IoT 2015 - Special Issue on Mobile Crowd Sensing for IoT

The ubiquitous sensor-rich mobile devices (smartphones, wearable devices, smart vehicles) have been playing an increasing important role in the evolution of the Internet of Things (IoTs), which bridge the digital space and physical world at a societal scale. Their powerful computing/communication capacities, huge population, and inherent mobility makes mobile-device networks a much more flexible and cost-effective IoT solution than static sensor networks. This promotes the emergence of a fast-growing consumer-centric sensing paradigm, the Mobile Crowd Sensing (MCS). As an evolution of participatory sensing, MCS has two unique features: (1) it involves both implicit and explicit participation; (2) MCS collects data from two user-participant data sources:
mobile social networks and mobile sensing. Various categories of knowledge (e.g. location, personal and social context, user feelings/opinions, traffic conditions, and pollution) reported by smart device users, are shared within the social sphere, practitioners, health care providers, and utility providers, enabling a broad range of applications and services such as urban dynamic mining, public safety, and environment monitoring. Numerous research challenges arise from the MCS paradigm including participatory and opportunistic data collection, incentive mechanism design, transient networking, quality of user-contributed data, privacy concerns, and big data processing and analytics. This special issue provides the opportunity for researchers, practitioners, and application developers to review and discuss the state-of-the-art and trends of MCS techniques and applications or propose new solutions. In particular, we solicit high-quality original research papers on MCS, including but not limited to the following topics:
? IoT Architecture/Framework for MCS
? Optimized Data Collection Task Allocation
? Communication in Transient Networking Environments
? Crowdsourced Data Processing and Urban/Social Context Mining
? Incentive Mechanisms for Participatory Sensing
? Heterogeneous Crowdsourced Data Fusion
? Dealing with Low Quality Data in MCS
? Trust and Privacy Issues in MCS
? MCS for Social Networking
? Hybrid Human-Machine Intelligence in MCS
? Emerging/Novel MCS Apps and Systems (environment monitoring, public safety, traffic planning, etc.)