Wireless industrial monitoring and control networks: the journey so far and the road ahead

While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks

Machine Learning Aided Methods for Resilient Industrial Wireless Sensor Network

Le Wireless Sensor Network (WSN) possono essere definite come un’ infrastruttura composta da sensori/dispositivi in grado di calcolare comunicare e effettuare sensing sul ambiente che gli circonda processando e analizzando i dati in modo da reagire a eventi e fenomeni che possono occorrere durante la comunicazione. Questo motiva un enorme effort nella ricerca, standardizzazione e investimento industriale in questo campo, nell’ultimo decennio. L’uso delle WSN nell’ambiente industriale è soggetto a diverse problematiche, dovuto all’ostilità dell’ambiente, come rumore, shadwoing, multi-percorso e interferenze. Nel nostro progetto, proponiamo un meccanismo basato sulle condizioni di propagazione del canale e algoritmi di machine learning che ci permettono di classificare lo stato del canale (LOS o NLOS) e migliorare qualità, sicurezza e in particolar modo l’affidabilità del sistema radio link da noi esaminato in differenti ambienti

A Survey on Communication Networks for Electric System Automation

Published in Computer Networks 50 (2006) 877–897, an Elsevier journal. The definitive version of this publication is available from Science Direct. Digital Object Identifier:10.1016/j.comnet.2006.01.005In today’s competitive electric utility marketplace, reliable and real-time information become the key factor for reliable delivery of power to the end-users, profitability of the electric utility and customer satisfaction. The operational and commercial demands of electric utilities require a high-performance data communication network that supports both existing functionalities and future operational requirements. In this respect, since such a communication network constitutes the core of the electric system automation applications, the design of a cost-effective and reliable network architecture is crucial. In this paper, the opportunities and challenges of a hybrid network architecture are discussed for electric system automation. More specifically, Internet based Virtual Private Networks, power line communications, satellite communications and wireless communications (wireless sensor networks, WiMAX and wireless mesh networks) are described in detail. The motivation of this paper is to provide a better understanding of the hybrid network architecture that can provide heterogeneous electric system automation application requirements. In this regard, our aim is to present a structured framework for electric utilities who plan to utilize new communication technologies for automation and hence, to make the decision making process more effective and direct.This work was supported by NEETRAC under Project #04-157

Applications of Soft Computing in Mobile and Wireless Communications

Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications

A Low Energy FPGA Platform for Real-Time Event-Based Control

We present a wireless sensor node suitable for event-based real-time control networks. The node achieves low-power operation thanks to tight clock synchronisation with the network master (at present we refer to a star network but extensions are envisaged). Also, the node does not employ any programmable device but rather an FPGA, thus being inherently immune to attacks based on code tampering. Experimental results on a simple laboratory apparatus are presented