Monitoring and visualization application of smart city energy economic management based on IoT sensors

Li, Qianyuan; Jiang, Zhiyong; Yuan, Feng

doi:10.1007/s00521-021-06108-1

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…With the rapid development of society, the demand for energy is constantly increasing, and the importance of energy monitoring and management is increasingly prominent [1][2][3][4][5]. Smart energy monitoring and analysis based on image recognition technology can provide more accurate and realtime data support for energy systems, improving the efficiency and level of energy management [6][7][8][9][10][11][12][13]. In the context of Industry 4.0 and digital transformation, various industries are constantly moving towards intelligent development.…”

Section: Introductionmentioning

confidence: 99%

Smart Energy Monitoring and Analysis Method Based on Image Recognition Technology

Yu¹,

Ali²,

Khan³

et al. 2023

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Smart energy monitoring and analysis based on image recognition technology can provide more accurate and real-time data support for energy systems, improving the efficiency and level of energy management. The method is sensitive to factors such as image quality, illumination, and angle, and when the image quality is not high, the recognition effect may be poor. Some methods, such as feature extraction and deep learning methods, have a large amount of computation and relatively poor real-time performance, which may affect the timeliness of energy monitoring. Therefore, this study conducts a study on smart energy monitoring and analysis methods based on image recognition technology. The energy monitoring instrument panel is preprocessed with brightness adjustment and Hough transform. After extracting the pointer instrument panel, the pointer detection and angle calculation are performed by using connected domain analysis, thinning algorithm, line fitting, and pointer direction judgment mechanism. The energy monitoring instrument reading recognition method is given. The effectiveness of the proposed method is verified through experimental results analysis.

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Section: Introductionmentioning

confidence: 99%

Smart Energy Monitoring and Analysis Method Based on Image Recognition Technology

Yu¹,

Ali²,

Khan³

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Xin [3] proposes a flexible structure controller based on type 2 fuzzy reinforcement learning algorithm. Li et al [4] proposed the application of IoT sensors to urban economic monitoring, the idea of early warning, and the construction of an urban economic data monitoring and early warning model. Lou [5] uses the Gaussian mixture model of machine vision to build the mapping relationship between the observed variables of the object and the robot joint variables.…”

mentioning

confidence: 99%