7,112 research outputs found
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
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
When mobile crowd sensing meets traditional industry
With the evolution of mobile phone sensing and wireless networking technologies, mobile crowd sensing (MCS) has become a promising paradigm for large-scale sensing applications. MCS is a type of multi-participant sensing that has been widely used by many sensing applications because of its inherent capabilities, e.g., high mobility, scalability, and cost effectiveness. This paper reviews the existing works of MCS and clarifies the operability of MCS in sensing applications.With wide use and operability of MCS, MCS’s industrial applications are investigated based on the clarifications of (i) the evolution of industrial sensing, and (ii) the benefits MCS can provide to current industrial sensing. As a feasible industrial sensing paradigm, MCS opens up a new field that provides a flexible, scalable, and costeffective solution for addressing sensing problems in industrial spaces
Crowdsourcing as a tool for urban emergency management: lessons from the literature and typology
Recently, citizen involvement has been increasingly used in urban disaster prevention and
management, taking advantage of new ubiquitous and collaborative technologies. This scenario has
created a unique opportunity to leverage the work of crowds of volunteers. As a result, crowdsourcing
approaches for disaster prevention and management have been proposed and evaluated. However,
the articulation of citizens, tasks, and outcomes as a continuous flow of knowledge generation reveals
a complex ecosystem that requires coordination efforts to manage interdependencies in crowd work.
To tackle this challenging problem, this paper extends to the context of urban emergency management
the results of a previous study that investigates how crowd work is managed in crowdsourcing
platforms applied to urban planning. The goal is to understand how crowdsourcing techniques
and quality control dimensions used in urban planning could be used to support urban emergency
management, especially in the context of mining-related dam outages. Through a systematic literature
review, our study makes a comparison between crowdsourcing tools designed for urban planning and
urban emergency management and proposes a five-dimension typology of quality in crowdsourcing,
which can be leveraged for optimizing urban planning and emergency management processes
Human Computation and Convergence
Humans are the most effective integrators and producers of information,
directly and through the use of information-processing inventions. As these
inventions become increasingly sophisticated, the substantive role of humans in
processing information will tend toward capabilities that derive from our most
complex cognitive processes, e.g., abstraction, creativity, and applied world
knowledge. Through the advancement of human computation - methods that leverage
the respective strengths of humans and machines in distributed
information-processing systems - formerly discrete processes will combine
synergistically into increasingly integrated and complex information processing
systems. These new, collective systems will exhibit an unprecedented degree of
predictive accuracy in modeling physical and techno-social processes, and may
ultimately coalesce into a single unified predictive organism, with the
capacity to address societies most wicked problems and achieve planetary
homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added
references to page 1 and 3, and corrected typ
Raising awareness for water polution based on game activities using internet of things
Awareness among young people regarding the environment and its resources and comprehension of the various factors that interplay, is key to changing human behaviour towards achieving a sustainable planet. In this paper IoT equipment, utilizing sensors for measuring various parameters of water quality, is used in an educational context targeting at a deeper understanding of the use of natural resources towards the adoption of environmentally friendly behaviours. We here note that the use of water sensors in STEM gameful learning is an area which has not received a lot of attention in the previous years. The IoT water sensing and related scenaria and practices, addressing children via discovery, gamification, and educational activities, are discussed in detail
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