phone has no direct line of sight to the TV screen, since ambient light reflected from walls is sufficient...
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