Matches in SemOpenAlex for { <https://semopenalex.org/work/W4384563657> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W4384563657 endingPage "107623" @default.
- W4384563657 startingPage "107623" @default.
- W4384563657 abstract "In response to the shortcomings of existing centralized IoT detection activities, this article proposes a new IoT detection scheme based on programmable switches and deep self coding, which combines programmable switches with IoT MQTT protocol and multidimensional feature fusion algorithm. Based on this point, a comprehensive programmable switch and machine learning centralized IoT detection system are designed. This system is different from traditional centralized IoT detection systems. The IoT detection module discussed in this article is located on a programmable switch between IoT nodes and servers. This system utilizes the potential of programmable switches to quickly collect required information from packet data and pre detect fault data from the front end of the server, thereby quickly making IoT node packet processing decisions (i.e. redirecting or directly discarding) based on programmable switches to minimize the delay in transmitting data packets. Finally, in order to apply this technology to the field of sports training, we examined different directions of sports training. Therefore, based on the development of simulation systems, this article greatly enhances the practicality of such projects, effectively increasing the usage time and meeting the actual training needs. Therefore, The deep self coding computer simulation of sports training is an issue that we must pay attention to. The article conducted research on IoT detection based on deep self coding multidimensional feature fusion, and applied the research results to sports training, promoting the rapid development of sports training." @default.
- W4384563657 created "2023-07-18" @default.
- W4384563657 creator A5018005349 @default.
- W4384563657 date "2023-09-01" @default.
- W4384563657 modified "2023-09-27" @default.
- W4384563657 title "Application of IoT detection based on deep self coding multidimensional feature fusion in sports training" @default.
- W4384563657 cites W2567445045 @default.
- W4384563657 cites W2778953522 @default.
- W4384563657 cites W2797672813 @default.
- W4384563657 cites W2891171053 @default.
- W4384563657 cites W2900706455 @default.
- W4384563657 cites W3004864462 @default.
- W4384563657 cites W3035366542 @default.
- W4384563657 cites W3046810637 @default.
- W4384563657 cites W3095000438 @default.
- W4384563657 cites W3126452964 @default.
- W4384563657 cites W3135028703 @default.
- W4384563657 cites W3148181069 @default.
- W4384563657 cites W4310537920 @default.
- W4384563657 doi "https://doi.org/10.1016/j.ypmed.2023.107623" @default.
- W4384563657 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37468074" @default.
- W4384563657 hasPublicationYear "2023" @default.
- W4384563657 type Work @default.
- W4384563657 citedByCount "0" @default.
- W4384563657 crossrefType "journal-article" @default.
- W4384563657 hasAuthorship W4384563657A5018005349 @default.
- W4384563657 hasConcept C105795698 @default.
- W4384563657 hasConcept C132868160 @default.
- W4384563657 hasConcept C138885662 @default.
- W4384563657 hasConcept C149635348 @default.
- W4384563657 hasConcept C154945302 @default.
- W4384563657 hasConcept C158379750 @default.
- W4384563657 hasConcept C179518139 @default.
- W4384563657 hasConcept C2776401178 @default.
- W4384563657 hasConcept C31258907 @default.
- W4384563657 hasConcept C33923547 @default.
- W4384563657 hasConcept C41008148 @default.
- W4384563657 hasConcept C41895202 @default.
- W4384563657 hasConcept C79403827 @default.
- W4384563657 hasConcept C81860439 @default.
- W4384563657 hasConceptScore W4384563657C105795698 @default.
- W4384563657 hasConceptScore W4384563657C132868160 @default.
- W4384563657 hasConceptScore W4384563657C138885662 @default.
- W4384563657 hasConceptScore W4384563657C149635348 @default.
- W4384563657 hasConceptScore W4384563657C154945302 @default.
- W4384563657 hasConceptScore W4384563657C158379750 @default.
- W4384563657 hasConceptScore W4384563657C179518139 @default.
- W4384563657 hasConceptScore W4384563657C2776401178 @default.
- W4384563657 hasConceptScore W4384563657C31258907 @default.
- W4384563657 hasConceptScore W4384563657C33923547 @default.
- W4384563657 hasConceptScore W4384563657C41008148 @default.
- W4384563657 hasConceptScore W4384563657C41895202 @default.
- W4384563657 hasConceptScore W4384563657C79403827 @default.
- W4384563657 hasConceptScore W4384563657C81860439 @default.
- W4384563657 hasLocation W43845636571 @default.
- W4384563657 hasLocation W43845636572 @default.
- W4384563657 hasOpenAccess W4384563657 @default.
- W4384563657 hasPrimaryLocation W43845636571 @default.
- W4384563657 hasRelatedWork W2091999583 @default.
- W4384563657 hasRelatedWork W2463524724 @default.
- W4384563657 hasRelatedWork W2769489861 @default.
- W4384563657 hasRelatedWork W2802923594 @default.
- W4384563657 hasRelatedWork W2807530277 @default.
- W4384563657 hasRelatedWork W3033136171 @default.
- W4384563657 hasRelatedWork W3134703581 @default.
- W4384563657 hasRelatedWork W3172228157 @default.
- W4384563657 hasRelatedWork W4205275965 @default.
- W4384563657 hasRelatedWork W4385254802 @default.
- W4384563657 hasVolume "174" @default.
- W4384563657 isParatext "false" @default.
- W4384563657 isRetracted "false" @default.
- W4384563657 workType "article" @default.