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

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

DOI: 10.2174/9789815179187123040013

Explainable Artificial Intelligence (XAI) for IoT

Pp: 150-160 (11)

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Abstract

SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.

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. 

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