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

Rule Managed Reporting in Energy Controlled Wireless Sensor Networks

This paper proposes a technique to extend the network lifetime of a wireless sensor network, whereby each sensor node decides its network involvement, based on energy resources and the information in each message (ascertained through a system of rules). Results obtained from the simulation of an industrial monitoring scenario have shown that a considerable increase in the lifetime and connectivity can be obtained

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book

Model-driven optimisation of monitoring system configurations for batch production

The increasing need to monitor asset health and the deployment of IoT devices have driven the adoption of non-desctructive testing methods in the industry sector. In fact, they constitute a key to production efficiency. However, engineers still struggle to meet requirements sufficiently due to the complexity and cross-dependency of system parameters. In addition, the design and configuration of industrial monitoring systems remains dependent on recurring issues: data collection, algorithm selection, model configuration and objective function modelling. In this paper, we shine a light on impact factors of machine vision and signal processing in industrial monitoring, from sensor configuration to model development. Since system design requires a deep understanding of the physical characteristics, we apply graph-based design languages to improve the decision and configuration process. Our model and architecture design method are adapted for processing image and signal data in highly sen sitive installations to increase transparency, shorten time-to-production and enable defect monitoring in environments with varying conditions. We explore the potential of model selection, pipeline generation and data quality assessment and discuss their impact on representative manufacturing processes

SMILE: Smart Monitoring IoT Learning Ecosystem

In industrial contexts to date, there are several solutions to monitor and intervene in case of anomalies and/or failures. Using a classic approach to cover all the requirements needed in the industrial field, different solutions should be implemented for different monitoring platforms, covering the required end-to-end. The classic cause-effect association process in the field of industrial monitoring requires thorough understanding of the monitored ecosystem and the main characteristics triggering the detected anomalies. In these cases, complex decision-making systems are in place often providing poor results. This paper introduces a new approach based on an innovative industrial monitoring platform, which has been denominated SMILE. It allows offering an automatic service of global modern industry performance monitoring, giving the possibility to create, by setting goals, its own machine/deep learning models through a web dashboard from which one can view the collected data and the produced results.  Thanks to an unsupervised approach the SMILE platform can understand which the linear and non-linear correlations are representing the overall state of the system to predict and, therefore, report abnormal behavior

Implementation of Micro-Controller Based Adaptive Motion Detection for Industrial Monitoring System

Industrial system has become concurrent research focus in most developed counties being an ultimate source of revenue benefited by citizens. This project emphasized on implementation of micro-controller based adaptive motion detection for industrial monitoring system as a factor that determines synergy and sustainability of industrial management. The camera will be interface with PC to detect the presence of object and report production activities through image capture and enable video stream for monitoring. The design is to create interface link between Microcontroller AVR PC, ATMEG16 and camera C3088. The PC will establish bi-directional communication with AVR while using I2C communication protocol is used to interface camera and AVR.  The industrial feedback process will be control with AVR based on adaptive motion detection from installed camera. The captured image obtain from the camera can be use for surveillance or can be process for image processing purpose in industries and organizations. Keywords: Lighting, LED, economic usage, light energy, detectio

Design and implementation of wireless sensor network with LoRa technology for industrial monitoring

El creciente desarrollo del Internet de las Cosas (IoT, Internet of Things) ha diversificado sus campos de aplicación, mejorando no solo la interconexión de personas, sino también, la comunicación entre maquinaria industrial (M2M, Machine-to-Machine), en las que sus características en alcance, escalabilidad y bajo costo de despliegue, pueden ser aprovechadas. Las tecnologías LoRa y LoRaWAN se muestran como una de las principales opciones de comunicación inalámbrica de bajo costo en la integración de sistemas industriales con mira a los nuevos requerimientos de la Industria 4.0. En este trabajo se realizó una campaña de mediciones y el análisis de los datos obtenidos, para evaluar el comportamiento y la aplicabilidad de las tecnologías LoRa y LoRaWAN dentro de ambientes industriales. Para contrastar los resultados, se realizaron pruebas en ambientes urbanos despejados, donde se observó que las condiciones dentro de las naves industriales, permiten establecer un enlace con condiciones de radio frecuencia favorables. Inicialmente se han considerado escenarios de corto alcance (<100 m) en los que se mantiene una línea de vista entre el transmisor y el receptor.The growing development of the Internet of Things (IoT) has diversified its fields of application, improving not only the interconnection of people but as well the communication between industrial machinery (M2M, Machine-to-Machine), in which its features in range, scalability, and low cost of deployment can be taken advantage of. LoRa and LoRaWAN technologies are presented as one of the main low-cost wireless communication options in the integration of industrial systems with a view to the new requirements of Industry 4.0. In this work, a measurement campaign and the analysis of the data obtained were performed to evaluate the behavior and applicability of LoRa and LoRaWAN technologies within industrial environments. To contrast the results, tests were performed in clear urban environments, where it was observed that the conditions inside the industrial buildings allow the establishment of a link with favorable radio frequency conditions. Initially, short-range scenarios (<100 m) have been considered in which a line of sight is maintained between the transmitter and the receiver

Development of RFID Based Smart Sensor Prototype for Wireless Industrial Monitoring and Control

The Purpose of this paper is to present one of the various wireless technologies currently available for industrial monitoring and control. Applications of wireless data transmission are universal. In industrial automation, the benefits of adopting wireless technologies in eliminating the needs for cables in hard to reach areas within the plant, increasing data availability and quality and monitoring and controlling remote assets, that otherwise were inaccessible. Radio frequency identification (RFID) technology is commonly used for object or animal identification and tracking. This article explores the feasibility of its use in a rapid solution to wireless real time monitoring of industry. A prototype system for wireless industrial monitoring and control was developed using a commercially available 12.5 GHZ RFID passive tags. Various parameters are sensed by respective sensors (Slaves), which are then monitored by low power, high performance, 8bit AVR microcontroller. Monitored signals are then sent to the RFID tag or transponder unit, hence the smart feature of the sensor. A receiving unit (Interrogator) emits an electromagnetic field which when detected by passive RFID tag causes it to transfer sensor information (data stored in memory) to the interrogator. Interrogator detects these parameters and sends them to the data collection PC (Master Unit). The architecture of the developed wireless sensor prototype allows for additional RFID tags (Slave Units) to be integrated into it without changes to the sensor designs. Design also provides means to update operating and monitoring parameters as well as sensors/RF link specific firmware modules ‘over - the - air’

On the Use of LoRaWAN for Indoor Industrial IoT Applications

Low-Power Wide-Area Networks (LPWANs) have recently emerged as appealing communication systems in the context of the Internet of Things (IoT). Particularly, they proved effective in typical IoT applications such as environmental monitoring and smart metering. Such networks, however, have a great potential also in the industrial scenario and, hence, in the context of the Industrial Internet of Things (IIoT), which represents a dramatically growing field of application. In this paper we focus on a specific LPWAN, namely, LoRaWAN, and provide an assessment of its performance for typical IIoT employments such as those represented by indoor industrial monitoring applications. In detail, after a general description of LoRaWAN, we discuss how to set some of its parameters in order to achieve the best performance in the considered industrial scenario. Subsequently we present the outcomes of a performance assessment, based on realistic simulations, aimed at evaluating the behavior of LoRaWAN for industrial monitoring applications. Moreover, the paper proposes a comparison with the IEEE 802.15.4 network protocol, which is often adopted in similar application contexts. The obtained results confirm that LoRaWAN can be considered as a strongly viable opportunity, since it is able to provide high reliability and timeliness, while ensuring very low energy consumption