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.