Challenges and Opportunities for Data Science and Machine Learning in IoT Systems – A Timely Debate: Part 2

Abstract

In Part 1 of this two-part article, we presented the first installment of a panel that was held within the Very Large Internet of Things Workshop (VLIoT) held in conjunction with the Very Large Data Bases (VLDB) conference in Los Angeles, California, in August of 2019. The panel addressed the challenges and opportunities in the intersecting areas of IoT, Data Science and Machine Learning. We presented the opening statements of four panelists, and a discussion of numerous questions addressing infrastructure issues and how it can support the growing demands for integrated intelligence, including communication, coordination, and distribution. In this second installment, we cover the remainder of this important debate focusing on the critical issues of scalable information and event processing, embedded machine learning, security and privacy, and speculating about the new business models that could soon be emerging as IoT meets Data Science and Machine Learning.