Clustering on the Chicago Array of Things: Spotting Anomalies in the Internet of Things Records

Clustering on the Chicago Array of Things: Spotting Anomalies in the Internet of Things Records

The Chicago Array of Things (AoT) is a robust dataset taken from over 100 nodes over four years. Each node contains over a dozen sensors. The array contains a series of Internet of Things (IoT) devices with multiple heterogeneous sensors connected to a processing and storage backbone to collect data...

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Bibliographic Details
Main Authors: Kyle DeMedeiros, Chan Young Koh, Abdeltawab Hendawi
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Future Internet
Subjects:
sensor network
IoT
anomaly detection
clustering
machine learning
neural networks
Online Access:https://www.mdpi.com/1999-5903/16/1/28

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