This paper is a contribution to the problems of road insecurity in Africa. Due to non-respect of road sign and to the lack of signing, roads have become places of all dangers. It becomes imperative to establish an interaction between the authorities and the offending drivers. To reach this goal, we modelled an interactive road-vehicle-signage system, who locally informs the driver on the requirements of traffic signs. This model having interest only in the event of driving by bad weather or deterioration of panels, we are amending by inserting functions aimed to warn and punish the driver in the event of maintenance of an offense. Indeed, when the driver is about to commit a fault, firstly the system issues a warming (visual, audible or mechanical). Then, a message (SMS) is sent to the authorities. We include the concept of floating process engaged by devices other than the signage. We show that, with a few considerations, from the functional point of view, they are identical to the process engaged by the signage. Furthermore, in terms of performance, the model renewed warnings that occurred just before the end panel of prohibitions. It stores messages of offenses occurred without the network, then notifies them when a network is detected. We propose algorithms for incremental design and analysis of the model, whose processes are activated and / or are extinguished, according to the type of sign or tag encountered. We show by simulation and by linear algebra that, the model retains its properties of absence of blocking and boundedness during the evolution of the system, hence its validation.

The increasing complexity of industrial systems and the increasingly severe operating constraints have forced specialists to design, specify and operate modern industrial processes. These evolutions thus imply the development of "intelligent" supervisory and prognostic systems, for the improvement of the control of the processes and the realization of the maintenance actions. This article presents our contribution in the study and the development of an interface of supervision and failures prediction of the Carbomill (malt mill) of the Breweries of Cameroon. The methodological approach is based on the design of a graphical interface made under Vijeo and controlled by an PLC, programmed on Unity Pro XL and the use of an ANFIS neuro-fuzzy network as a prediction tool. The expected results lead at the end of the learning on the evaluation by an RMSE cost function of 0.2142.

This paper presents a functional and dysfunctional behavioral study of a telecommunication system, with the aim to evaluate the performance of its constituent units. It is question of taking advantage offered by artificial intelligence in order to evaluate by modeling and simulation in system reliability. The methodological approach consists in combining ANFIS neuro-fuzzy networks with hybrid stochastic automata. The Neuro-Fuzzy ANFIS networks provide a prediction for the passage from nominal mode to degraded mode, by controlling the occurrence of malfunctions at transient levels. This allows to anticipate the occurrence of events degrading system performance, such as failures and disturbances. The objective is to maintain the system in nominal operating mode and prevent its tipping in degraded mode. The results are implanted around a demonstrator based on Scilab, and implemented on Matlab / Simulink.

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