Chapter 7 - Knowledge Representation for Causal Calculi on Internet of Things

Abstract

The chapter introduces knowledge representation for expressing causal calculus in Internet of Things (IoT). This research discusses how IoT devices and sensors harness causal inference. Causal calculi are the mathematical foundations for expressing and computing causation. Causation describes how one event may cause another. IoT devices and systems may collect, parse, process, calculate, and send causal implications. There are several approaches to causal calculi. Independently Pearl and Shafer give causal systems. In addition, Halpern and Pearl give a causal system. Causal systems are founded in logic and probability theories—Pearl’s method uses Bayesian networks on acyclic directed graphs. Shafer’s method works on the dynamics of probability trees. And, the Halpern–Pearl model builds on Pearl’s model yielding two causal views. One of these views attribute causes of past while the other view focuses on causal reasoning giving events.