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15
Identifying meaningful places: The nonparametric way
- Proceedings of the 6th International Conference on Pervasive Computing
, 2008
"... Abstract. Gathering and analyzing location data is an important part of many ubiquitous computing applications. The most common way to represent location information is to use numerical coordinates, e.g., latitudes and longitudes. A problem with this approach is that numerical coordinates are usuall ..."
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Abstract. Gathering and analyzing location data is an important part of many ubiquitous computing applications. The most common way to represent location information is to use numerical coordinates, e.g., latitudes and longitudes. A problem with this approach is that numerical coordinates are usually meaningless to a user and they contrast with the way humans refer to locations in daily communication. Instead of using coordinates, humans tend to use descriptive statements about their location; for example, ”I’m home ” or ”I’m at Starbucks. ” Locations, to which a user can attach meaningful and descriptive semantics, are often called places. In this paper we focus on the automatic extraction of places from discontinuous GPS measurements. We describe and evaluate a non-parametric Bayesian approach for identifying places from this kind of data. The main novelty of our approach is that the algorithm is fully automated and does not require any parameter tuning. Another novel aspect of our algorithm is that it can accurately identify places without temporal information. We evaluate our approach using data that has been gathered from different users and different geographic areas. The traces that we use exhibit different characteristics and contain data from daily life as well as from traveling abroad. We also compare our algorithm against the popular k-means algorithm. The results indicate that our method can accurately identify meaningful places from a variety of location traces and that the algorithm is robust against noise. 1
Abstracting People's Trajectories for Social Robots to Proactively Approach Customers
- IEEE TRANSACTIONS ON ROBOTICS
, 2009
"... For a robot providing services to people in a public space such as a shopping mall, it is important to distinguish potential customers, such as window shoppers, from other people, such as busy commuters. In this paper, we present a series of abstraction techniques for people's trajectories and ..."
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Cited by 14 (4 self)
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For a robot providing services to people in a public space such as a shopping mall, it is important to distinguish potential customers, such as window shoppers, from other people, such as busy commuters. In this paper, we present a series of abstraction techniques for people's trajectories and a service framework for using these techniques in a social robot, which enables a designer to make the robot proactively approach customers by only providing information about target local behavior. We placed a ubiquitous sensor network consisting of six laser range finders in a shopping arcade. The system tracks people's positions as well as their local behaviors, such as fast walking, idle walking, wandering, or stopping. We accumulated people's trajectories for a week, applying a clustering technique to the accumulated trajectories to extract information about the use of space and people's typical global behaviors. This information enables the robot to target its services to people who are walking idly or stopping. The robot anticipates both the areas in which people are likely to perform these behaviors as well as the probable local behaviors of individuals a few seconds in the future. In a field experiment, we demonstrate that this service framework enables the robot to serve people efficiently.
What Happened to Bob? Semantic Data Mining of Context Histories
"... Abstract. We report on event recognition within the life logging application IYOUIT for the automatic creation of static diary-like Blogs. Based on the qualitative context histories produced by IYOUIT, we developed pragmatic event modeling and recognition techniques using technology available today. ..."
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Abstract. We report on event recognition within the life logging application IYOUIT for the automatic creation of static diary-like Blogs. Based on the qualitative context histories produced by IYOUIT, we developed pragmatic event modeling and recognition techniques using technology available today. Our approach combines Description Logics with queries and rules to model event recognizers in terms of context ontologies and Allen’s temporal interval algebra. We found the ability to efficiently compute Allen relations between events to be crucial for the performance and scalability of the whole approach. Therefore, we evaluate a set of modeling alternatives and give some practical guidance. 1
Towards Personalised Ambient Monitoring
- of Mental Health via Mobile Technologies,” Technology and Health Care (18:4-5
, 2010
"... Abstract. Managing bipolar disorder is an important health issue that can strongly affect the patient's quality of life during occurrences of depressive or manic episodes and is therefore a growing burden to healthcare systems. A widely practised method of monitoring the course of the disorder ..."
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Abstract. Managing bipolar disorder is an important health issue that can strongly affect the patient's quality of life during occurrences of depressive or manic episodes and is therefore a growing burden to healthcare systems. A widely practised method of monitoring the course of the disorder is by mood and general mental health questionnaires, which are nowadays often implemented on mobile electronic devices. Detecting changes to daily routine and behaviour is of crucial importance as they can be symptomatic of an ongoing episode, or in the case of an external cause, may trigger such an episode. Current mobile phones and geospatial technology provide a means of monitoring aspects of daily routine and lifestyle which may be valuable in facilitating self-management of the condition. This manuscript introduces a methodology for analysing data obtained from a simple wearable system based on a mid-range mobile phone, along with trial results from a control group of three participants with no history of Bipolar Disorder. It is suggested that such an approach offers an unobtrusive, acceptable and low cost means of monitoring bipolar disorder patients that could significantly improve their care.
GPS-based Location Extraction and Presence Management for Mobile Instant Messenger 1
"... Abstract. Location is the most essential presence information for mobile users. In this paper, we present an improved time-based clustering technique for extracting significant locations from GPS data stream. This new location extraction mechanism is incorporated with Google Maps for realizing a coo ..."
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Abstract. Location is the most essential presence information for mobile users. In this paper, we present an improved time-based clustering technique for extracting significant locations from GPS data stream. This new location extraction mechanism is incorporated with Google Maps for realizing a cooperative place annotation service on mobile instant messenger (MIM). We also design an ontology-based MIM presence model for inferring the location clues of IM buddies, to support context-aware presence management in our MIM system. The GPS-based location extraction algorithm has been implemented on a Smartphone and evaluated using a real-life GPS trace. We show that the proposed clustering algorithm can achieve more accurate location extraction as it considers the time interval of intermittent location revisits. The incorporation of location information with the high-level contexts, such as mobile user’s current activity and their social relationship, can achieve more efficient presence management and context-aware communication. 1
Precise Location Acquisition of Mobility Data Using Cell-id
"... Cellular network data has become a hot source of study for extraction of user-mobility and spatio-temporal trends. Location binding in mobility data can be done through different methods like GPS, service provider assisted faux-GPS and Cell Global Identity (CGI). Among these Cell Global Identity is ..."
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Cellular network data has become a hot source of study for extraction of user-mobility and spatio-temporal trends. Location binding in mobility data can be done through different methods like GPS, service provider assisted faux-GPS and Cell Global Identity (CGI). Among these Cell Global Identity is most inexpensive method and readily available solution for mobility extraction; however exact spatial extraction is somehow a problem in it. This paper presents the spatial extraction technique of mobile phone user raw data which carries the information like location information, proximity location and activity of subjects. This work mainly focuses on the data pre-processing methodology and technique to interpret the low level mobility data into high level mobility information using the designed clustering methodology and publically available Cell-IDs databases. Work proposed the semisupervised strategy to derive the missing locations thorough the usage of semantic tag information and removal of spatial outliers for precise mobility profile building by adopting the LAC-clustering, which is a variant of a hierarchical clustering.
unknown title
, 2010
"... Translating mobile sensor data Into meaningful context descriptions ..."
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SEE PROFILE
, 2009
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Design, Experimentation
"... In ubiquitous computing, activity-related data is typically gathered using customized sensing equipment that give physiological measurements. Unfortunately, such systems are often proprietary or expensive to obtain. Recently, the decrease in the prices of Bluetooth chips has made Bluetooth sensors a ..."
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In ubiquitous computing, activity-related data is typically gathered using customized sensing equipment that give physiological measurements. Unfortunately, such systems are often proprietary or expensive to obtain. Recently, the decrease in the prices of Bluetooth chips has made Bluetooth sensors a viable alternative. In previous research, various systems for gathering data from Bluetooth sensors have been proposed, but they are usually limited to a specific set of sensors or to a specific runtime platform. To address these shortcomings, we have developed BeTelGeuse, a tool for Bluetooth data gathering. BeTelGeuse turns a standard mobile device such as a cellular phone into a relay node which gathers data from a body area network over Bluetooth, and forwards it to a remote server over a mobile data service such as GPRS.
IYOUIT – Share, Life, Blog, Play
"... IYOUIT is a prototype mobile service to pioneer a context-aware digital lifestyle and its reflection on the Web. The service is made freely available and leverages Semantic Web technology to implement smart application features. We intend to not only present and demonstrate IYOUIT at ISWC’08 but als ..."
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IYOUIT is a prototype mobile service to pioneer a context-aware digital lifestyle and its reflection on the Web. The service is made freely available and leverages Semantic Web technology to implement smart application features. We intend to not only present and demonstrate IYOUIT at ISWC’08 but also to provide it to conference attendees, based on their demand. 1. OVERVIEW IYOUIT 1 is a mobile application that allows users to automatically collect so-called context information centered on places they visit and people they meet. The application aims at making it easy to collect such data on a standard phone and facilitates an instant and light-hearted sharing of personal experiences within communities and rich contextual tagging for use in everyday life. All data collected by IYOUIT is aggregated into a wealth of context information and made accessible to the user on the Web and on the mobile phone. For selected contextual sources, value is added through the transformation of quantitative context information into qualitative statements about a user’s given situation. By hooking up to Web2.0 services like Flickr and Twitter, the application allows the user to share personal context with others online. Sharing can be instant, by posting single data items to such services, or through the aggregated contextual experience in potentially lifelong online blogs. IYOUIT is a fully functional research prototype that can be experienced as an always-on service on the mobile phone, as an added value to 3 rd party Web services or as a set of components for application development. Both, from our research perspective as well as in its service features, IYOUIT is shaped towards the four target application domains Share, Life, Blog and Play.