Industry 4.0 Convergence with AI, IoT, Big Data and Cloud Computing: Fundamentals, Challenges and Applications

Explainable Artificial Intelligence (XAI) for IoT

Author(s): Prashant C. Dhas*, Parikshit N. Mahalle and Gitanjali R. Shinde

Pp: 150-160 (11)

DOI: 10.2174/9789815179187123040013

* (Excluding Mailing and Handling)

Abstract

Artificial Intelligence and Machine Learning are the latest topics across industries. A lot of concentration has been given to these areas and still the adoption has been challenged by users and experts in this field in the search for some kind of solution to be provided that the output can be trusted by all. The purpose of this paper is to focus on the sensor data coming from various IoT devices and how the data can be interpreted by various available algorithms. The ML algorithm is considered a black box with a focus on providing the required output without finding the causes behind the decision and working mechanism provided by that model. In this chapter, we tried to explain various common techniques/models available for eXplainable Artificial Intelligence (XAI) and how those can be used for IoT data. 


Keywords: Artificial intelligence, Explainable artificial intelligence (XAI), Machine learning (ML), The internet of things (IoT).

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