FCS Special section on
IoT enabled Business Data Analytics
Recent years have witnessed rapid development of Internet of Things (IoT), which drives many applications such as urban computing, unmanned supermarket, smart house, smart logistics, etc. The ubiquitous sensors and GPS devices installed on smartphones have been utilized as basic IoT infrastructure to support these distinct applications, reshaping human behaviors as well as the relationships and interaction patterns between human, things, and the environment. As all the things are connected in a network enabled by IoT infrastructure, the status of each object can be monitored in real-time, which opens up new perspectives for traditional management and poses great challenges for operational and managerial decisions in real business scenarios.
Indeed, the marriage of IoT and management suggests the possibility of an unshaped yet tangible new scientific paradigm. On one hand, data is generating in million-second scale from IoT infrastructure, which can help disclose behavioral patterns and corresponding working conditions and thus calls for detailed data management and analytical solutions. On the other, management and decisions can be operated in a more delicate way, because the granularity of control can be as tiny as each monitored object, which calls for more research on new management problems aroused by the proliferation of IoT, including decision process, scheduling strategies, quality control, value creation, etc.
This special issue aims to bring together scholars from both computer science and management science to integrate IoT applications with the interdisciplinary field of management, in order to propose new management visions, novel algorithms and strategies to tackle the challenges with the advancement of IoT technology. Topic of interests include but not limited to:
● Management theories in IoT
● Big data management and analytics inIoT
● Mechanism design in IoT enabledapplications
● Behavioral analysis inIoT
● Operation management inIoT
● Value creation and governance in IoTenvironment
● Modeling organizational structure underIoT
● Intelligent scheduling by way of IoTinfrastructures
● Intelligent monitoring and quality control based on IoTinfrastructure
● IoT applications in smart city, smart house,etc.
● Ubiquitous IoTcomputing
● Perspectives about future trends of IoT enabled business analytics
Manuscript SubmissionDeadline: 2018/12/31
Initial Decision: 2019/3/31
R1 Version: 2019/5/31
Acceptance Notification: 2019/6/30
Final Manuscripts Due: 2019/7/15
Submissions will be evaluated on a "first-come-first-served" basis. The manuscripts submitted before the deadlines will be reviewed and notified ahead of the schedule.
The submitted papers will be evaluated based on their originality, presentation, relevance and contributions, as well as their suitability to the special issue. The submitted papers must be written in English and describe original work that has not been published nor currently under review by any journals and conferences. Previously published conference papers should be clearly identified by the authors at the submission stage and a summary of changes should be provided about how such papers have been significantly changed and extended to be considered for this special issue. Papers that either lack originality, clarity in presentation or fall outside the scope of the special issue will be rejected without reviews.
Submissions need to conform to the layout, format limits in Frontiers of Computer Science (FCS). The submitted papers will be reviewed by at least three independent reviewers. Final decisions will be approved by the journal editors. Manuscripts need to be prepared for publication according to the journal’s Author Guidelines available at FCS.
Submission Website: http://mc.manuscriptcentral.com/hepfcs
Please select “IoT enabled Business Data Analytics” tag when you submit your paper, and indicate “Submission to Special Issue on IoT enabled Business Data Analytics” in the cover letter.
Junjie Wu, Beihang University, China, firstname.lastname@example.org
Jingyuan Wang, Beihang University, China, email@example.com
Xiangpei Hu, Dalian University of Technology, China, firstname.lastname@example.org
HuiXiong, Rutgers University, USA, email@example.com