1,198 research outputs found

    Joint transceiver design and power optimization for wireless sensor networks in underground mines

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    Avec les grands développements des technologies de communication sans fil, les réseaux de capteurs sans fil (WSN) ont attiré beaucoup d’attention dans le monde entier au cours de la dernière décennie. Les réseaux de capteurs sans fil sont maintenant utilisés pour a surveillance sanitaire, la gestion des catastrophes, la défense, les télécommunications, etc. De tels réseaux sont utilisés dans de nombreuses applications industrielles et commerciales comme la surveillance des processus industriels et de l’environnement, etc. Un réseau WSN est une collection de transducteurs spécialisés connus sous le nom de noeuds de capteurs avec une liaison de communication distribuée de manière aléatoire dans tous les emplacements pour surveiller les paramètres. Chaque noeud de capteur est équipé d’un transducteur, d’un processeur de signal, d’une unité d’alimentation et d’un émetteur-récepteur. Les WSN sont maintenant largement utilisés dans l’industrie minière souterraine pour surveiller certains paramètres environnementaux, comme la quantité de gaz, d’eau, la température, l’humidité, le niveau d’oxygène, de poussière, etc. Dans le cas de la surveillance de l’environnement, un WSN peut être remplacé de manière équivalente par un réseau à relais à entrées et sorties multiples (MIMO). Les réseaux de relais multisauts ont attiré un intérêt de recherche important ces derniers temps grâce à leur capacité à augmenter la portée de la couverture. La liaison de communication réseau d’une source vers une destination est mise en oeuvre en utilisant un schéma d’amplification/transmission (AF) ou de décodage/transfert (DF). Le relais AF reçoit des informations du relais précédent et amplifie simplement le signal reçu, puis il le transmet au relais suivant. D’autre part, le relais DF décode d’abord le signal reçu, puis il le transmet au relais suivant au deuxième étage s’il peut parfaitement décoder le signal entrant. En raison de la simplicité analytique, dans cette thèse, nous considérons le schéma de relais AF et les résultats de ce travail peuvent également être développés pour le relais DF. La conception d’un émetteur/récepteur pour le relais MIMO multisauts est très difficile. Car à l’étape de relais L, il y a 2L canaux possibles. Donc, pour un réseau à grande échelle, il n’est pas économique d’envoyer un signal par tous les liens possibles. Au lieu de cela, nous pouvons trouver le meilleur chemin de la source à la destination qui donne le rapport signal sur bruit (SNR) de bout en bout le plus élevé. Nous pouvons minimiser la fonction objectif d’erreur quadratique moyenne (MSE) ou de taux d’erreur binaire (BER) en envoyant le signal utilisant le chemin sélectionné. L’ensemble de relais dans le chemin reste actif et le reste des relais s’éteint, ce qui permet d’économiser de l’énergie afin d’améliorer la durée de vie du réseau. Le meilleur chemin de transmission de signal a été étudié dans la littérature pour un relais MIMO à deux bonds mais est plus complexe pour un ...With the great developments in wireless communication technologies, Wireless Sensor Networks (WSNs) have gained attention worldwide in the past decade and are now being used in health monitoring, disaster management, defense, telecommunications, etc. Such networks are used in many industrial and consumer applications such as industrial process and environment monitoring, among others. A WSN network is a collection of specialized transducers known as sensor nodes with a communication link distributed randomly in any locations to monitor environmental parameters such as water level, and temperature. Each sensor node is equipped with a transducer, a signal processor, a power unit, and a transceiver. WSNs are now being widely used in the underground mining industry to monitor environmental parameters, including the amount of gas, water, temperature, humidity, oxygen level, dust, etc. The WSN for environment monitoring can be equivalently replaced by a multiple-input multiple-output (MIMO) relay network. Multi-hop relay networks have attracted significant research interest in recent years for their capability in increasing the coverage range. The network communication link from a source to a destination is implemented using the amplify-and-forward (AF) or decode-and-forward (DF) schemes. The AF relay receives information from the previous relay and simply amplifies the received signal and then forwards it to the next relay. On the other hand, the DF relay first decodes the received signal and then forwards it to the next relay in the second stage if it can perfectly decode the incoming signal. For analytical simplicity, in this thesis, we consider the AF relaying scheme and the results of this work can also be developed for the DF relay. The transceiver design for multi-hop MIMO relay is very challenging. This is because at the L-th relay stage, there are 2L possible channels. So, for a large scale network, it is not economical to send the signal through all possible links. Instead, we can find the best path from source-to-destination that gives the highest end-to-end signal-to-noise ratio (SNR). We can minimize the mean square error (MSE) or bit error rate (BER) objective function by sending the signal using the selected path. The set of relay in the path remains active and the rest of the relays are turned off which can save power to enhance network life-time. The best path signal transmission has been carried out in the literature for 2-hop MIMO relay and for multiple relaying it becomes very complex. In the first part of this thesis, we propose an optimal best path finding algorithm at perfect channel state information (CSI). We consider a parallel multi-hop multiple-input multiple-output (MIMO) AF relay system where a linear minimum mean-squared error (MMSE) receiver is used at the destination. We simplify the parallel network into equivalent series multi-hop MIMO relay link using best relaying, where the best relay ..

    Real Time Gas Monitoring System Using Wireless Sensor Network

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    Miner’s safety is the main issue in the present era. Miner’s health is affected by many means which includes unstable and cumbersome underground activities and awkward loads, heavy tools and equipment, exposure to toxic dust and chemicals, gas or dust explosions, improper use of explosives, gas intoxications, collapsing of mine structures, electrical burn, fires, flooding, rock falls from roofs and side walls workers stumbling/slipping/falling, or errors from malfunctioning or improperly used mining equipment. In earlier days for detection of gases canary and small animals are used but they didn’t provide the exact condition of the mines so safety in the mine in not guaranteed. Hence, there is a need of monitoring system which utilised the ZigBee wireless sensor network technology. There are two units of the monitoring system Sensor unit and Monitoring unit. Sensor unit will be placed in the underground section and Monitoring unit will be placed in the above the mines from where monitoring is done. Firstly, the Sensor unit is placed in the underground section of the mine. Where input is taken from the sensors in terms of Methane (CH4) i.e. MQ-2 sensor, Hydrogen Sulphide (H2S) i.e. MQ-136 sensor, and Natural Gases i.e. MQ-5 sensor. Then they are compared with their threshold value by the Microcontroller Module and if the value is above the threshold value, the Buzzer starts ringing meanwhile data is displayed in the Display module and sent to the Wireless Communication Module of the Monitor unit i.e. ends device or coordinator through the Wireless Communication Module of the Sensor unit i.e. router. In this way, the study can help the miners get relief from any casualty and ultimately save their lives. The device encompasses a large range of networking. The data can also be stored for future investigation. The device is also durable and costs effective with a price of approx. Rs. 6,500 to 7,000/-

    A routing protocol for multisink wireless sensor networks in underground coalmine tunnels

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    Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use of wireless sensor networks (WSNs) has been proposed. However, the shape of coalmine tunnels is not conducive to the deployment of WSNs as they are long and narrow. Therefore, issues with the network arise, such as extremely large energy consumption, very weak connectivity, long time delays, and a short lifetime. To solve these problems, in this study, a new routing protocol algorithm for multisink WSNs based on transmission power control is proposed. First, a transmission power control algorithm is used to negotiate the optimal communication radius and transmission power of each sink. Second, the non-uniform clustering idea is adopted to optimize the cluster head selection. Simulation results are subsequently compared to the Centroid of the Nodes in a Partition (CNP) strategy and show that the new algorithm delivers a good performance: Power efficiency is increased by approximately 70%, connectivity is increased by approximately 15%, the cluster interference is diminished by approximately 50%, the network lifetime is increased by approximately 6%, and the delay is reduced with an increase in the number of sinks

    Feature Selection and Energy Management in Wireless Sensor Networks using Deep Learning

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    In wireless sensor networks, when the available energy sources and battery capacity are extremely constrained, energy efficiency is a major issue to be adressed. One of the main goals in the design of wireless sensor networks (WSNs) is to maximize longevity of battery life. Designers can benefit from the use of intelligent power utilization models to accomplish this goal. These models seek to decrease the number of chosen sensors used to record environmental measures in order to minimize power utilization while retaining the acceptable level of measurement accuracy. In order to simulate wireless sensor networks, we looked at real world datasets. Our simulation findings demonstrate that the suggested strategy can be used to accomplish significant goals by using the right number of sensors using deep learning, extend the lifespan of the wireless sensor networks

    Low-cost sensors technologies for monitoring sustainability and safety issues in mining activities: advances, gaps, and future directions in the digitalization for smart mining

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    Nowadays, monitoring aspects related to sustainability and safety in mining activities worldwide are a priority, to mitigate socio-environmental impacts, promote efficient use of water, reduce carbon footprint, use renewable energies, reduce mine waste, and minimize the risks of accidents and fatalities. In this context, the implementation of sensor technologies is an attractive alternative for the mining industry in the current digitalization context. To have a digital mine, sensors are essential and form the basis of Industry 4.0, and to allow a more accelerated, reliable, and massive digital transformation, low-cost sensor technology solutions may help to achieve these goals. This article focuses on studying the state of the art of implementing low-cost sensor technologies to monitor sustainability and safety aspects in mining activities, through the review of scientific literature. The methodology applied in this article was carried out by means of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and generating science mapping. For this, a methodological procedure of three steps was implemented: (i) Bibliometric analysis as a quantitative method, (ii) Systematic review of literature as a qualitative method, and (iii) Mixed review as a method to integrate the findings found in (i) and (ii). Finally, according to the results obtained, the main advances, gaps, and future directions in the implementation of low-cost sensor technologies for use in smart mining are exposed. Digital transformation aspects for data measurement with low-cost sensors by real-time monitoring, use of wireless network systems, artificial intelligence, machine learning, digital twins, and the Internet of Things, among other technologies of the Industry 4.0 era are discussed.The authors are indebted to the projects PID2021-126405OB-C31 and PID2021-126405OB-C32 funded by FEDER funds—A Way to Make Europe and Spanish Ministry of Economy and Competitiveness MICIN/AEI/10.13039/501100011033/. The financial support of the Research Department of the Catholic University of Temuco and the Civil Engineering Department of the University of Castilla-La Mancha is also appreciated.Peer ReviewedPostprint (published version

    A Wireless Sensor Network Based Personnel Positioning Scheme in Coal Mines with Blind Areas

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    This paper proposes a novel personnel positioning scheme for a tunnel network with blind areas, which compared with most existing schemes offers both low-cost and high-precision. Based on the data models of tunnel networks, measurement networks and mobile miners, the global positioning method is divided into four steps: (1) calculate the real time personnel location in local areas using a location engine, and send it to the upper computer through the gateway; (2) correct any localization errors resulting from the underground tunnel environmental interference; (3) determine the global three-dimensional position by coordinate transformation; (4) estimate the personnel locations in the blind areas. A prototype system constructed to verify the positioning performance shows that the proposed positioning system has good reliability, scalability, and positioning performance. In particular, the static localization error of the positioning system is less than 2.4 m in the underground tunnel environment and the moving estimation error is below 4.5 m in the corridor environment. The system was operated continuously over three months without any failures

    Environmental Pollution and Chronic Disease Management – A Prognostics Approach

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