OSMAN, Magdah; ELGHAFFI, Fatma; BEN DALLA, Llahm; KARAL, Ömer; RASHID, Tarik. A New Approach for Low-Latency, High-Accuracy Anomaly Detection at the Edge: Benchmarking Quantized Autoencoders, LSTMs, and Lightweight Transformers on RT-IoT2022 Time-Series Traffic. Wadi Alshatti University Journal of Pure and Applied Sciences, Libya, v. 4, n. 1, p. 110–121, 2026. DOI: 10.63318/waujpasv4i1_12. Disponível em: https://waujpas.com/index.php/journal/article/view/300.. Acesso em: 30 jan. 2026.