The Internet of Things (IoT) is rapidly emerging as a transformational paradigm with a multitude of products and services now available and being adopted by corporations as well as individuals seeking to harness the vast opportunities it offers.
But we do face a major obstacle in realizing the full potential of the IoT. The sheer variety, volume and velocity of data generated by the IoT presents unprecedented challenges in deriving meaningful and actionable insights and calls for a strategic approach to data management and usage. These approaches also need to address business strategies, business processes, enterprise architecture, systems and applications, and security and privacy considerations. It is also important to examine and decide what data is to be captured and on which device(s), how to store and extract that data, and how to glean value from data that will result in new and improved products and services, better decision-making, or enhanced policy development.
An upcoming issue of Cutter IT Journal with Guest Editors San Murugesan and Bhuvan Unhelkar seeks insight on strategies for leveraging the potential of the IoT including data management and analytics. We welcome articles from practitioners as well as academics involved in application-oriented or industry-based research, and/or those who can share practical experience, present empirical evidence, or offer recommendations on successfully harnessing the potential of the IoT and the data it generates.
Possible discussion points include those mentioned above, as well as, but not limited, to the following:
- What are the key challenges in realizing the full potential of the IoT and the data it generates, and how can we address these challenges?
- What are some effective strategies for managing IoT data? Are they different from managing traditional enterprise (big) data, and if so, how?
- How can big data technologies such as the Hadoop Eco system and NoSQL be effectively used in managing IoT data? How can Enterprise Architecture (EA) help in strategizing the IoT?
- How can we derive value from the variety of data the IoT can potentially generate?
- What types of data analytics are appropriate, and under which circumstances?
- Do IoT analytics differ from other analytic applications, and if so, how?
- What are the platforms or computational techniques that are suited better for IoT analytics?
- What are some appealing IoT use cases?
- How can various types of IoT data analytics be used in effective decision making, say by business executives, buyers/clients, or individuals for personal enhancements?
- What approaches are available for operational analytics of IoT data?
- How can we better integrate IoT data with enterprise information systems and organizational operational data?
- How does the role of the CIO, CTO or data scientist get redefined in the context of an IoT-enabled, ubiquitously connected environment?
- How can we successfully transition from current business processes to IoT-based (driven) business processes?
- How can IoT data be used for creating ‘augmented reality’ or ‘assisted living’?
ARTICLE IDEAS DUE: FEBRUARY 26, 2016
Please send your article ideas to Bhuvan Unhelkar at bhuvan[dot]unhelkar[at]gmail.com and San Murugesan at san1[at]internode[dot]net with a copy to cgenerali[at]cutter[dot]com no later than February 26, 2016 and include an extended abstract and a short article outline showing major discussion points.
Accepted articles are due by APRIL 1, 2016.