2017 IEEE 15th International Conference on Industrial Informatics (INDIN)最新文献

A time-synchronized ZigBee building network for smart water management 用于智能水管理的时间同步ZigBee建筑网络

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2020-11-01 DOI: 10.1109/INDIN.2017.8104948

C. Wu, Hongxu Zhu, L. Lai, Anna S. F. Chang, Fengjun Li, K. Tsang, R. Kalawsky

引用次数: 5

Novel infrastructure with common API using docker for scaling the degree of platforms for smart community services 新颖的基础设施，具有使用docker的通用API，用于扩展智能社区服务平台的程度

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104818

Tatsuki Miura, J. Wijekoon, Shanaka Prageeth, H. Nishi

{"title":"Novel infrastructure with common API using docker for scaling the degree of platforms for smart community services","authors":"Tatsuki Miura, J. Wijekoon, Shanaka Prageeth, H. Nishi","doi":"10.1109/INDIN.2017.8104818","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104818","url":null,"abstract":"The development of smart communities has diversified not only service execution platforms but also the resolvers of multiple service requirements, each of which has different requirements in terms of processing delay, anonymity, computational cost, the amount of data at a given level of granularity, etc. To meet these requirements, an infrastructure that easily performs service migration and provides services with the correct processing nodes using IP-independent distributed processing methods such as Authorized Stream Contents Analysis (ASCA) is becoming a pressing need of smart communities. ASCA is an advanced method of analyzing packet streams and filtering necessary packet streams according to the marker tags in the contents of the streams under the Opt-In manner. Moreover, smart communities require that every service be able to perform ASCA and gather necessary data because of the diversified nature of the services. Consequently, in this paper, we have implemented a service infrastructure using a Docker container that facilitates service migration and provides services with a common Application Programming Interface (API) using ASCA. The API provides a process throughput of over 60 Gbps on a Docker container using Zero-Copy mechanism.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"25 1","pages":"474-479"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75999218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Ontology-driven IoT code generation for FIWARE FIWARE的本体驱动物联网代码生成

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104743

Charles Steinmetz, Greyce N. Schroeder, A. Roque, C. Pereira, Carolin Wagner, Philipp Saalmann, B. Hellingrath

引用次数: 16

Benchmarking of existing OPC UA implementations for Industrie 4.0-compliant digitalization solutions 对工业4.0数字化解决方案的现有OPC UA实现进行基准测试

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104838

Hermann Haskamp, Michaelene A Meyer, Romina Mollmann, Florian Orth, A. Colombo

引用次数: 26

Unsupervised mode detection in cyber-physical systems using variable order Markov models 基于变阶马尔可夫模型的网络物理系统无监督模式检测

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104881

Barış Gün Sürmeli, Feyza Eksen, Bilal Dinc, P. Schüller, M. Tümer

{"title":"Unsupervised mode detection in cyber-physical systems using variable order Markov models","authors":"Barış Gün Sürmeli, Feyza Eksen, Bilal Dinc, P. Schüller, M. Tümer","doi":"10.1109/INDIN.2017.8104881","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104881","url":null,"abstract":"Sequential data generated from various sources in a multi-mode industrial production system provides valuable information on the current mode of the system and enables one to build a model for each individual operating mode. Using these models in a multi-mode system, one may distinguish modes of the system and, furthermore, detect whether the current mode is a (normal or faulty) mode known from historical data, or a new mode. In this work, we model each individual mode by a probabilistic suffix tree (PST) used to implement variable order Markov models (VOMMs) and propose a novel unsupervised PST matching algorithm that compares the tree models by a matching cost once they are constructed. The matching cost we define comprises of a subsequence dissimilarity cost and a probability cost. Our tree matching method enables to compare two PSTs in linear time by one concurrent top-down pass. We use this matching cost as a similarity measure for k-medoid clustering and cluster PSTs obtained from system modes according to their matching costs. The overall approach yields promising results for unsupervised identification of modes on data obtained from of a physical factory demonstrator. Notably we can distinguish modes on two levels of granularity, both corresponding to human expert labels, with a RAND score of up to 73 % compared to a baseline of at most 42 %.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"42 1","pages":"841-846"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79068753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Cloud architecture for industrial image processing: Platform for realtime inline quality assurance 工业图像处理的云架构:实时在线质量保证平台

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104749

Dirk Jacobsen, P. Ott

{"title":"Cloud architecture for industrial image processing: Platform for realtime inline quality assurance","authors":"Dirk Jacobsen, P. Ott","doi":"10.1109/INDIN.2017.8104749","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104749","url":null,"abstract":"Cloud computing offers the opportunity to minimize the evaluation time of complex algorithms — e.g. needed for computational imaging — by horizontal scaling of the available computing resources. By this way, new image analyzing algorithms can be employed in weak real-time conditions, like inline quality analysis in production with time stamps in the order of several tens of seconds. The cloud offers a platform to merge sensor data of all production processes to analyze quality data comprehensively, e.g. for methods like predictive maintenance. Typically, cloud environments are applied for the Internet of things (IoT) or Big Data analysis. But IoT-applications usually generate very small data packages (like sensor values with a size much less than 1 megabyte), while BigData applications deal with very high data volume (terra-or petabyte). Image processing requires an environment, which is optimized for medium size data streaming, composed of images with a size in the lower megabyte range. In this paper, a sensor-to-cloud architecture as a platform for image processing is described. This approach is upward compatible, because it is not necessary to change the sensor hardware, e.g. if algorithms with considerable higher computing complexity are desired (like for a smart camera), so algorithms can be exchanged in the cloud without interrupting the production process.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"1 1","pages":"72-74"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77309759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Next-generation enterprise architectures: Common vernacular and evolution towards service-orientation 下一代企业架构:通用术语和面向服务的演进

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104742

M. Moghaddam, C. Robert Kenley, Julia M. Colby, Marissa N. Cadavid Berns, R. Rausch, J. Markham, W. Skeffington, J. Garrity, A. Chaturvedi, A. Deshmukh

引用次数: 10

Developing open source cyber-physical systems for service-oriented architectures using OPC UA 使用OPC UA为面向服务的体系结构开发开源网络物理系统

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104751

M. Müller, Elmar Wings, L. Bergmann

{"title":"Developing open source cyber-physical systems for service-oriented architectures using OPC UA","authors":"M. Müller, Elmar Wings, L. Bergmann","doi":"10.1109/INDIN.2017.8104751","DOIUrl":"https://doi.org/10.1109/INDIN.2017.8104751","url":null,"abstract":"Cyber-physical systems (CPS) are key enabling technologies for the fourth industrial revolution, referred to as Industrie 4.0 or Industry 4.0. The Reference Architecture Model Industrie 4.0 (RAMI4.0) has recently been standardized and OPC Unified Architecture (OPC UA) is listed as the sole recommendation for implementation of a communication layer. Many automation and control systems offer already implementations of OPC UA but no satisfying implementation of OPC UA was found for Arduino, a popular platform for engineering physical computing systems. This paper presents open source integration and application of a customizable OPC UA server on an Arduino Yun board using open62541, an open source and free implementation of OPC UA. The Arduino board discussed in this paper offers hot-end closed-loop temperature control for a 3D printer but the temperature set value and control parameters can be manipulated and requested via OPC UA using OPC UA clients. The application is verified using Prosys OPC UA Client and UaExpert. The results of our research can be used for developing open source cyber-physical systems without specialized knowledge in microcontroller programming, bringing Industry 4.0 applications into classrooms without effort.","PeriodicalId":6595,"journal":{"name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","volume":"63 1","pages":"83-88"},"PeriodicalIF":0.0,"publicationDate":"2017-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84329491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Computerized control strategy to prevent wastewater plants pollution 防止污水厂污染的计算机控制策略

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104811

Y. Bolea, A. Grau-Saldes, H. Martínez

引用次数: 0

Big data as a promoter of industry 4.0: Lessons of the semiconductor industry 大数据作为工业4.0的推动者:半导体行业的经验教训

2017 IEEE 15th International Conference on Industrial Informatics (INDIN) Pub Date : 2017-07-24 DOI: 10.1109/INDIN.2017.8104778

David Cemernek, H. Gursch, Roman Kern

引用次数: 19