1,078 research outputs found
Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey
The integration of things’ data on the Web and Web linking for things’ description and discovery is leading the way towards smart Cyber–Physical Systems (CPS). The data generated in CPS represents observations gathered by sensor devices about the ambient environment that can be manipulated by computational processes of the cyber world. Alongside this, the growing use of social networks offers near real-time citizen sensing capabilities as a complementary information source. The resulting Cyber–Physical–Social System (CPSS) can help to understand the real world and provide proactive services to users. The nature of CPSS data brings new requirements and challenges to different stages of data manipulation, including identification of data sources, processing and fusion of different types and scales of data. To gain an understanding of the existing methods and techniques which can be useful for a data-oriented CPSS implementation, this paper presents a survey of the existing research and commercial solutions. We define a conceptual framework for a data-oriented CPSS and detail the various solutions for building human–machine intelligence
Studying user behavior through a participatory sensing framework in an urban context
A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsThe widespread use of mobile devices has given birth to participatory sensing,
a data collection approach leveraging the sheer number of device users, their
mobility, intelligence and device’s increasingly powerful computing and sensing
capabilities. As a result, participatory sensing is able to collect various types of
information at a high spatial and temporal resolution and it has many applications
ranging from measuring cellular signal strength or road condition monitoring to
observing the distribution of birds. However, in order to achieve better results from
participatory sensing, some issues needed to be dealt with. On a high level, this
thesis addressed two issues: (1) the design and development of a participatory
sensing framework that allows users to flexibly create campaigns and at the same
time collect different types of data and (2) the study of different aspects of the user
behaviors in the context of participatory sensing.
In particular, the first contribution of the thesis is the design and development of
Citizense, a participatory sensing framework that facilitates flexible deployments
of participatory sensing campaigns while at the same time providing intuitive
interfaces for users to create sensing campaigns and collect a variety of data
types. During the real-world deployments of Citizense, it has shown its effectiveness
in collecting different types of urban information and subsequently received
appreciation from different stakeholders. The second contribution of the thesis
is the in-depth study of user behavior under the presence of different monetary
incentive mechanisms and the analysis of the spatial and temporal user behavior
when participants are simultaneously exposed to a large number of participatory
sensing campaigns. Concerning the monetary incentive, it is observed that participants
prefer fixed micro-payment to other mechanisms (i.e., lottery, variable
micro-payment); their participation was increased significantly when they were
given this incentive. When taking part in the participatory sensing process, participants exhibit certain spatial and temporal behaviors. They tend to primarily
contribute in their free time during the working week, although the decision to
respond and complete a particular participatory sensing campaign seems to be
correlated to the campaign’s geographical context and/or the recency of the participants’
activities. Participants can be divided into two groups according to their
behaviors: a smaller group of active participants who frequently perform participatory
sensing activities and a larger group of regular participants who exhibit more
intermittent behaviors
Advanced Information Services for Cognitive Behaviour of Travellers
Smart transportation is essentially leveraged by
decision making of humans, especially behaviour of
travellers.
The behaviour (movements; information management) and the
advanced information services are mutually entangled. The
travellers and the ICT (integrated infocommunication systems
of
transportation) is considered as an undecomposable set, which
has new cognitive capabilities. These capabilities are to be
used
for mobility related decisions in order to improve
sustainability
of transportation.
In order to reveal, how these capabilities coelvolve with
smart
transportation comprehensive system and process-oriented
scientific research had been launched. Herewith the basic
definitions, the architecture and the operation of the
integrated
system of smart transportation and the model of the smart
traveller have been presented following top-down approach of
system engineering
Health Participatory Sensing Networks for Mobile Device Public Health Data Collection and Intervention
The pervasive availability and increasingly sophisticated functionalities of smartphones and their connected external sensors or wearable devices can provide new data collection capabilities relevant to public health. Current research and commercial efforts have concentrated on sensor-based collection of health data for personal fitness and personal healthcare feedback purposes. However, to date there has not been a detailed investigation of how such smartphones and sensors can be utilized for public health data collection. Unlike most sensing applications, in the case of public health, capturing comprehensive and detailed data is not a necessity, as aggregate data alone is in many cases sufficient for public health purposes. As such, public health data has the characteristic of being capturable whilst still not infringing privacy, as the detailed data of individuals that may allow re-identification is not needed, but rather only aggregate, de-identified and non-unique data for an individual. These types of public health data collection provide the challenge of the need to be flexible enough to answer a range of public health queries, while ensuring the level of detail returned preserves privacy. Additionally, the distribution of public health data collection request and other information to the participants without identifying the individual is a core requirement. An additional requirement for health participatory sensing networks is the ability to perform public health interventions. As with data collection, this needs to be completed in a non-identifying and privacy preserving manner. This thesis proposes a solution to these challenges, whereby a form of query assurance provides private and secure distribution of data collection requests and public health interventions to participants. While an additional, privacy preserving threshold approach to local processing of data prior to submission is used to provide re-identification protection for the participant. The evaluation finds that with manageable overheads, minimal reduction in the detail of collected data and strict communication privacy; privacy and anonymity can be preserved. This is significant for the field of participatory health sensing as a major concern of participants is most often real or perceived privacy risks of contribution
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