In industrial internet of things (IIoT), some data obtained may experience problems during the communication process between nodes that cause high latency, channel limitations, and network congestion. Therefore, detection of faulty nodes is necessary. Various methods for detecting faulty nodes in IIoT and an overview of their systems are discussed in this paper. However, the previous solution experienced a long delay in identifying and isolating nodes that produced incorrect data. Artiﬁcial intelligence (AI) is a good solution to this problem because of its ability to accelerate time thereby reducing computing time and delays. Main purpose of this paper is to serve a framework for researchers about how faulty nodes in IIoT can be detected, the weaknesses of each system related to the problem of delay, and propose a mechanism which allows each node to rapidly identify whether it produces faulty data.