This project suggests utilizing a deep learning system to classify IoT networks. The preprocessing technique receives the input data. The dataset’s null and repeated values are eliminated using this method. Following preprocessing, the preprocessed data is moved into the feature selection block. The feature selection process makes use of the chi square. The extraction areas are processed using the Chi Square technique to extract different characteristics and select the aspects that are needed to improve classification. Subsequently, the data extraction procedure moves on to categorization. Convolutional neural networks (CNNs) are utilized for classification based on the model’s performance analysis using CNN classification. This paper provides a useful model to classify IoT network traffic in an actual IoT scenario. The software used to implement this project is Python.