Mobile Crowd Sensing and Computing

Abstract

With the surging of smartphone sensing, wireless networking, and mobile social networking techniques, Mobile Crowd Sensing and Computing (MCSC) has become a promising paradigm for cross-space and largescale sensing. MCSC extends the vision of participatory sensing by leveraging both participatory sensory data from mobile devices (offline) and user-contributed data from mobile social networking services (online). Further, it explores the complementary roles and presents the fusion/collaboration of machine and human intelligence in the crowd sensing and computing processes. This article characterizes the unique features and novel application areas of MCSC and proposes a reference framework for building human-in-the-loop MCSC systems. We further clarify the complementary nature of human and machine intelligence and envision the potential of deep-fused human-machine systems. We conclude by discussing the limitations, open issues, and research opportunities of MCSC. . 2015. Mobile crowd sensing and computing: The review of an emerging human-powered sensing paradigm.

Building a platform to collect crowdsensing data. Preliminary considerations

“…This would involve performing a thorough literature review in both fields and extracting the significant concepts that can be used to classify and characterize such a system. In addition, exploring open challenges in the field of MCSC, as outlined in [13] would prove a worthy endeavour. With regards to the language specification category, work would focus on improving the expressiveness of the domain specific TSL.…”

“…Next, [11] further elaborated on MCS and highlighted its roots in participatory sensing [12], while [13] expanded this concept into mobile crowd sensing and computing (MCSC), thereby highlighting the increased computing power possessed by the current generation of mobile devices. Since then, the field has seen a steady increase in publications across the major journals.…”

Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey

“…The vast amounts of data obtained by the sensing of physical phenomena by distributed sensor networks and those contributed by city inhabitants through their sensor-enabled smartphones and on online social networks, can offer near real-time large-scale sensing for intelligence mining to facilitate responsive and intelligent services in urban settings [13]. Extracting knowledge out of the data, typically through big data analytics techniques, can help to build a picture of urban dynamics, which can enable intelligent applications and services, and guide decision-making, both for city authorities and city inhabitants [21].…”

“…Shih et al [45] review the middleware, computation model, data quality and run-time environments necessary for smart building and smart city implementations, while Salim et al [46] survey approaches for engaging human interaction with urban computing technologies. A survey of mobile crowd sensing approaches [13] that is closely aligned to this paper, presents a taxonomy based on the data collection steps, processing architecture and resulting applications. In contrast to these surveys, this article collects works on urban CPSS implementations and organizes them from a data perspective.…”

“…The high installation cost of fixed sensor networks and insufficient spatial coverage has led to mobile sensing initiatives, primarily by city authorities [13], which involve sensors mounted on public transportation vehicles (e.g., for environment monitoring [14][15][16]). …”