An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion
The application of Internet of Things (IoT) technology in news media communication has significantly enhanced the effectiveness and coverage of news data releases. However, as the scale of news data continues to grow, traditional IoT approaches face challenges such as slow data processing speed and...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2023-06-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-1428.pdf |
| _version_ | 1797796736512557056 |
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| author | Zhuozheng Xie Junren Wang |
| author_facet | Zhuozheng Xie Junren Wang |
| author_sort | Zhuozheng Xie |
| collection | DOAJ |
| description | The application of Internet of Things (IoT) technology in news media communication has significantly enhanced the effectiveness and coverage of news data releases. However, as the scale of news data continues to grow, traditional IoT approaches face challenges such as slow data processing speed and low mining efficiency. To address these issues, a novel news feature mining system combining IoT and Artificial Intelligence (AI) has been developed. The hardware components of the system include a data collector, a data analyzer, a central controller, and sensors. The GJ-HD data collector is utilized to gather news data. Multiple network interfaces are designed at the device terminal to ensure data extraction from the internal disk in case of device failure. The central controller integrates the MP/MC and DCNF interfaces for seamless information interconnection. In the software aspect of the system, the network transmission protocol of the AI algorithm is embedded, and a communication feature model is constructed. This enables fast and accurate mining of news data communication features. Experimental results demonstrate that the system achieves a mining accuracy of over 98%, enabling efficient processing of news data. Overall, the proposed IoT and AI-based news feature mining system overcomes the limitations of traditional approaches, allowing for efficient and accurate processing of news data in a rapidly expanding digital landscape. |
| first_indexed | 2024-03-13T03:37:34Z |
| format | Article |
| id | doaj.art-829f7d7cbd5c40a493db1cec95230bd9 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-03-13T03:37:34Z |
| publishDate | 2023-06-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-829f7d7cbd5c40a493db1cec95230bd92023-06-23T15:05:07ZengPeerJ Inc.PeerJ Computer Science2376-59922023-06-019e142810.7717/peerj-cs.1428An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusionZhuozheng XieJunren WangThe application of Internet of Things (IoT) technology in news media communication has significantly enhanced the effectiveness and coverage of news data releases. However, as the scale of news data continues to grow, traditional IoT approaches face challenges such as slow data processing speed and low mining efficiency. To address these issues, a novel news feature mining system combining IoT and Artificial Intelligence (AI) has been developed. The hardware components of the system include a data collector, a data analyzer, a central controller, and sensors. The GJ-HD data collector is utilized to gather news data. Multiple network interfaces are designed at the device terminal to ensure data extraction from the internal disk in case of device failure. The central controller integrates the MP/MC and DCNF interfaces for seamless information interconnection. In the software aspect of the system, the network transmission protocol of the AI algorithm is embedded, and a communication feature model is constructed. This enables fast and accurate mining of news data communication features. Experimental results demonstrate that the system achieves a mining accuracy of over 98%, enabling efficient processing of news data. Overall, the proposed IoT and AI-based news feature mining system overcomes the limitations of traditional approaches, allowing for efficient and accurate processing of news data in a rapidly expanding digital landscape.https://peerj.com/articles/cs-1428.pdfIoT technologyNews communicationSensorsArtificial intelligence |
| spellingShingle | Zhuozheng Xie Junren Wang An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion PeerJ Computer Science IoT technology News communication Sensors Artificial intelligence |
| title | An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion |
| title_full | An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion |
| title_fullStr | An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion |
| title_full_unstemmed | An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion |
| title_short | An artificial intelligence based news feature mining system based on the Internet of Things and multi-sensor fusion |
| title_sort | artificial intelligence based news feature mining system based on the internet of things and multi sensor fusion |
| topic | IoT technology News communication Sensors Artificial intelligence |
| url | https://peerj.com/articles/cs-1428.pdf |
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