Title: Study on regional digital teaching resource sharing platform based on internet of things and big data

Authors: Xiaohong Zhu

Addresses: Modern Service and Management Department, Cangzhou Technical College, Cangzhou 061001, Hebei, China

Abstract: In order to overcome the problems of low upload rate and poor data integrity of traditional teaching resource sharing platforms, the paper proposes a regional digital teaching resource sharing platform based on the internet of things and big data. The least square algorithm to construct the operation and maintenance elastic model is introduced, and the dual residual and the original residual of the model output data are calculated. The platform adopts the WebAPI framework, including the design of user login service, teacher resource information service, teaching information service, and online recommendation service for sharing teaching information. The experimental results show that the platform designed in this paper has a higher transmission rate, which has been maintained above 4G/s with the increase of time. In the state of network interruption, the platform's return matrix data status detection shows that the storage data of the platform in this paper does not appear abnormal.

Keywords: internet of things; big data; ADMM algorithm; operation and maintenance elasticity; dual function; Lagrange function.

DOI: 10.1504/IJISE.2023.132771

International Journal of Industrial and Systems Engineering, 2023 Vol.44 No.4, pp.458 - 474

Received: 27 Jul 2021
Accepted: 17 Sep 2021
Published online: 09 Aug 2023 *

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