Research Article
Fast Integration System of English Online Learning Resources Based on Multi Sensor Network
@INPROCEEDINGS{10.1007/978-3-030-94182-6_5, author={Hai-yun Han and Bing-bing Han}, title={Fast Integration System of English Online Learning Resources Based on Multi Sensor Network}, proceedings={IoT and Big Data Technologies for Health Care. Second EAI International Conference, IoTCare 2021, Virtual Event, October 18-19, 2021, Proceedings, Part II}, proceedings_a={IOTCARE PART 2}, year={2022}, month={6}, keywords={Multi sensor network English Online learning Resource integration}, doi={10.1007/978-3-030-94182-6_5} }- Hai-yun Han
Bing-bing Han
Year: 2022
Fast Integration System of English Online Learning Resources Based on Multi Sensor Network
IOTCARE PART 2
Springer
DOI: 10.1007/978-3-030-94182-6_5
Abstract
Common English online learning resources rapid integration system, resulting in the system in the traffic load gradually increases, there is a throughput reduction phenomenon, can not meet the needs of users, this paper proposes a multi-sensor network based English online learning resources rapid integration system. In terms of hardware, the browser/server architecture and client/server architecture are combined to configure the hardware architecture of the system; according to the way of multi-sensor network collecting English online learning resources, the multi-sensor network structure is determined, and the hardware design of the system is completed. In terms of software, based on OAIS and multi-sensor network, the overall structure of English online learning resource integration system is designed; according to the three steps of resource collection and submission, resource storage and management, resource release and service, the system function module is designed to complete the system software design. Design the test environment and system performance test interface, experimental results: after the traffic load increases, the designed system has no obvious change compared with the two groups of commonly used system throughput, low loss rate and false detection rate, and high integration efficiency.
