Fuzzy decision method to improve the information exchange in a vehicle sensor tracking system

Abstract

Internet of Things is based on the identification of real-world objects in a unique way that interconnects them by means of communication interfaces. Such a simple idea allows the emergence of a huge number of new applications in almost any domain of knowledge. One of the most prominent areas of application is road vehicles, which currently have, on average, more than 50 sensors inside and which information can be accessed through a standard protocol. With this, vehicles have become real smart objects that can interact with other objects or any software system. To allow that, our previous work focused on proposing and developing the Vitruvius platform, where users with no programming knowledge can design and quickly generate Web applications based on the real-time data consumption from interconnected vehicles. The problem is that the sending of such information is out of control, being unable to filter out when the best time to send the information is and what information should be sent at any moment in order to minimize the resource consumption of the mobile device that acts as a bride between the vehicle and the database in which all the information is stored. Thus, in this work we propose a fuzzy algorithm that allows to optimize the resources that are used by real-time applications that constantly send data while maintaining data quality, contextualized in vehicle sensor tracking systems and the applications that can be built above them.