Document Type

Paper

Subject Area(s)

Computer and Information Sciences

Abstract

Thousands of academic articles have been written about the various facets of the Internet of Things (IoT). Added to those are books of multiple flavors, conference proceedings, and a host of web-based content authored by a diverse cast of IoT community constituents. While there are many examples of successful IoT application solutions, participating technologies and how best to use them, are still relatively immature. These solutions are complex, geographically diverse, incorporate a broad spectrum of ever-evolving technologies that allow organizations to gather new data, create new value and do new things they haven’t been able to do effectively before.

Despite the promise, excitement, and future thinking that leads organizations to pursue IoT projects, many of those projects have fallen short of original expectations. Too many projects fail, never making it past the pilot stage for many reasons. Authors elsewhere have written and are continuing to write about those IoT experiences, so they are not addressed in this paper. Instead, this paper looks at three critical data issues arising from the deployment of IoT solutions: 1. The magnitude of data being collected and stored from IoT solutions, and challenging if all such data is necessary; 2. How little of this data is actually being used and why; and 3. The concerns held by many users about poor data quality, what causes it, and what can be done about it. At the heart of every IoT solution are multitudes of sensors of all shapes, sizes, and purposes. It becomes apparent that sensors may be the largest source of data defects that when unresolved contribute significantly to poor solution data quality. To better understand this premise, this paper looks at the challenges inherent in sensor-generated data and possible approaches for mitigating its impact.

Download

Share

COinS