Jammer Detection on Embedded Android Implementation: Blue Bird Group Case Study

As one of the largest transportation companies in Indonesia. Blue Bird Group know that keeping our driver competition healthy is one of the biggest concerns of our engineering team. The malicious behaviour of one driver can affect other drivers’ performance. The presence of the Internet of Things (IoT) in Blue Bird Group’s fleet can provide a predictive detection of such behaviour so that the operation team can act accordingly. This paper provides an overview of the Blue Bird Group’s implementation of jammer detection to minimize the usage of jamming devices and build trust among our drivers. In each of our fleets, there is an IoT device embedded to help our driver receive orders and the company track its fleet. The idea is to embed an artificial intelligence model on the IoT device and use Android API to provide information for the artificial intelligence model to process. Blue Bird Group also build a web-based control centre that provides information on the malicious driver’s behaviour. The first model has 94.18% accuracy and 11% loss, and the second model has 100% accuracy and 0% loss.