Abstract
Internet of things search service is one of the most important services provided by the Internet of things. However, how to efficiently and accurately obtain the most suitable information from the massive, heterogeneous and dynamic entity data of Internet of things is a big challenge. First of all, there is no unified description model of entity resources in the Internet of things at this stage, which leads to the heterogeneity of resource description and brings difficulties to the data collection and processing of entity search system in the Internet of things. Secondly, the access of large-scale heterogeneous Internet of things devices makes the Internet of things entity data have the characteristics of mass, polymorphism and relevance. The traditional web search technology is no longer suitable for the Internet of things environment. This paper focuses on the design and development of electrical automation experiment platform. The main task of this project is to build and develop a flexible and easy-to-use electrical automation experimental platform with multi-function, which can meet the requirements of teaching experiment and scientific research. The automation platform takes Schneider m218, m258 PLC and lmc058 motion controller as the core, and also includes touch screen, frequency converter, servo driver, servo motor and mechanical arm. It solves the problem of single and inflexible equipment of the original experimental platform, and has good practical significance.
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References
Senniah, J.P., Prasad, A.R.: Efficient data sensing with group key management for intelligent automation system by one-way key derivation in wireless networks. J. Ambient. Intell. Humaniz. Comput. 12(5), 4655–4662 (2021)
Senniah, J.P., Prasad, A.: Efficient data sensing with group key management for intelligent automation system by one-way key derivation in wireless networks. J. Ambient Intell. Human. Comput. 12, 4655–4662 (2020). https://doi.org/10.1007/s12652-020-01862-x
Paveethra, S.R., Barathi, B., Geethapriya, M., et al.: Theoretical modelling and implementation of home energy management system using IoT based automation system. Mater. Today Proc. 45, 1790–1793 (2020)
Ms, A., Yong, W.: Renewable energy supply chain management with flexibility and automation in a production system. Mater. Today Proc. 45, 1790–1793 (2021)
Zhang, X.L.: Discussion on application of power plant electrical integrated automation technology (2021)
Wang, Y., Zhang, N., Guan, Y., et al.: Inheritance and expansion analysis of research topics between energy internet and smart grid. Autom. Electr. Power Syst. 44(4), 1–8 (2020)
Zúiga, A.A., Baleia, A., Fernandes, J., et al.: Classical failure modes and effects analysis in the context of smart grid cyber-physical systems. Energies 13(5), 1215 (2020)
Rosewater, D., Schenkman, B., Santoso, S.: Adaptive modeling process for a battery energy management system. In: 2020 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) (2020)
Lin, L., Yue, S.: Application of electrical engineering automation technology in power system operation. Int. J. Power Energy Syst. 32(2), 969–976 (2020)
Wang, Z., Ma, X., Huang, W.: Vehicle license plate recognition based on wavelet transform and vertical edge matching. Int. J. Pattern Recognit. Artif. Intell. 34(06), 1134–1142 (2020)
NF C46-908-4/A1-2020: Communication networks and systems for power utility automation - part 4: system and project management
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Song, T. (2022). Design and Implementation of Electrical Automation System Management Based on Internet of Things Technology. In: Xu, Z., Alrabaee, S., Loyola-González, O., Zhang, X., Cahyani, N.D.W., Ab Rahman, N.H. (eds) Cyber Security Intelligence and Analytics. CSIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 125. Springer, Cham. https://doi.org/10.1007/978-3-030-97874-7_112
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DOI: https://doi.org/10.1007/978-3-030-97874-7_112
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