Challenges and opportunities for data science and machine learning in iot systems--a timely debate: part 1

This position paper summarizes the main visions, opinions, and arguments of four experienced and well known researchers in the area of Internet of Things (IoT) and its relation to Data Science and Machine Learning (ML) as IoT permeates the globe and becomes “very large”. These visions were raised in an enthusiastic discussion panel held during the Third International Workshop on Very Large Internet of Things Systems (VLIoT 2019), in conjunction with VLDB 2019, in Los Angeles, USA. Each panelist delivered a vision statement before the floor was opened for questions and comments from the audience. Instead of reproducing ipsis literis each of the speeches, questions and replies, we decided to structure a two-part paper summarizing in-depth the panel opinions and discussions. In this first installment, we present the panelists' opening statements and views on issues related to IoT infrastructure and how it can support the growing demands for integrated intelligence, including communication, coordination and distribution challenges and how such challenges can be faced in the new generation of IoT systems.