mlsanityData to 7 Oct 2026

Internet of Behavior (IoB) and Explainable AI Systems for Influencing IoT Behavior

arXiv 2109.07239 ↗First posted 15 Sep 2021cs.DC cs.AI cs.CYcited by 3

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Abstract (arXiv)

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 improving users' 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 95.04 Euro for the same period. Moreover, decreasing the global active power will reduce the power intensity through the positive correlation.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 1 of its 20 references that are in the map. First posted on arXiv 15 Sep 2021.

Builds on

1 of 20 references.

References · 1

  1. 2020Distributed Deep Reinforcement Learning for Intelligent Load Scheduling in Residential Smart Gridscited by 10

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Citing papers per year: 2022: 2; 2023: 1.

3 papers.