Industrial Internet of Things (IIoT) applications use the observability, control, and analytics of industrial processes while also guaranteeing the safety of these environments. IIoT applications are typified by data-centric innovations. In IIoT deployments, the use of wireless connections is growing quickly as a means of enhancing operational connectivity for industrial data services. These services include monitoring of equipment, parts, and goods on the factory floor and elsewhere, as well as communications with industrial robots and massive process data collecting. To develop wireless systems for Internet of Things (IoT) applications, wireless network planners, operational technology (OT) engineers, and information technology (IT) system architects collaborate. This method is inherently cooperative. Interference from radio waves may hinder data transmission in wireless networks. Furthermore, because of the weak signal, some data packets can be dropped during transmission. As a consequence, network operations are unpredictable and data transfer is dangerous. In order to ensure the long-term viability of IEEE 802.11 networks, this study investigates co-channel and neighbouring channel interference. This study aims to quantify the degree of signal interference that access points encounter and the effect that interference has on network performance. To track and calculate interference in the wireless network, the Riverbed Modeller tool was used. The study's conclusions suggest that the main underlying cause of excessive interference in wireless Industrial Internet of Things applications (IIoT) is the improper channel assignment to access points.