[AISWorld] Special Issue (Q1 Journal | IoT Journal): AI-driven IoT Data Monetization: A Transition From “Value Islands” To “Value Ecosystems”

[IEEE COINS Conference]

*AI-driven IoT Data Monetization: A Transition From “Value Islands” To
“Value Ecosystems”*


IEEE Internet of Things Journal (Q1)

Submission Deadline: June  15, 2020
http://ieee-iotj.org/



IEEE Internet of Things Journal (IoT-J) Special Issue on

*AI-driven IoT Data Monetization: A Transition From “Value Islands” To
“Value Ecosystems”*



With the trajectory of the Internet of Things (IoT) moving at a rapid pace
and with the rapid worldwide development and public embracement of wearable
sensors, these days, most companies and organizations are awash in data.
However, discovering how to derive a profit from the data tsunami can
differentiate a business from its competitors. The potential for data to
deliver value for many parts of the business is tremendous. We have already
seen a layer of monetization across vertical domains by most organizations
embarking on the IoT journey where connected IoT things will be stacked
with various Software-as-a-Services, from smart insights to subscription
models. However, we are proceeding even further and what is emerging is the
evolutionary creation of the “machine data economy." Indeed, a unique
source of competitive advantage and differentiation in the digital economy
lies in the ability to leverage and monetize data effectively, rather than
simply hoarding it. The recent advent of the technological advancements in
all spheres of analytics — artificial intelligence, machine learning, big
data analytics, etc. — has paved the path for a new era of competitiveness
where IoT data is considered as a living and evolving asset that can unlock
enormous new opportunities for monetization. This has brought forth a slew
of architectures, tools, platforms, marketplaces, business models, and
trading spaces designed to enable companies to monetize data. For example,
recently, the digital world is witnessing the rise of new business models
aiming to tip the balance of power between users and the companies that
doing profit by ingesting, aggregating, analyzing, trading, and harvesting
customer data. In this context, several start-ups have started empowering
customers to monetize data by allowing them to sell their data directly to
the end data consumers e.g., advertisers. It should be noted that there is
not only one way to generate value by selling data resources, but also to
apply value-adding steps to make this resource even more valuable. In
general, data owners can take three main approaches to monetize their data:
(1) improving internal business processes and decisions e.g., using
data/information management, productizing information, and
informationalizing, (2) developing new services or products or improving
existing products or services, and (3) making raw data or extracted
insights/analysis available to customers and partners (e.g., data
marketplace). This special issue aims to address key challenges, such as
the development and provision of new business models, methods, and
architectures for IoT data monetization from the edge, to fog, cloud, big
data analytics, and data marketplace. In particular, we encourage original
and high-quality submissions related to one or more of the following topics
(but not limited to):



   - Multidisciplinary data monetization strategies
   - Benefits and risks of data monetization adoption by organizations
   - Challenges in topic discovery, data collection, and data preparation
   - Modern analytics architectures for data monetization
   - Blockchain and Distributed Ledger Technologies for data monetization
   - International Data Space (IDS) Architecture
   - Trust-oriented designs for IoT data monetization
   - Emerging trends and architectures in Edge-Cloud interplay for IoT Data
   monetization
   - Artificial intelligence for decision making in the era of Big Data
   - Big data analytics and deep learning techniques e.g., predictive
   maintenance, fraud detection, recommendation systems, people analytics,
   social media research, and omnichannel customer experience
   - Privacy-preserving machine learning algorithms and techniques for
   collaborating data monetization
   - Privacy and security aspects of data monetization



   - Secure embedded IoT devices in the era of IoT data monetization
   - Advanced computational technologies for data monetization
   - Economics of privacy and anonymity
   - Cross-market value delivery
   - Measurement and quantification of privacy and security risks
   - Economic models of data pricing
   - Privacy and anonymity models
   - Valuation of personal data
   - Protocols and architectures for data-price negotiation and data
   exchanging
   - Privacy-aware data monetization mechanisms
   - Privacy monitoring and auditing
   - Behavioral advertising
   - Impact on society and economy
   - Incentives for data disclosure
   - Primary challenges e.g., business focus, ownership, accountability,
   cultural, regulatory, and reputational barriers
   - Real-world experiences and use cases

*IMPORTANT DATES*

Submissions Deadline: June 15, 2020

Revision Due: October 15, 2020

Final Manuscript Due: November 30, 2020

First Reviews Due: August 30, 2020

Second Reviews Due: November 15, 2020

Publication Date: 2021



*SUBMISSION*

All original manuscripts or revisions to the IEEE IoT Journal must be
submitted electronically through IEEE Manuscript Central,
http://mc.manuscriptcentral.com/iot. Solicited original submissions must
not be currently under consideration for publication in other venues.
Author guidelines and submission information can be found at
http://ieee-iotj.org/. For additional information please contact the Guest
Editors by sending an email to <farshad.firouzi at duke.edu>



*GUEST EDITORS*

*Farshad Firouzi*, Duke University (farshad.firouzi at duke.edu)

*Mahmoud Daneshmand, *Stevens Institute of Technology

*Cesare Pautasso,* University of Lugano

*Bahar Farahani*, Shahid Beheshti University






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