An overview of the importance of vehicle count and classification data as inputs for intelligent transportation systems (ITS). A very promising solution for measuring various traffic factors is provided by technology based on magnetic sensors. A single magnetometer is used in this study to offer a revolutionary real-time vehicle detection and classification model. External equipment is not required to execute the necessary computations because the detection, feature extraction, and classification are done online. An apparatus set into the pavement's surface was used to collect data in an actual setting. The suggested technique was trained and validated using an enormous number of data that contained measurements of different vehicle classes. Nine distinct vehicle classes were used to investigate the capabilities of magnetometers, which is significantly more than in comparable methodologies. Artificial neural networks (ANNs) with three layers of feed forward are used for the classification.