Academic literature on the topic 'Automatic data collecting systems'

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Journal articles on the topic "Automatic data collecting systems"

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Palmieri Lage, Juliano, Altigran S. da Silva, Paulo B. Golgher, and Alberto H. F. Laender. "Automatic generation of agents for collecting hidden Web pages for data extraction." Data & Knowledge Engineering 49, no. 2 (May 2004): 177–96. http://dx.doi.org/10.1016/j.datak.2003.10.003.

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Byrd Christoph, Orinda, Scott P. Stevens, and Richard T. Christoph. "Automatic Data Collection Systems: Observed Benefits and Problems." International Journal of Operations & Production Management 12, no. 5 (May 1992): 57–68. http://dx.doi.org/10.1108/01443579210011417.

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Serov, Dmitry. "Information technologies implementation for reducing water losses in water supply systems." E3S Web of Conferences 164 (2020): 01005. http://dx.doi.org/10.1051/e3sconf/202016401005.

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The article discusses the elements of an automated system for collecting, storing and transmitting data on water consumption, modern metering devices, data collection and transmission devices. The author analyzes the shortcomings of existing accounting and analysis automation systems at Russian water utilities. A comprehensive approach to automated systems in the field of water consumption accounting is proposed. The article considers the experience of the State unitary enterprise “Vodokanal of Saint Petersburg” in the sphere development and application of a single automated complex for diagnostics, monitoring and management of the water supply network. The goals and main functions of the complex are revealed, the main stages and results of its implementation are presented.
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Truong, Do Quoc, Pham Ngoc Phuong, Tran Hoang Tung, and Luong Chi Mai. "DEVELOPMENT OF HIGH-PERFORMANCE AND LARGE-SCALE VIETNAMESE AUTOMATIC SPEECH RECOGNITION SYSTEMS." Journal of Computer Science and Cybernetics 34, no. 4 (January 30, 2019): 335–48. http://dx.doi.org/10.15625/1813-9663/34/4/13165.

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Automatic Speech Recognition (ASR) systems convert human speech into the corresponding transcription automatically. They have a wide range of applications such as controlling robots, call center analytics, voice chatbot. Recent studies on ASR for English have achieved the performance that surpasses human ability. The systems were trained on a large amount of training data and performed well under many environments. With regards to Vietnamese, there have been many studies on improving the performance of existing ASR systems, however, many of them are conducted on a small-scaled data, which does not reflect realistic scenarios. Although the corpora used to train the system were carefully design to maintain phonetic balance properties, efforts in collecting them at a large-scale are still limited. Specifically, only a certain accent of Vietnam was evaluated in existing works. In this paper, we first describe our efforts in collecting a large data set that covers all 3 major accents of Vietnam located in the Northern, Center, and Southern regions. Then, we detail our ASR system development procedure utilizing the collected data set and evaluating different model architectures to find the best structure for Vietnamese. In the VLSP 2018 challenge, our system achieved the best performance with 6.5% WER and on our internal test set with more than 10 hours of speech collected real environments, the system also performs well with 11% WER
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Hodosh, M., P. Young, and J. Hockenmaier. "Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics." Journal of Artificial Intelligence Research 47 (August 30, 2013): 853–99. http://dx.doi.org/10.1613/jair.3994.

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The ability to associate images with natural language sentences that describe what is depicted in them is a hallmark of image understanding, and a prerequisite for applications such as sentence-based image search. In analogy to image search, we propose to frame sentence-based image annotation as the task of ranking a given pool of captions. We introduce a new benchmark collection for sentence-based image description and search, consisting of 8,000 images that are each paired with five different captions which provide clear descriptions of the salient entities and events. We introduce a number of systems that perform quite well on this task, even though they are only based on features that can be obtained with minimal supervision. Our results clearly indicate the importance of training on multiple captions per image, and of capturing syntactic (word order-based) and semantic features of these captions. We also perform an in-depth comparison of human and automatic evaluation metrics for this task, and propose strategies for collecting human judgments cheaply and on a very large scale, allowing us to augment our collection with additional relevance judgments of which captions describe which image. Our analysis shows that metrics that consider the ranked list of results for each query image or sentence are significantly more robust than metrics that are based on a single response per query. Moreover, our study suggests that the evaluation of ranking-based image description systems may be fully automated.
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Shang, Chun Min, Dong Mei Zhang, and Xin Ming Zhang. "Subsurface Safety Valve Automation Test Systems Design." Applied Mechanics and Materials 543-547 (March 2014): 1188–91. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1188.

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To the subsurface safety valve testing, an intelligent automatic test system is designed based on the control computer and programmable logic controller. Based on modular concept, the entire system is mainly composed of mechanical components and computer control system. The working principle is analyzed for the subsurface safety valve test. The control system based on the Labview and PLC can accomplish hydraulic and gas testing with functions of the testing process control, data collection and analysis, automatic generating test report, friendly interface and high degree automation. Experiments prove that the test system can achieve expected effect and satisfy the test requirement, and the procedure is simple and convenient. The system has great significance to improve the subsurface safety valve test accuracy, efficiency and automation level.
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Vuong, Quan-Hoang, Viet-Phuong La, Thanh-Huyen T. Nguyen, Minh-Hoang Nguyen, Tam-Tri Le, and Manh-Toan Ho. "An AI-Enabled Approach in Analyzing Media Data: An Example from Data on COVID-19 News Coverage in Vietnam." Data 6, no. 7 (June 25, 2021): 70. http://dx.doi.org/10.3390/data6070070.

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This method article presents the nuts and bolts of an AI-enabled approach to extracting and analyzing social media data. The method is based on our previous rapidly cited COVID-19 research publication, working on a dataset of more than 14,000 news articles from Vietnamese newspapers, to provide a comprehensive picture of how Vietnam has been responding to this unprecedented pandemic. This same method is behind our IUCN-supported research regarding the social aspects of environmental protection missions, now appearing in print in Wiley’s Corporate Social Responsibility and Environmental Management. Homemade AI-enabled software was the backbone of the study. The software has provided a fast and automatic approach in collecting and analyzing social data. Moreover, the tool also allows manually sorting the data, AI-generated word tokenizing in the Vietnamese language, and powerful visualization. The method hopes to provide an effective but low-cost method for social scientists to gather a massive amount of data and analyze them in a short amount of time.
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Tanaka, Mikio. "Data Re-allocation Method for Automatic Toll Collection Systems for Transportation Services." IEEJ Transactions on Industry Applications 117, no. 9 (1997): 1106–14. http://dx.doi.org/10.1541/ieejias.117.1106.

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BABA, Seiki, and Nobuhiro MIZUNO. "Automatic Data Collection and Remote-Measurement Systems at SPring-8 MX Beamlines." Nihon Kessho Gakkaishi 63, no. 3 (August 31, 2021): 216–18. http://dx.doi.org/10.5940/jcrsj.63.216.

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Grisé, Emily, and Ahmed El-Geneidy. "Identifying the Bias: Evaluating Effectiveness of Automatic Data Collection Methods in Estimating Details of Bus Dwell Time." Transportation Research Record: Journal of the Transportation Research Board 2647, no. 1 (January 2017): 33–40. http://dx.doi.org/10.3141/2647-05.

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Data from automated vehicle location (AVL) systems, automatic passenger counter (APC) systems, and fare box payments have been heavily used to generate dwell time models with the goal of recommending improvements in efficiency and reliability of bus transit systems. However, automatic data collection methods may result in a loss of detail with regard to the dynamics of passenger activity, which may bias the estimates associated with dwell or passenger activity time. The purpose of this study is to understand better any biases that might exist from using data from AVL–APC systems or fare box payments when estimating dwell time. Manually collected data from Montreal, Quebec, Canada, are used to estimate detailed dwell time models. This study compared those estimates to models generated by using data similar to what was reported by AVL–APC systems and fare boxes. The results reveal an overestimation in the passenger activity component of dwell time, which is mainly attributed to excess dwell time that AVL–APC data and fare box payments generally do not capture. While AVL–APC and fare box technologies provide transit agencies with rich data for analysis, adjustments to such data collection methods are warranted to reduce the overestimation of dwell time and to provide a more accurate picture of what is happening on the ground to generate better interventions that can reduce dwell times.
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Dissertations / Theses on the topic "Automatic data collecting systems"

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Jan, Jonathan. "Collecting Data for Building Automation Analytics : A case study for collecting operational data with minimal human intervention." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233319.

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Approximately 40% of the total energy consumption within the EU is due to buildings, and similar numbers can be found in the US. If the principal inefficiencies in buildings were easily identifiable, then a facility manager could focus their resources to make the buildings more efficient, which would lead to both cost savings for the facility owners and decrease the building’s ecological footprint. In building automation systems today, data is already being collected every second, but due to the lack of standardization for describing this data, having access to data is not the same as being able to make use of it. The existing heterogeneity makes it very costly to gather data from multiple buildings, thus making it difficult to understand the big picture. Facility managers cannot fix what they cannot see; thus it is important to facilitate the visualization of the data collected from all of the different building automation systems. This potentially offers great benefits with regards to both sustainability and economy. In this thesis, the author’s goal is to propose a sustainable, cost and time effective data integration strategy for real estate owners who wish to gain greater insight into their buildings’ efficiency. The study begins with a literature study to find previous and on-going attempts to solve this problem. Some initiatives for standardization of semantic models were found. Two of these models, Brick and Haystack, were chosen. One building automation system (BAS) was tested in a pilot case study, to test the appropriateness of a solution. The key results from this thesis project show that data from building automation systems, can be integrated into an analysis platform, and an extract, transform, and load (ETL) process for this is presented. How time efficiently data can be tagged and transformed into a common format is very dependent upon the current control system’s data storage format and whether information about its structure is adequate. It is also noted that there is no guarantee that facility managers have access to the control system’s database or information about how that is structured, in such cases other techniques can be used such as BACnet/IP, or Open Platform Communications (OPC) Unified Architecture.
Ungefär 40 % av den totala energikonsumtionen i E.U. och U.S.A. förbrukas av fastigheter. Om de delar av fastigheten som är ineffektiva enkelt kunde identifieras, skulle det underlätta fastighetsförvaltarnas arbete i att göra byggnader mer energisnåla. Detta har i sin tur potential att minska kostnader och byggnaders ekologiska fotavtryck. I dagens fastighetsautomationssystem samlas data in varje sekund, men på grund av att det saknas ett standardiserat sätt att beskriva den på, är det skillnad på att ha tillgång till data och att faktiskt kunna använda sig av den. Heterogeniteten gör att det blir både kostsamt och tidskrävande för fastighetsförvaltare att samla in data från sina fastigheter. Fastighetsförvaltare kan inte åtgärda något det inte kan se. Därför är det viktigt att underlätta möjligheten för visualisering av data från olika typer av fastighetsautomationssystem. Att lyckas med detta har potential att ge positiva effekter både när det gäller hållbarhet och ekonomi. I den här uppsatsen är författarens mål att komma fram till en hållbar, kostnads- och tidseffektiv integrationsstrategi för fastighetsförvaltare som vill få bättre insikter hur effektiv deras byggnad faktiskt är. Forskningsarbetet inleds med en litteraturstudie för att finna tidigare och pågående försök att lösa detta problem. Några initiativ för standardisering av semantiska modeller för att beskriva data inom fastighetsautomation hittades. Två av dessa, Brick och Project Haystack, valdes ut. En byggnad, och ett fastighetsautomationssystem testades i en pilotstudie. Resultaten från studien pekar på att data från fastighetautomationssystem kan integreras med en analysplattform, och en så kallad ETL-process, efter de engelska orden: extract, transform, load; presenteras för att uppnå det målet. Hur tidseffektivt data kan taggas och transformeras beror på det nuvarande kontrollsystemets datalagringsformat och om information om dess struktur är adekvat. Det noteras att det inte finns någon garanti till att få åtkomst till kontrollsystemets databas, eller information om dess struktur, därför presenteras även alternativa tekniker, däribland BACnet/IP och Open Platform Communications (OPC) Unified Architecture.
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Librescu, Joseph. "Bar code data collection system implementation and laboratory exercise." Master's thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-10242009-020101/.

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Gurung, Sanjaya Acevedo Miguel Felipe. "Integrating environmental data acquisition and low cost Wi-Fi data communication." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/ark:/67531/metadc12131.

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Ward, Michael P. "An architectural framework for describing Supervisory Control and Data Acquisition (SCADA) systems." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Sep%5FWard.pdf.

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Thesis (M.S. in Computer Science)--Naval Postgraduate School, Sept. 2004.
Thesis Advisor(s): Cynthia E. Irvine, Deborah S. Shifflett. Includes bibliographical references (p. 73-75). Also available online.
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Feldman, Adam Michael. "Using observations to recognize the behavior of interacting multi-agent systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24771.

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Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2008.
Committee Chair: Balch, Tucker; Committee Member: Essa, Irfan; Committee Member: Isbell, Charles; Committee Member: Starner, Thad; Committee Member: Wallen, Kim.
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Natale, Robert J. Jr. "Further development of Delaware's first permanently instrumented bridge." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 126 p, 2008. http://proquest.umi.com/pqdweb?did=1619620021&sid=6&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Miller, Matthew Scott. "Development of a non-contact data acquisition system for robotic welding process monitoring." Thesis, Georgia Institute of Technology, 1999. http://hdl.handle.net/1853/16071.

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Yee, Tze-Sung. "A hardware based optical digital code scanning system." Ohio : Ohio University, 1988. http://www.ohiolink.edu/etd/view.cgi?ohiou1182536210.

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Zhou, Huafeng, and 周華鋒. "Design of grid service-based power system control centers for future electricity systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40687429.

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Zhou, Huafeng. "Design of grid service-based power system control centers for future electricity systems." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B40687429.

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Books on the topic "Automatic data collecting systems"

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Automatic identification and data collection systems. London: McGraw-Hill, 1994.

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American Society of Mechanical Engineers. Winter Meeting. Sensors for manufacturing: Presented at the Winter Annual Meeting of the American Society of Mechanical Engineers, Boston, Massachusetts, December 13-18, 1987. New York, N.Y. (345 E. 47th St., New York 10017): American Society of Mechanical Engineers, 1987.

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Tippie, J. W. High performance data acquisition and control. Lockport, Ill: KineticSystems Corporation, 1994.

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Steve, Mackay, and IDC Technologies (Firm), eds. Practical data acquisition for instrumentation and control systems. Oxford: Newnes, 2003.

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Data acquisition for sensor systems. London: Chapman & Hall, 1997.

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Adams, Russell E. Sourcebook of automatic identification and data collection. New York: Van Nostrand Reinhold, 1990.

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Adams, Russ. Sourcebook of automatic identification and data collection. New York: Van Nostrand Reinhold, 1990.

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Green, A. J. A synchronous data analyzer for the minimum delay data format (MDDF) and launch trajectory acquisition system (LTAS): Andrew J. Green. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Office, 1987.

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Soloman, Sabrie. Sensors and control systems in manufacturing. 2nd ed. New York: McGraw-Hill, 2010.

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Sensors and control systems in manufacturing. New York: McGraw Hill, 1994.

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Book chapters on the topic "Automatic data collecting systems"

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Sharma, Gajendra, Manish Kumar, and Shekhar Verma. "An Approach of Automatic Data Collection and Categorization." In Advances in Intelligent Systems and Computing, 527–36. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7868-2_51.

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El-Sakhawy, Dayna, Slim Abdennadher, and Injy Hamed. "Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose." In Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction, 99–108. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15557-9_10.

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Pereira, Ivo F., Tiago M. Sousa, Isabel Praca, Ana Freitas, Tiago Pinto, Zita Vale, and Hugo Morais. "Automatic Electricity Markets Data Extraction for Realistic Multi-agent Simulations." In Advances in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection, 371–74. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07551-8_41.

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Cornford, Tony, and Steve Smithson. "Collecting research data." In Project Research in Information Systems, 90–107. London: Macmillan Education UK, 1996. http://dx.doi.org/10.1007/978-1-349-13863-0_6.

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Cornford, Tony, and Steve Smithson. "Collecting research data." In Project Research in Information Systems, 113–26. London: Macmillan Education UK, 2006. http://dx.doi.org/10.1007/978-1-137-06918-4_7.

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Tannock, J. D. T. "Statistical process control software, data collection and computer-aided inspection." In Automating Quality Systems, 181–97. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2366-2_14.

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Homenda, Wladyslaw, and Witold Pedrycz. "Automatic Data Understanding." In Advances in Intelligent Systems and Computing, 217–28. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11313-5_21.

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Ziegler, Cai-Nicolas. "Fully-Automatic Web Data Extraction." In Encyclopedia of Database Systems, 1–4. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_1159-2.

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Ziegler, Cai-Nicolas. "Fully Automatic Web Data Extraction." In Encyclopedia of Database Systems, 1544–48. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_1159.

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Ziegler, Cai-Nicolas. "Fully-Automatic Web Data Extraction." In Encyclopedia of Database Systems, 1191–93. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_1159.

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Conference papers on the topic "Automatic data collecting systems"

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Rossetti, Manuel, Bradley Hobbs, and Paul Faas. "An Object-Oriented Framework for Simulating Automatic Data Collection Systems." In 2006 Winter Simulation Conference. IEEE, 2006. http://dx.doi.org/10.1109/wsc.2006.322925.

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Cinque, Marcello, Domenico Cotroneo, Carlos Rodriguez-Dominguez, and Jose Luis Garrido. "Automatic collection of failure data from the iOS platform." In 2013 43rd Annual IEEE/IFIP Conference on Dependable Systems and Networks Workshop (DSN-W). IEEE, 2013. http://dx.doi.org/10.1109/dsnw.2013.6615508.

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Praca, I., T. M. Sousa, A. Freitas, T. Pinto, Z. Vale, and M. Silva. "Adaptive Tool for Automatic Data Collection of Real Electricity Markets." In 2012 23rd International Workshop on Database and Expert Systems Applications (DEXA). IEEE, 2012. http://dx.doi.org/10.1109/dexa.2012.79.

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Clark, Ian M., and Glenn Shaw. "Pipeline Control: Merging SCADA and Gas Measurement." In 1998 2nd International Pipeline Conference. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/ipc1998-2106.

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This paper discusses the merits of merging SCADA1 and gas measurement from a technical and economical perspective. Because traditional SCADA is largely limited to control room data used only for day to day operational purposes, the real-time metering data is not often utilized in the external revenue-generation business systems of the organization. In many cases, entirely separate measurement systems are utilized in isolation which often have few, if any, ties to the SCADA system which is capable of collecting pertinent measurement information. Measurement data validation provides automatic data validation of flow measurement data upon retrieval from telemetered or non-telemetered data sources. Row measurement data can be supplied from field devices such as electronic flow computers or from other sources of flow measurement data such as manual operator entry, third party collection systems, chart integration sources, etc. Flow measurement data undergoes a series of automated validation tests including single-run limit checking, meter run comparisons (at a given metering station) and historical validation tests (such as searching for frozen values). The outcome of these tests determines the data quality code assigned to each flow measurement reading (indicating the results of validation tests). When combined with a real-time processing and data acquisition engine in a SCADA system that is capable of communicating with field devices via leased lines, VSAT, radio, dial-up, etc., many benefits can be realized.
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Afzalan, Milad, Farrokh Jazizadeh, and Mehdi Ahmadian. "Toward Railway Automated Defect Detection From Onboard Data Using Deep Learning." In 2020 Joint Rail Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/jrc2020-8031.

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Abstract Regular monitoring of railway systems is imperative for improving safety and ride quality. To this end, data collection is carried out regularly in the rail industry to document performance and maintenance. The use of machine learning methods in the past recent years has provided opportunities for improved data processing and defect detection and monitoring. Such methods rely on installing instrumentation wayside or collecting data from onboard rolling stock. Using the former approach, only specific locations can be monitored, which could hinder covering a large territory. The latter, however, enables monitoring large sections of track, hence proving far more spatial efficiency. In this paper, we have investigated the feasibility of rail defect detection using deep learning from onboard data. The source of data is acceleration and track geometry collected from onboard railcars. Such an approach allows collecting a large set of data on a regular basis. A long short-term memory (LSTM) architecture is proposed to examine the measured time-series to flag potential track defects. The proposed architecture investigates the characteristics of time-series signatures during a short time (∼ls) and classifies the associated track segment to normal/defect states. Furthermore, a novel automated labeling method is proposed to parse the exception report data (recorded by the maintenance team) and label defects for associated time-series signatures during the training phase. In a pilot study, field data from a revenue service Class I railroad has been used to evaluate the proposed deep learning method. The results show that it is possible to efficiently analyze the data (collected onboard a railcar operated in revenue service) for automated defect detection, with relatively higher accuracy for FRA type I defects.
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Wu, Dazhong, Janis Terpenny, Li Zhang, Robert Gao, and Thomas Kurfess. "Fog-Enabled Architecture for Data-Driven Cyber-Manufacturing Systems." In ASME 2016 11th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/msec2016-8559.

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Over the past few decades, both small- and medium-sized manufacturers as well as large original equipment manufacturers (OEMs) have been faced with an increasing need for low cost and scalable intelligent manufacturing machines. Capabilities are needed for collecting and processing large volumes of real-time data generated from manufacturing machines and processes as well as for diagnosing the root cause of identified defects, predicting their progression, and forecasting maintenance actions proactively to minimize unexpected machine down times. Although cloud computing enables ubiquitous and instant remote access to scalable information and communication technology (ICT) infrastructures and high volume data storage, it has limitations in latency-sensitive applications such as high performance computing and real-time stream analytics. The emergence of fog computing, Internet of Things (IoT), and cyber-physical systems (CPS) represent radical changes in the way sensing systems, along with ICT infrastructures, collect and analyze large volumes of real-time data streams in geographically distributed environments. Ultimately, such technological approaches enable machines to function as an agent that is capable of intelligent behaviors such as automatic fault and failure detection, self-diagnosis, and preventative maintenance scheduling. The objective of this research is to introduce a fog-enabled architecture that consists of smart sensor networks, communication protocols, parallel machine learning software, and private and public clouds. The fog-enabled architecture will have the potential to enable large-scale, geographically distributed online machine and process monitoring, diagnosis, and prognosis that require low latency and high bandwidth in the context of data-driven cyber-manufacturing systems.
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Larsson, So¨ren, and J. A. P. Kjellander. "An Industrial Robot and a Laser Scanner as a Flexible Solution Towards an Automatic System for Reverse Engineering of Unknown Objects." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58277.

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Reverse Engineering (RE) is concerned with the problem of creating CAD-models of real objects by measuring point data from their surfaces. Current solutions either require manual interaction or expect the nature of the objects to be known. In order to create a fully automatic system for Reverse Engineering of unknown objects the software that creates the CAD-model must be able to control the operation of the measuring system. This paper presents a real implementation of a measuring system suited for that purpose. The experimental setup is based on an industrial robot with a laser scanner mounted at the tool-mounting flange. The key component of the system is a programable CAD-system. The CAD system is used to simulate and control the movement of the robot, as well as collecting the data acquired from both the laser scanner and from the robot’s positional system.
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Chan, Shao-Hung, Xiaoyue Xu, Ping-Tsang Wu, Ming-Li Chiang, and Li-Chen Fu. "Real-time Obstacle Avoidance using Supervised Recurrent Neural Network with Automatic Data Collection and Labeling." In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2019. http://dx.doi.org/10.1109/smc.2019.8914281.

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Kim, Sanghee, Rob H. Bracewell, and Ken M. Wallace. "A Framework for Automatic Causality Extraction Using Semantic Similarity." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35193.

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Textual documents are the most common way of storing and distributing information within organizations. Extracting useful information from large text collections is therefore the goal of every organization that would like to take advantage of the experience encapsulated in those texts. Entering data using a free text style is easy, as it does not require any special training. However, unstructured texts pose a major challenge for automatic extraction and retrieval systems. Generally, deep levels of text analysis using advanced and complex linguistic processing are necessary that involve computational linguistic experts and domain experts. Linguistic experts are rare in engineering organizations, which thus find it difficult to apply and exploit such advanced extraction techniques. It is therefore desirable to minimize the extensive involvement of linguist experts by learning extraction patterns automatically from example texts. In doing so, the analysis of given texts is necessary in order to identify the scope and suitable automatic methods. Focusing on causality reasoning in the field of fault diagnosis, the results of experimenting with an automatic causality extraction method using shallow linguistic processing are presented.
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Grigoriev, Gleb, Vladimir Gulin, Alexei Nikitin, Nikita Sivoy, Eugene Bondarev, Marat Islamuratov, Oksana Zakharova, Igor Karpov, Evgenii Liubimov, and Vladislav Votsalevskiy. "Integrated Droneborne Geophysics Application as a Tool for Exploration Optimization. Case Studies." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206250-ms.

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Abstract Unmanned aerial vehicles (UAV) have a great potential for geological exploration optimization at all stages. This study considers UAV implementation at different exploration stage. Integrated approach using unmanned aerial systems shows great effectiveness based on the completed surveys. Low-depth electrical exploration using the shallow electrical exploration method is one of the possible UAVs technologies with great potential. In this study there are several cases describing main field data acquisition, models and cross-sections processing. Unmanned aerial systems are applicable at all stages of the oil and gas value chain and are already an integral part of oil&gas production process. Now there are more than 70 unmanned aerial systems application scenarios. The main advantages of drones are that the use of this operational data collection tool allows: – to reduce the duration of collecting geospatial data by 70%, and the cost by 3 times; – make the best decisions quickly; – to realize additional potential for increasing efficiency (application at all stages of the production chain) – increase the production processes safety level The most promising and actively developing areas of technology application are: Geophysical surveys at different stages of geological exploration. Drones have great potential for application in non-seismic exploration methods in the early stages of geological exploration. In addition, UAV surveys are suitable for planning geological exploration and working out the conceptual arrangement of the terrain. The presence of an accurate digital elevation model at the start of work of the project team makes it possible to remove a number of uncertainties and questions about conducting field work on seismic exploration, the placement of infrastructure and corridor communications. Objective control of the capital construction progress. Another important area of drones application is aerial photography at all stages of capital construction. With the help of UAVs, it is possible to control such parameters as the status and quality of construction and installation works, equipment of contractors, compliance with safety and environmental standards, and others. To do this, the unmanned vehicle flies around the object with a given regularity, filming it from different angles. After aerial photography, special software stitches the results into photogrammetric products (digital terrain model, orthophotomaps, 3D models) with an accuracy of 4–6 centimeters. On the constructed models, you can calculate the dynamics by one or another parameter. Operational fieldwork and intrastructure monitoring. At the same time, one of the key goals of technology application is the creation of a network of autonomous stations with drones at all assets for remote control of the company's production processes. The first step in this direction was the joint pilot testing of an automated take-off and landing station with an unmanned aerial vehicle of a multi-rotor type. The use of the station will reduce the time and cost of collecting data on capital construction and infrastructure. Project teams will be able to react faster to changes. An automated take-off and landing station allows the use of unmanned aerial vehicles without human intervention. The drone can independently take off, perform the necessary operations, land and recharge. Thus, flight operations and data collection can be performed remotely without the constant presence of a specialist on site.
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Reports on the topic "Automatic data collecting systems"

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Gaponenko, Artiom, and Andrey Golovin. Electronic magazine with rating system of an estimation of individual and collective work of students. Science and Innovation Center Publishing House, October 2017. http://dx.doi.org/10.12731/er0043.06102017.

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«The electronic magazine with rating system of an estimation of individual and collective work of students» (EM) is developed in document Microsoft Excel with use of macros. EM allows to automate all the calculated operations connected with estimation of amount scored by students in each form of the current control. EM provides automatic calculation of rating of the student with reflection of a maximum quantity of the points received in given educational group. The rating equal to “1” is assigned to the student who has got a maximum quantity of points for the certain date. For the other students the share of their points in this maximum size is indicated. The choice of an estimation is made in an alphabetic format according to requirements of the European translation system of test units for the international recognition of results of educational outcomes (ECTS - European Credit Transfer System), by use of a corresponding scale of an estimation. The list of students is placed on the first page of magazine and automatically displayed on all subsequent pages. For each page of magazine the optimal size of document printing is set with automatic enter of current date and time. Owing to accounting rate of complexity of task EM is the universal technical tool which can be used for any subject matter.
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Trenkle, Allen H. Evaluation of Rumen Boluses as an Electronic Identification System for Cattle in an Automated Data Collection System. Ames (Iowa): Iowa State University, January 2006. http://dx.doi.org/10.31274/ans_air-180814-591.

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Kolawa, A., B. Strickland, and A. Hicken. Automatic Test Data Generation Tool for Large- Scale Software Systems. Fort Belvoir, VA: Defense Technical Information Center, May 1994. http://dx.doi.org/10.21236/ada289081.

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Bates, C. Richards, Melanie Chocholek, Clive Fox, John Howe, and Neil Jones. Scottish Inshore Fisheries Integrated Data System (SIFIDS): Work package (3) final report development of a novel, automated mechanism for the collection of scallop stock data. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23449.

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[Extract from Executive Summary] This project, aimed at the development of a novel, automated mechanism for the collection of scallop stock data was a sub-part of the Scottish Inshore Fisheries Integrated Data Systems (SIFIDS) project. The project reviewed the state-of-the-art remote sensing (geophysical and camera-based) technologies available from industry and compared these to inexpensive, off-the -shelf equipment. Sea trials were conducted on scallop dredge sites and also hand-dived scallop sites. Data was analysed manually, and tests conducted with automated processing methods. It was concluded that geophysical acoustic technologies cannot presently detect individual scallop but the remote sensing technologies can be used for broad scale habitat mapping of scallop harvest areas. Further, the techniques allow for monitoring these areas in terms of scallop dredging impact. Camera (video and still) imagery is effective for scallop count and provide data that compares favourably with diver-based ground truth information for recording scallop density. Deployment of cameras is possible through inexpensive drop-down camera frames which it is recommended be deployed on a wide area basis for further trials. In addition, implementation of a ‘citizen science’ approach to wide area recording is suggested to increase the stock assessment across the widest possible variety of seafloor types around Scotland. Armed with such data a full, statistical analysis could be completed and data used with automated processing routines for future long-term monitoring of stock.
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Berney, Ernest, Andrew Ward, and Naveen Ganesh. First generation automated assessment of airfield damage using LiDAR point clouds. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/40042.

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This research developed an automated software technique for identifying type, size, and location of man-made airfield damage including craters, spalls, and camouflets from a digitized three-dimensional point cloud of the airfield surface. Point clouds were initially generated from Light Detection and Ranging (LiDAR) sensors mounted on elevated lifts to simulate aerial data collection and, later, an actual unmanned aerial system. LiDAR data provided a high-resolution, globally positioned, and dimensionally scaled point cloud exported in a LAS file format that was automatically retrieved and processed using volumetric detection algorithms developed in the MATLAB software environment. Developed MATLAB algorithms used a three-stage filling technique to identify the boundaries of craters first, then spalls, then camouflets, and scaled their sizes based on the greatest pointwise extents. All pavement damages and their locations were saved as shapefiles and uploaded into the GeoExPT processing environment for visualization and quality control. This technique requires no user input between data collection and GeoExPT visualization, allowing for a completely automated software analysis with all filters and data processing hidden from the user.
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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, May 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.
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Wright, Kirsten. Collecting Plant Phenology Data In Imperiled Oregon White Oak Ecosystems: Analysis and Recommendations for Metro. Portland State University, March 2020. http://dx.doi.org/10.15760/mem.64.

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Highly imperiled Oregon white oak ecosystems are a regional conservation priority of numerous organizations, including Oregon Metro, a regional government serving over one million people in the Portland area. Previously dominant systems in the Pacific Northwest, upland prairie and oak woodlands are now experiencing significant threat, with only 2% remaining in the Willamette Valley in small fragments (Hulse et al. 2002). These fragments are of high conservation value because of the rich biodiversity they support, including rare and endemic species, such as Delphinium leucophaeum (Oregon Department of Agriculture, 2020). Since 2010, Metro scientists and volunteers have collected phenology data on approximately 140 species of forbs and graminoids in regional oak prairie and woodlands. Phenology is the study of life-stage events in plants and animals, such as budbreak and senescence in flowering plants, and widely acknowledged as a sensitive indicator of environmental change (Parmesan 2007). Indeed, shifts in plant phenology have been observed over the last few decades as a result of climate change (Parmesan 2006). In oak systems, these changes have profound implications for plant community composition and diversity, as well as trophic interactions and general ecosystem function (Willis 2008). While the original intent of Metro’s phenology data-collection was to track long-term phenology trends, limitations in data collection methods have made such analysis difficult. Rather, these data are currently used to inform seasonal management decisions on Metro properties, such as when to collect seed for propagation and when to spray herbicide to control invasive species. Metro is now interested in fine-tuning their data-collection methods to better capture long-term phenology trends to guide future conservation strategies. Addressing the regional and global conservation issues of our time will require unprecedented collaboration. Phenology data collected on Metro properties is not only an important asset for Metro’s conservation plan, but holds potential to support broader research on a larger scale. As a leader in urban conservation, Metro is poised to make a meaningful scientific contribution by sharing phenology data with regional and national organizations. Data-sharing will benefit the common goal of conservation and create avenues for collaboration with other scientists and conservation practitioners (Rosemartin 2013). In order to support Metro’s ongoing conservation efforts in Oregon white oak systems, I have implemented a three-part master’s project. Part one of the project examines Metro’s previously collected phenology data, providing descriptive statistics and assessing the strengths and weaknesses of the methods by which the data were collected. Part two makes recommendations for improving future phenology data-collection methods, and includes recommendations for datasharing with regional and national organizations. Part three is a collection of scientific vouchers documenting key plant species in varying phases of phenology for Metro’s teaching herbarium. The purpose of these vouchers is to provide a visual tool for Metro staff and volunteers who rely on plant identification to carry out aspects of their job in plant conservation. Each component of this project addresses specific aspects of Metro’s conservation program, from day-to-day management concerns to long-term scientific inquiry.
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Neeley, Aimee, Stace E. Beaulieu, Chris Proctor, Ivona Cetinić, Joe Futrelle, Inia Soto Ramos, Heidi M. Sosik, et al. Standards and practices for reporting plankton and other particle observations from images. Woods Hole Oceanographic Institution, July 2021. http://dx.doi.org/10.1575/1912/27377.

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This technical manual guides the user through the process of creating a data table for the submission of taxonomic and morphological information for plankton and other particles from images to a repository. Guidance is provided to produce documentation that should accompany the submission of plankton and other particle data to a repository, describes data collection and processing techniques, and outlines the creation of a data file. Field names include scientificName that represents the lowest level taxonomic classification (e.g., genus if not certain of species, family if not certain of genus) and scientificNameID, the unique identifier from a reference database such as the World Register of Marine Species or AlgaeBase. The data table described here includes the field names associatedMedia, scientificName/ scientificNameID for both automated and manual identification, biovolume, area_cross_section, length_representation and width_representation. Additional steps that instruct the user on how to format their data for a submission to the Ocean Biodiversity Information System (OBIS) are also included. Examples of documentation and data files are provided for the user to follow. The documentation requirements and data table format are approved by both NASA’s SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and the National Science Foundation’s Biological and Chemical Oceanography Data Management Office (BCO-DMO).
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Li, Howell, Enrique Saldivar-Carranza, Jijo K. Mathew, Woosung Kim, Jairaj Desai, Timothy Wells, and Darcy M. Bullock. Extraction of Vehicle CAN Bus Data for Roadway Condition Monitoring. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317212.

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Obtaining timely information across the state roadway network is important for monitoring the condition of the roads and operating characteristics of traffic. One of the most significant challenges in winter roadway maintenance is identifying emerging or deteriorating conditions before significant crashes occur. For instance, almost all modern vehicles have accelerometers, anti-lock brake (ABS) and traction control systems. This data can be read from the Controller Area Network (CAN) of the vehicle, and combined with GPS coordinates and cellular connectivity, can provide valuable on-the-ground sampling of vehicle dynamics at the onset of a storm. We are rapidly entering an era where this vehicle data can provide an agency with opportunities to more effectively manage their systems than traditional procedures that rely on fixed infrastructure sensors and telephone reports. This data could also reduce the density of roadway weather information systems (RWIS), similar to how probe vehicle data has reduced the need for micro loop or side fire sensors for collecting traffic speeds.
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Tidd, Alexander N., Richard A. Ayers, Grant P. Course, and Guy R. Pasco. Scottish Inshore Fisheries Integrated Data System (SIFIDS): work package 6 final report development of a pilot relational data resource for the collation and interpretation of inshore fisheries data. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23452.

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[Extract from Executive Summary] The competition for space from competing sectors in the coastal waters of Scotland has never been greater and thus there is a growing a need for interactive seascape planning tools that encompass all marine activities. Similarly, the need to gather data to inform decision makers, especially in the fishing industry, has become essential to provide advice on the economic impact on fishing fleets both in terms of alternative conservation measures (e.g. effort limitations, temporal and spatial closures) as well as the overlap with other activities, thereby allowing stakeholders to derive a preferred option. The SIFIDS project was conceived to allow the different relevant data sources to be identified and to allow these data to be collated in one place, rather than as isolated data sets with multiple data owners. The online interactive tool developed as part of the project (Work Package 6) brought together relevant data sets and developed data storage facilities and a user interface to allow various types of user to view and interrogate the data. Some of these data sets were obtained as static layers which could sit as background data e.g. substrate type, UK fishing limits; whilst other data came directly from electronic monitoring systems developed as part of the SIFIDS project. The main non-static data source was Work Package 2, which was collecting data from a sample of volunteer inshore fishing vessels (<12m). This included data on location; time; vessel speed; count, time and position of deployment of strings of creels (or as fleets and pots as they are also known respectively); and a count of how many creels were hauled on these strings. The interactive online tool allowed all the above data to be collated in a specially designed database and displayed in near real time on the web-based application.
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