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Detecting and characterising vehicles is one of the purposes of embedded systems used in intelligent environments. An analysis of a vehicle’s characteristics can reveal inappropriate or dangerous behaviour. This detection makes it possible to sanction or notify emergency services to take early and practical actions. Vehicle detection and characterisation systems employ complex sensors such as video cameras, especially in urban environments. These sensors provide high precision and performance, although the price and computational requirements are proportional to their accuracy. These sensors offer high accuracy, but the price and computational requirements are directly proportional to their performance. This article introduces a system based on modular devices that is economical and has a low computational cost. These devices use ultrasonic sensors to detect the speed and length of vehicles. The measurement accuracy is improved through the collaboration of the device modules. The experiments were performed using multiple modules oriented to different angles. This module is coupled with another specifically designed to detect distance using previous modules’ speed and length data. The collaboration between different modules reduces the speed relative error ranges from 1 to 5%, depending on the angle configuration used in the modules.

En este artículo se describe una estrategia de control distribuida, utilizando elementos empotrados, mediante un middlewarede control denominado núcleo de control, en el que se implementan controladores digitales de altas prestaciones, diseñados de forma modular, en sistemas con capacidad de cómputo limitada. Se presenta una metodología tanto para la obtención de una métrica que permita la comparación de los distintos modos de funcionamiento ante pérdidas de datos, como para la elección de los parámetros de los controladores a implementar en cada nodo del sistema distribuido de control. Se presentan varios modos de funcionamiento que permite adaptar el sistema desarrollado a distintas situaciones. El trabajo se completa con la implementación de la simulación del sistema distribuido y su prueba sobre un proceso real.