Elsevier's Pervasive and Mobile Computing (PMC) journal
Special issue on "Crowd-sensed Big Data for Internet of Things Services"

The advent of Internet of Things (IoT) is creating huge research challenges for the industry and academia, towards novel potential impacts on the monitoring, control and understanding of world, weather, social life, security, health, emergencies and so on. The solutions to those challenges are expected soon to provide an effective and scalable support for the computation, data storage, analysis and use of the data that will be created by the explosive adoption of the IoT and machine to machine communication in a number of contexts. The IoT revolution has already started and there is a risk that immature "de facto" solutions will take momentun without the required background of design and analysis, resulting in a weak basis against future challenges. Moreover, issues concerning the privacy, anonimity, protection and abuse of data must be resolved on a standard platform under a paradox situation where data location and ownership are often an intrinsic value of the data itself.

Thanks to the cost reduction of pervasive sensing devices often found in off-the-shelf technology, and new wireless standards that enabled new communication and services paradigms, crowd-sensing and Big Data have already revealed their huge potential for innovation and services deployment, still waiting the IoT to explode. Crowd-sensing data has revealed to be a very effective distributed solution for gathering data where the cost for dedicated infrastructure and platform is unaffordable. Specific additional challenges include policies for boosting and rewarding the data provision through gamification, entertainment, and value-added services.
On a Big Data perspective, the new age of data, though in its infancy, has started and the world is still possibly not fully aware and prepared to the incredible demand created for storage, scalable data management, interoperable data access and analysis solutions, as well as new generation middleware and application/services paradigms (e.g Industry 4.0) and platforms.

Challenges like data heterogeneity and interoperability, natural language processing, data mining and analytics, scalability of storage and analysis solutions based on AI and Beyond-Turing paradigms, edge/fog/cloud computing, communication platforms' bottlenecks, privacy and security will be stressed by the expected provision of new data coming out from the IoT and crowd-sensing data sources. Recent analyses provided incredible numbers: 150 billions of connected sensors within 10 years will double the quantity of available data every 12 hours, with a magnitude of 40 ZettaByte (1 ZB = 1e21 Bytes) per year already in 2020.
The set of themes illustrated for research is huge, however, the focus of this special issue is more specifically on Crowd-sensed Big Data for Internet of Things Services.

Topics of interest for this special issue include, but are not limited to:
* Crowd-sensing devices prototypes
* Mobile Applications for Crowd-sensing
* Gamification techniques for Crowd-sensing campaigns
* Heterogeneous data integration
* Data Interoperability
* Semantic technologies for IoT
* Web platforms for IoT
* Machine learning techniques for big data
* NLP for data classification
* Data mining
* Interfaces to exploit big data
* Open data integration for IoT
* IoT for smart cities
* IoT services built on big data
* IoT services built on crowd-sensed data
* IoT interoperability
* Security and Privacy for Crowd-sensed data
* Crowd-sensed data anonymization
* Innovative Crowd-sensing methodologies
* Other emerging new topics


Important Dates
Submission deadline: November 15, 2017
Initial feedback to authors: March 15, 2018
Final notification: June 15, 2018

Submission Guidelines
All submissions have to be prepared according to the Guide for Authors as published in the Journal Web Site at http://www.journals.elsevier.com/pervasive-and-mobile-computing/.
Submissions should be sent through http://www.evise.com/evise/jrnl/PMC
Authors should select "VSI:Crowdsensed Big Data-IoT", from the "Choose Article Type" pull-down menu during the submission process. All contributions must not have been previously published or be under consideration for publication elsewhere. A submission based on contribution from one or more papers that appeared elsewhere has to comprise major value-added extensions (at least 30% new contribution of high relevance). In that case, authors are requested to attach to the submitted paper their relevant, previously published articles and a summary document explaining the additional contribution made in the journal version.

Guest Editors of the Special Issue
- Dr. Luca Bedogni, University of Bologna, Italy.
- Prof. Salil Kanhere, The University of New South Wales, Australia,
- Prof. Hongyi Wu, ECE dept, Old Dominion University, Virginia, USA
- Prof. Luciano Bononi, University of Bologna, Italy