1,018 research outputs found

    Exploring sensor data management

    Get PDF
    The increasing availability of cheap, small, low-power sensor hardware and the ubiquity of wired and wireless networks has led to the prediction that `smart evironments' will emerge in the near future. The sensors in these environments collect detailed information about the situation people are in, which is used to enhance information-processing applications that are present on their mobile and `ambient' devices.\ud \ud Bridging the gap between sensor data and application information poses new requirements to data management. This report discusses what these requirements are and documents ongoing research that explores ways of thinking about data management suited to these new requirements: a more sophisticated control flow model, data models that incorporate time, and ways to deal with the uncertainty in sensor data

    RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

    Get PDF
    Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

    Cost-Effective Implementation of a Temperature Traceability System Based on Smart RFID Tags and IoT Services

    Full text link
    [EN] This paper presents the design and validation of a traceability system, based on radio frequency identification (RFID) technology and Internet of Things (IoT) services, intended to address the interconnection and cost-implementation problems typical in traceability systems. The RFID layer integrates temperature sensors into RFID tags, to track and trace food conditions during transportation. The IoT paradigm makes it possible to connect multiple systems to the same platform, addressing interconnection problems between different technology providers. The cost-implementation issues are addressed following the Data as a Service (DaaS) billing scheme, where users pay for the data they consume and not the installed equipment, avoiding the big initial investment that these high-tech solutions commonly require. The developed system is validated in two case scenarios, one carried out in controlled laboratory conditions, monitoring chopped pumpkin. Another case, carried out in a real scenario, monitors oranges sent from Valencia, Spain to Cork, Ireland.Urbano, O.; Perles, A.; Pedraza, C.; Rubio-Arraez, S.; CastellĂł GĂłmez, ML.; Ortolá Ortolá, MD.; Mercado Romero, R. (2020). Cost-Effective Implementation of a Temperature Traceability System Based on Smart RFID Tags and IoT Services. Sensors. 20(4):1-19. https://doi.org/10.3390/s20041163119204Aung, M. M., & Chang, Y. S. (2014). Traceability in a food supply chain: Safety and quality perspectives. Food Control, 39, 172-184. doi:10.1016/j.foodcont.2013.11.007Bosona, T., & Gebresenbet, G. (2013). Food traceability as an integral part of logistics management in food and agricultural supply chain. Food Control, 33(1), 32-48. doi:10.1016/j.foodcont.2013.02.004Bechini, A., Cimino, M. G. C. A., Marcelloni, F., & Tomasi, A. (2008). Patterns and technologies for enabling supply chain traceability through collaborative e-business. Information and Software Technology, 50(4), 342-359. doi:10.1016/j.infsof.2007.02.017Badia-Melis, R., Mishra, P., & Ruiz-GarcĂ­a, L. (2015). Food traceability: New trends and recent advances. A review. Food Control, 57, 393-401. doi:10.1016/j.foodcont.2015.05.005Timestrip Visual Indicators of Time and Temperaturehttps://timestrip.com/Storøy, J., Thakur, M., & Olsen, P. (2013). The TraceFood Framework – Principles and guidelines for implementing traceability in food value chains. Journal of Food Engineering, 115(1), 41-48. doi:10.1016/j.jfoodeng.2012.09.018Pizzuti, T., Mirabelli, G., Sanz-Bobi, M. A., & GomĂ©z-GonzalĂ©z, F. (2014). Food Track & Trace ontology for helping the food traceability control. Journal of Food Engineering, 120, 17-30. doi:10.1016/j.jfoodeng.2013.07.017Landt, J. (2005). The history of RFID. IEEE Potentials, 24(4), 8-11. doi:10.1109/mp.2005.1549751Costa, C., Antonucci, F., Pallottino, F., Aguzzi, J., Sarriá, D., & Menesatti, P. (2012). A Review on Agri-food Supply Chain Traceability by Means of RFID Technology. Food and Bioprocess Technology, 6(2), 353-366. doi:10.1007/s11947-012-0958-7Mainetti, L., Mele, F., Patrono, L., Simone, F., Stefanizzi, M. L., & Vergallo, R. (2013). An RFID-Based Tracing and Tracking System for the Fresh Vegetables Supply Chain. International Journal of Antennas and Propagation, 2013, 1-15. doi:10.1155/2013/531364Figorilli, S., Antonucci, F., Costa, C., Pallottino, F., Raso, L., Castiglione, M., … Menesatti, P. (2018). A Blockchain Implementation Prototype for the Electronic Open Source Traceability of Wood along the Whole Supply Chain. Sensors, 18(9), 3133. doi:10.3390/s18093133Aguzzi, J., Sbragaglia, V., Sarriá, D., GarcĂ­a, J. A., Costa, C., RĂ­o, J. del, … SardĂ , F. (2011). A New Laboratory Radio Frequency Identification (RFID) System for Behavioural Tracking of Marine Organisms. Sensors, 11(10), 9532-9548. doi:10.3390/s111009532Donelli, M. (2018). An RFID-Based Sensor for Masonry Crack Monitoring. Sensors, 18(12), 4485. doi:10.3390/s18124485De Souza, P., Marendy, P., Barbosa, K., Budi, S., Hirsch, P., Nikolic, N., … Davie, A. (2018). Low-Cost Electronic Tagging System for Bee Monitoring. Sensors, 18(7), 2124. doi:10.3390/s18072124Corchia, L., Monti, G., & Tarricone, L. (2019). A Frequency Signature RFID Chipless Tag for Wearable Applications. Sensors, 19(3), 494. doi:10.3390/s19030494Zuffanelli, S., Aguila, P., Zamora, G., Paredes, F., Martin, F., & Bonache, J. (2016). A High-Gain Passive UHF-RFID Tag with Increased Read Range. Sensors, 16(7), 1150. doi:10.3390/s16071150Monteleone, S., Sampaio, M., & Maia, R. F. (2017). A novel deployment of smart Cold Chain system using 2G-RFID-Sys temperature monitoring in medicine Cold Chain based on Internet of Things. 2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). doi:10.1109/soli.2017.8120995Zou, Z., Chen, Q., Uysal, I., & Zheng, L. (2014). Radio frequency identification enabled wireless sensing for intelligent food logistics. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 372(2017), 20130313. doi:10.1098/rsta.2013.0313Azzarelli, J. M., Mirica, K. A., Ravnsbæk, J. B., & Swager, T. M. (2014). Wireless gas detection with a smartphone via rf communication. Proceedings of the National Academy of Sciences, 111(51), 18162-18166. doi:10.1073/pnas.1415403111Pies, M., Hajovsky, R., & Ozana, S. (2014). Wireless measurement of carbon monoxide concentration. 2014 14th International Conference on Control, Automation and Systems (ICCAS 2014). doi:10.1109/iccas.2014.6987843Azzara, A., Bocchino, S., Pagano, P., Pellerano, G., & Petracca, M. (2013). Middleware solutions in WSN: The IoT oriented approach in the ICSI project. 2013 21st International Conference on Software, Telecommunications and Computer Networks - (SoftCOM 2013). doi:10.1109/softcom.2013.6671886Ribeiro, A. R. L., Silva, F. C. S., Freitas, L. C., Costa, J. C., & FrancĂŞs, C. R. (2005). SensorBus. Proceedings of the 3rd international IFIP/ACM Latin American conference on Networking - LANC ’05. doi:10.1145/1168117.1168119Sulc, V., Kuchta, R., & Vrba, R. (2010). IQRF Smart House - A Case Study. 2010 Third International Conference on Advances in Mesh Networks. doi:10.1109/mesh.2010.17Porkodi, R., & Bhuvaneswari, V. (2014). The Internet of Things (IoT) Applications and Communication Enabling Technology Standards: An Overview. 2014 International Conference on Intelligent Computing Applications. doi:10.1109/icica.2014.73EPC Radio-Frequency Identity Protocols. Generation-2 UHF RFIDhttps://www.gs1.org/sites/default/files/docs/epc/uhfc1g2_2_0_0_standard_20131101.pdfUusitalo, M. (2006). Global Vision for the Future Wireless World from the WWRF. IEEE Vehicular Technology Magazine>, 1(2), 4-8. doi:10.1109/mvt.2006.283570Sung, J., Lopez, T. S., & Kim, D. (2007). The EPC Sensor Network for RFID and WSN Integration Infrastructure. Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW’07). doi:10.1109/percomw.2007.113Chunxiao Fan, Zhigang Wen, Fan Wang, & Yuexin Wu. (2011). A middleware of Internet of Things (IoT) based on ZigBee and RFID. IET International Conference on Communication Technology and Application (ICCTA 2011). doi:10.1049/cp.2011.0765Centenaro, M., Vangelista, L., Zanella, A., & Zorzi, M. (2016). Long-range communications in unlicensed bands: the rising stars in the IoT and smart city scenarios. IEEE Wireless Communications, 23(5), 60-67. doi:10.1109/mwc.2016.7721743Hai Liu, Bolic, M., Nayak, A., & Stojmenovic, I. (2008). Taxonomy and Challenges of the Integration of RFID and Wireless Sensor Networks. IEEE Network, 22(6), 26-35. doi:10.1109/mnet.2008.4694171Bertolini, M., Bevilacqua, M., & Massini, R. (2006). FMECA approach to product traceability in the food industry. Food Control, 17(2), 137-145. doi:10.1016/j.foodcont.2004.09.013Zhang, M., & Li, P. (2012). RFID Application Strategy in Agri-Food Supply Chain Based on Safety and Benefit Analysis. Physics Procedia, 25, 636-642. doi:10.1016/j.phpro.2012.03.137Engels, D. W., Kang, Y. S., & Wang, J. (2013). On security with the new Gen2 RFID security framework. 2013 IEEE International Conference on RFID (RFID). doi:10.1109/rfid.2013.6548148SINIEV: Un Centro Inteligente De Control De Tránsito Y Transporte Que BeneficiarĂ­a A Todo El PaĂ­shttps://revistadelogistica.com/actualidad/siniev-un-centro-inteligente-de-control-de-transito-y-transporte-que-beneficiara-a-todo-el-pais/Tentzeris, M. M., Kim, S., Traille, A., Aubert, H., Yoshihiro, K., Georgiadis, A., & Collado, A. (2013). Inkjet-printed RFID-enabled sensors on paper for IoT and “Smart Skin” applications. ICECom 2013. doi:10.1109/icecom.2013.6684749Vega, F., Pantoja, J., Morales, S., Urbano, O., Arevalo, A., Muskus, E., … Hernandez, N. (2016). An IoT-based open platform for monitoring non-ionizing radiation levels in Colombia. 2016 IEEE Colombian Conference on Communications and Computing (COLCOM). doi:10.1109/colcomcon.2016.7516379Yang, K., & Jia, X. (2011). Data storage auditing service in cloud computing: challenges, methods and opportunities. World Wide Web, 15(4), 409-428. doi:10.1007/s11280-011-0138-0Alfian, G., Rhee, J., Ahn, H., Lee, J., Farooq, U., Ijaz, M. F., & Syaekhoni, M. A. (2017). Integration of RFID, wireless sensor networks, and data mining in an e-pedigree food traceability system. Journal of Food Engineering, 212, 65-75. doi:10.1016/j.jfoodeng.2017.05.008Chen, R.-Y. (2015). Autonomous tracing system for backward design in food supply chain. Food Control, 51, 70-84. doi:10.1016/j.foodcont.2014.11.004Song, J., Wei, Q., Wang, X., Li, D., Liu, C., Zhang, M., & Meng, L. (2018). Degradation of carotenoids in dehydrated pumpkins as affected by different storage conditions. Food Research International, 107, 130-136. doi:10.1016/j.foodres.2018.02.024Montesano, D., Rocchetti, G., Putnik, P., & Lucini, L. (2018). Bioactive profile of pumpkin: an overview on terpenoids and their health-promoting properties. Current Opinion in Food Science, 22, 81-87. doi:10.1016/j.cofs.2018.02.003Rubio-Arraez, S., Capella, J. V., CastellĂł, M. L., & Ortolá, M. D. (2016). Physicochemical characteristics of citrus jelly with non cariogenic and functional sweeteners. Journal of Food Science and Technology, 53(10), 3642-3650. doi:10.1007/s13197-016-2319-4Carmona, L., AlquĂ©zar, B., Marques, V. V., & Peña, L. (2017). Anthocyanin biosynthesis and accumulation in blood oranges during postharvest storage at different low temperatures. Food Chemistry, 237, 7-14. doi:10.1016/j.foodchem.2017.05.07

    Spatial and Temporal Analysis on the Distribution of Active Radio-Frequency Identification (RFID) Tracking Accuracy with the Kriging Method

    Get PDF
    Radio frequency identification (RFID) technology has already been applied in a number of areas to facilitate the tracking process. However, the insufficient tracking accuracy of RFID is one of the problems that impedes its wider application. Previous studies focus on examining the accuracy of discrete points RFID, thereby leaving the tracking accuracy of the areas between the observed points unpredictable. In this study, spatial and temporal analysis is applied to interpolate the continuous distribution of RFID tracking accuracy based on the Kriging method. An implementation trial has been conducted in the loading and docking area in front of a warehouse to validate this approach. The results show that the weak signal area can be easily identified by the approach developed in the study. The optimum distance between two RFID readers and the effect of the sudden removal of readers are also presented by analysing the spatial and temporal variation of RFID tracking accuracy. This study reveals the correlation between the testing time and the stability of RFID tracking accuracy. Experimental results show that the proposed approach can be used to assist the RFID system setup process to increase tracking accuracy

    Semantic discovery and reuse of business process patterns

    Get PDF
    Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

    Federated Sensor Network architectural design for the Internet of Things (IoT)

    Get PDF
    An information technology that can combine the physical world and virtual world is desired. The Internet of Things (IoT) is a concept system that uses Radio Frequency Identification (RFID), WSN and barcode scanners to sense and to detect physical objects and events. This information is shared with people on the Internet. With the announcement of the Smarter Planet concept by IBM, the problem of how to share this data was raised. However, the original design of WSN aims to provide environment monitoring and control within a small scale local network. It cannot meet the demands of the IoT because there is a lack of multi-connection functionality with other WSNs and upper level applications. As various standards of WSNs provide information for different purposes, a hybrid system that gives a complete answer by combining all of them could be promising for future IoT applications. This thesis is on the subject of `Federated Sensor Network' design and architectural development for the Internet of Things. A Federated Sensor Network (FSN) is a system that integrates WSNs and the Internet. Currently, methods of integrating WSNs and the Internet can follow one of three main directions: a Front-End Proxy solution, a Gateway solution or a TCP/IP Overlay solution. Architectures based on the ideas from all three directions are presented in this thesis; this forms a comprehensive body of research on possible Federated Sensor Network architecture designs. In addition, a fully compatible technology for the sensor network application, namely the Sensor Model Language (SensorML), has been reviewed and embedded into our FSN systems. The IoT as a new concept is also comprehensively described and the major technical issues discussed. Finally, a case study of the IoT in logistic management for emergency response is given. Proposed FSN architectures based on the Gateway solution are demonstrated through hardware implementation and lab tests. A demonstration of the 6LoWPAN enabled federated sensor network based on the TCP/IP Overlay solution presents a good result for the iNET localization and tracking project. All the tests of the designs have verified feasibility and achieve the target of the IoT concept

    Towards industrial internet of things: crankshaft monitoring, traceability and tracking using RFID

    Get PDF
    The large number of requirements and opportunities for automatic identification in manufacturing domains such as automotive and electronics has accelerated the demand for item-level tracking using radio-frequency identification technology. End-users are interested in implementing automatic identification systems, which are capable of ensuring full component process history, traceability and tracking preventing costly downtime to rectify processing defects and product recalls. The research outlined in this paper investigates the feasibility of implementing an RFID system for the manufacturing and assembly of crankshafts. The proposed solution involves the attachment of bolts with embedded RFID functionality by fitting a reader antenna reader to an overhead gantry that spans the production line and reads and writes production data to the tags. The manufacturing, assembly and service data captured through RFID tags and stored on a local server, could further be integrated with higher-level business applications facilitating seamless integration within the factory
    • …
    corecore