Author(s)

Xue Lu¹, JiZhe Zhang^2*

Affiliation(s)

¹Foreign Languages College, Kashi University, Kashgar 844000, Xinjiang, China.

²College of Artificial Intelligence and Computer Science, Northwest Normal University, Lanzhou 730070, Gansu, China.

Corresponding Author

JiZhe Zhang

ABSTRACT

Smart classrooms continuously generate large volumes of visual data that enable educational big data analytics, including learner-state assessment and classroom activity understanding. In practice, however, bandwidth-constrained and noise-impaired wireless links render conventional compress-then-transmit pipelines inefficient: pixel-fidelity-oriented compression typically requires high transmission rates to sustain downstream recognition performance. This paper studies a task-oriented semantic communication framework for image analytics over additive white Gaussian noise (AWGN) channels. We develop a unified multi-SNR, multi-rate training and evaluation protocol and benchmark a learned semantic link against a conventional DCT-based link under matched rate budgets. The proposed semantic link integrates (i) an encoder that extracts task-relevant latent representations, (ii) a rate-controllable channel-selection bottleneck that regulates the transmitted feature budget, and (iii) a decoder that reconstructs images for a fixed downstream classifier. Using CIFAR-10 as a reproducible testbed, we report task performance alongside perceptual quality metrics across a grid of SNR and rate settings. Experimental results indicate that the semantic link consistently sustains higher classification accuracy in low-to-medium SNR and low-rate regimes. In addition, PSNR/SSIM do not necessarily exceed the DCT baseline, revealing a task-perception mismatch that favors task-driven transmission. Overall, the proposed framework offers a practical methodology for designing communication pipelines that better support educational big data image analytics.

KEYWORDS

Educational big data; Smart classroom; Semantic communication; Image classification

CITE THIS PAPER

Xue Lu, JiZhe Zhang. Task-oriented semantic communication for smart classroom image analytics. Journal of Computer Science and Electrical Engineering. 2026, 8(1): 11-17. DOI: https://doi.org/10.61784/jcsee3112.

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