Paper
10 October 2023 Design and implementation of a scenario classification system for the internet of things application
Hao Zheng, Hong Li, Bo Xu
Author Affiliations +
Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279945 (2023) https://doi.org/10.1117/12.3006002
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia
Abstract
With the rapid development of the Internet of Things industry today, it is imperative to classify the Internet of Things scenarios to adapt to the needs of the Internet of Things in different scenarios. In recent years, Convolutional Neural Network (CNN) has succeeded in scene parsing. The methods based on CNN generally extract the visual features of the input images through the step-by-step abstraction of multiple convolutional layers and then parse the corresponding segmentation results of the output images through the step-by-step restoration of multiple deconvolutions. Screen the scene pictures of the Internet of Things from the large data set, use the image recognition algorithm to extract the features of the photographs, and use the extracted features to cluster the image set (for example, it can be divided into a family environment, car environment, etc.), divide the pictures with similar features into the same set, and finally measure the clustering accuracy to realize the Internet of Things scene classification. Finally, scene recognition accuracy is about 87%, and the clustering of feature vectors is also satisfactory.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hao Zheng, Hong Li, and Bo Xu "Design and implementation of a scenario classification system for the internet of things application", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279945 (10 October 2023); https://doi.org/10.1117/12.3006002
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KEYWORDS
Internet of things

Education and training

Data modeling

Feature extraction

Classification systems

Principal component analysis

Image processing

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