
TL;DR
This paper discusses how big data analytics enhances the Internet of Things by enabling sophisticated data processing and decision-making across interconnected devices, with implications for performance improvement and social concerns.
Contribution
It provides an overview of the role of big data analytics in IoT, highlighting current impacts, future potential, and social implications.
Findings
Big data analytics significantly improves IoT device performance.
IoT ecosystem benefits from advanced data analytics techniques.
Social and ethical concerns are associated with IoT data use.
Abstract
Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBig Data and Business Intelligence · IoT and Edge/Fog Computing
