Monitoring a large construction site using wireless sensor networks

Despite the significant advances made by wireless sensor network research, deployments of such networks in real application environments are fraught with significant difficulties and challenges that include robust topology design, network diagnostics and maintenance. Based on our experience of a six-month-long wireless sensor network deployment in a large construction site, we highlight these challenges and argue the need for new tools and enhancements to current protocols to address these challenges.This research has been funded by the EPSRC Innovation and Knowledge Centre for Smart Infrastructure and Construction project (EP/K000314/1). We would like to thank Costain-Skanska Joint Venture (CSJV) and our industrial partner Crossrail for allowing access and instrumentation of the Paddington site. We would also like to thank Dr Munenori Shibata from Japan Railway Technical Research Institute for his assistance with network deployment.This is the author accepted manuscript. The final version is available from ACM via http://dx.doi.org/10.1145/2820990.2820997 Data supporting this paper is available from https://www.repository.cam.ac.uk/handle/1810/250538

Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings

PERANCANGAN DAN IMPLEMENTASI WIRELESS SENSOR NETWORK (WSN) UNTUK MONITORING GETARAN REL KERETA API BERBASIS ACCELEROMETER 3 SUMBU MENGGUNAKAN PROTOKOL ZIGBEE (IEEE 802.15.4)

ABSTRAKSI: Setelah dilakukan pengujian dan implementasi didapat beberapa hasil kesimpulan diantaranya: website SMP Negeri 1 Klaten ini dapat membantu sekolah dalam penyampaian informasi secara online, sehingga masyarakat dapat mengetahui seluk beluk SMP Negeri 1 Klaten, dan orangtua siswa dapat mengetahui detail nilai dari siswa yang bersangkutan. Selain itu diperoleh MOS dari website sebesar 4.16 oleh guru dan 4.39 oleh siswa, dari nilai tersebut tergolong baik. Sedangkan berdasarkan hasil pengujian kemampuan web server diperoleh bahwa website ini mampu melayani 50 pengguna dengan baik tanpa terjadi error.Dalam Tugas Akhir ini, dilakukan perancangan dan implementasi perangkat keras sistem monitoring getaran rel kereta api menggunakan sensor accelerometer ADXL345 dan modul Zigbee yang memiliki kemampuan mengirimkan data dengan jaringan wireless sensor network. Hasil dari transfer data tersebut diharapkan dapat mengetahui secara langsung kualitas rel kereta api. Parameter yang dikaji adalah akselerasi getaran, Bit Error Rate (BER), dan Receive Signal Level (RSL).Hasil dari pengujian sistem pemantauan getaran rel kereta api yang telah dilakukan, menunjukkan bahwa kualitas rel kereta api tersebut berada dalam kondisi baik. Jarak maksimal modul Zigbee mampu mengirimkan data sebesar 100 meter dengan jarak antar modul Zigbee sebesar 50 meter dengan nilai BER maksimum sebesar 2,8×10-4 dan nilai RSL yang terukur sebesar -96,59 dBm.Kata Kunci : wireless sensor network, zigbee, monitoring, ADXL345, BER, RSLABSTRACT: The case of a train accidents that occurred in Indonesia were caused by several factors, one of them was poor rail conditions. The condition of the railway problem is an issue that needs special attention from PT. KAI (KERETA API INDONESIA) as the train transport company in Indonesia. One effort to overcome these problems by monitoring the vibrations that occurs on the rail needs is done continuously to determine the quality of rail based on standard used by PT KAI to minimize train accidents. ZigBee is technology focused on the data communication which has characteristics such as low data rate, low cost, and small power consumption. One of function of ZigBee technology is the monitoring system. This monitoring system can be applied to monitor rail vibration.In this final project, design and implementation of hardware vibration monitoring system are using the railroad ADXL345 accelerometer sensor and Zigbee modules that have the ability to transmit data over a wireless network sensor network, Results of the data transfer is expected to find out the quality of the railway. The parameters studied are the vibration acceleration, Bit Error Rate (BER), and Receive Signal Level (RSL).The result of railway vibration monitoring system testing railway that had been done, showed the quality of the train tracks are in good condition. Maximum distance Zigbee module can transmit data at 100 meter spaced at 50 meter Zigbee module with a maximum BER value of 2,8×10-4 and the measured values of RSL -96.59 dBm.Keyword: wireless sensor networks, zigbee, monitoring, ADXL345, BER, RS

Rock falls impacting railway tracks. Detection analysis through an artificial intelligence camera prototype

During the last few years, several approaches have been proposed to improve early warning systems for managing geological risk due to landslides, where important infrastructures (such as railways, highways, pipelines, and aqueducts) are exposed elements. In this regard, an Artificial intelligence Camera Prototype (AiCP) for real-time monitoring has been integrated in a multisensor monitoring system devoted to rock fall detection. An abandoned limestone quarry was chosen at Acuto (central Italy) as test-site for verifying the reliability of the integratedmonitoring system. A portion of jointed rockmass, with dimensions suitable for optical monitoring, was instrumented by extensometers. One meter of railway track was used as a target for fallen blocks and a weather station was installed nearby. Main goals of the test were (i) evaluating the reliability of the AiCP and (ii) detecting rock blocks that reach the railway track by the AiCP. At this aim, several experiments were carried out by throwing rock blocks over the railway track. During these experiments, the AiCP detected the blocks and automatically transmitted an alarm signal

Integrated process of images and acceleration measurements for damage detection

The use of mobile robots and UAV to catch unthinkable images together with on-site global automated acceleration measurements easy achievable by wireless sensors, able of remote data transfer, have strongly enhanced the capability of defect and damage evaluation in bridges. A sequential procedure is, here, proposed for damage monitoring and bridge condition assessment based on both: digital image processing for survey and defect evaluation and structural identification based on acceleration measurements. A steel bridge has been simultaneously inspected by UAV to acquire images using visible light, or infrared radiation, and monitored through a wireless sensor network (WSN) measuring structural vibrations. First, image processing has been used to construct a geometrical model and to quantify corrosion extension. Then, the consistent structural model has been updated based on the modal quantities identified using the acceleration measurements acquired by the deployed WSN. © 2017 The Authors. Published by Elsevier Ltd

Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft

Data fusion strategy for precise vehicle location for intelligent self-aware maintenance systems

Abstract— Nowadays careful measurement applications are handed over to Wired and Wireless Sensor Network. Taking the scenario of train location as an example, this would lead to an increase in uncertainty about position related to sensors with long acquisition times like Balises, RFID and Transponders along the track. We take into account the data without any synchronization protocols, for increase the accuracy and reduce the uncertainty after the data fusion algorithms. The case studies, we have analysed, derived from the needs of the project partners: train localization, head of an auger in the drilling sector localization and the location of containers of radioactive material waste in a reprocessing nuclear plant. They have the necessity to plan the maintenance operations of their infrastructure basing through architecture that taking input from the sensors, which are localization and diagnosis, maps and cost, to optimize the cost effectiveness and reduce the time of operation

More is less: Connectivity in fractal regions

Ad-hoc networks are often deployed in regions with complicated boundaries. We show that if the boundary is modeled as a fractal, a network requiring line of sight connections has the counterintuitive property that increasing the number of nodes decreases the full connection probability. We characterise this decay as a stretched exponential involving the fractal dimension of the boundary, and discuss mitigation strategies. Applications of this study include the analysis and design of sensor networks operating in rugged terrain (e.g. railway cuttings), mm-wave networks in industrial settings and vehicle-to-vehicle/vehicle-to-infrastructure networks in urban environments.Comment: 5 page