Document Type

Article

Publication Title

arXiv

Abstract

Pandemics and natural disasters over the years have changed the behavior of people, which has had a tremendous impact on all life aspects. With the technologies available in each era, governments, organizations, and companies have used these technologies to track, control, and influence the behavior of individuals for a benefit. Nowadays, the use of the Internet of Things (IoT), cloud computing, and artificial intelligence (AI) have made it easier to track and change the behavior of users through changing IoT behavior. This article introduces and discusses the concept of the Internet of Behavior (IoB) and its integration with Explainable AI (XAI) techniques to provide trusted and evident experience in the process of changing IoT behavior to ultimately improve user behavior. Therefore, a system based on IoB and XAI has been proposed in a use case scenario of electrical power consumption that aims to influence user consuming behavior to reduce power consumption and cost. The scenario results showed a decrease of 522.2 kW of active power when compared to original consumption over a 200-hours period. It also showed a total power cost saving of C95.04 for the same period. Moreover, decreasing the global active power will reduce the global intensity through the positive correlation. © 2021, CC BY.

DOI

10.48550/arXiv.2109.07239

Publication Date

9-15-2021

Keywords

Behavioral research, Deep learning, Disasters, Electric power utilization, Active power, Artificial intelligence systems, Deep learning, Energy sustainability, Government companies, Government organizations, Internet of behavior, Natural disasters, Track control, XAI, Internet of things, Artificial Intelligence (cs.AI), Computers and Society (cs.CY), Distributed, Parallel, and Cluster Computing (cs.DC), Machine Learning (cs.LG)

Comments

Open access version thanks to arXiv

License: CC BY 4.0

Uploaded July 05, 2022

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