2014 IEEE 15th International Conference on Mobile Data Management

This seminar overviews recent research on novel data models for the advanced representation of mobility data encompassing semantic and contextual information. View full abstract»

In this seminar we will consider how concepts of information fusion, crowdsourcing and mobility complement each other and accelerate novel advanced research directions in mobile data management. We will elaborate on each of those concepts and explore their synergy under a prominent scenario of situation assessment in multi-robot search and rescue missions. View full abstract»

This is a tutorial paper covering issues associated dynamic management of information as well as content in wireless networks of different types such as Mobile Peer-to-Peer (MP2P), Vehicle-to-Vehicle (V2V) and Delay-Tolerant Networks (DTNs). View full abstract»

With the increase in number of available interesting locations, it becomes difficult for users to find interesting ones, thus imposes a need for recommender systems to suggest interesting locations. Further, to ease the user's decision making, the amount of supplementary information, such as right time to visit, weather conditions, traffic condition, right mode of transport, crowdedness, security ... View full abstract»

With the wide spread usage of LBS, convenience has reached on the finger tips of mobile users, but on the other side, it has escalated many security and privacy concerns. In this paper we address the location K-anonymity problem using fuzzy spatio-temporal attributes, a new perspective of looking at privacy issue in location privacy. In the context of LBSs and mobile clients, location K-anonymity ... View full abstract»

The volume of spatio-temporal data is growing at a rapid pace. This is driven by several factors, including the widespread adoption of GPS-enabled mobile devices and the proliferation of RFID-tagged objects in sensor networks. Besides the volume, such spatio-temporal data is characterized by high "velocity", with its high rate of time-stamped location updates. The rise of spatio-temporal "Big data... View full abstract»

Group Activity Recognition (GAR) is a challenging research area in context-aware computing which has attracted much attention recently. Many studies have been conducted in the field of activity recognition (AR) along with their applications in domains such as health, smart homes, daily living and life logging. However, still many open issues exist. Lack of an energy-efficient approach is one of th... View full abstract»

Rising awareness of the environmental impacts of dominant mobility practices lead to the development of the sustainable mobility paradigm. This paradigm advocates three features of a mobility system: 1. A reduced need to travel, 2. Modal shift towards more sustainable options, and 3. Reduced vehicle kilometres travelled. In this paper, two sets of data are presented to explore the potential of ele... View full abstract»

In this paper, given a spatial range Q and a set of query points specified by users, the goal of this paper is to return the travel routes that fulfill two requirements: 1.) travel routes should contain all those query points specified, and 2.) travel routes should be within the spatial range Q. Furthermore, we claim that each query point may have its proper visiting time. As such, the travel rout... View full abstract»

We present methods to predict and validate home and work places of anonymized users using their mobile network data. Knowledge of home and work place of a user is essential in order to find his (and overall population) mobility profiles. There are many methods that predict home and work places using GPS data. But unlike GPS data, mobile network data using GSM do not provide the exact location of a... View full abstract»

With the increasing availability of human-tracking data (e.g., Public transport IC card data, trajectory data, etc.), human mobility prediction is increasingly important. In this paper, we study a novel problem of using human-tracking data to predict human mobility and to detect over-crowded stations in public transport networks, and then finding unobstructed routes to go around these over-crowded... View full abstract»

This work addresses the problem of energy efficient management of mobile resource distribution in Wireless Sensor Networks (WSN), subject to Quality of Service (QoS) constraints. Monitored phenomena may require an increased coverage within a particular area and we present novel methodologies for optimizing the "bargaining stage" when deciding how to select the mobile resources to be re-located in ... View full abstract»

Location-based services (LBSs) are important applications for mobile users. We consider an application in which the source node periodically disseminates location-based information in mobile ad hoc networks (MANETs). We define beneficial information as that which may be of benefit to mobile users planning to pass near the location related to the information. However, typically, mobile users change... View full abstract»

Peer-to-Peer technologies have been widely used in networks which manage vast amount of data daily. The proliferation of mobile devices strongly motivates mobile peer-to-peer network (M-P2P) applications, with benefits from network effects. We argue that logic programming for crowd sourcing can be useful in peer-to-peer computing for querying and multicasting tasks shared over peer networks. We in... View full abstract»

Public transportation is a key enabler of mobility in today's urban environment. Transportation service operators are exploring various technologies in order to be able to provide passengers accurate real-time information to plan their journeys. For them, the challenge is often in understanding where, when and how there is a demand. With rapid advancements in mobile technology, crowd sourcing or p... View full abstract»