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--- emrp:ws2025:amt [2026/02/26 21:31] – 37554_students.hsrw
+++ emrp:ws2025:amt [2026/02/28 21:17] (current) – 36502_students.hsrw
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 Future work plans include improving model performance with larger datasets, evaluating different communication technologies, and transforming the system into a fully portable edge-cloud architecture. Furthermore, hardware optimization and detailed power profile analysis can further improve battery life. In conclusion, the developed system offers a scalable and modular solution for IoT applications requiring low power consumption and real-time motion detection.
-===== 6. References =====
+===== 6. References & Sources =====
 European Telecommunications Standards Institute (ETSI). 2018. “Short Range Devices (SRD) operating in the frequency range 25 MHz to 1 000 MHz; Part 2: Harmonised Standard for access to radio spectrum for non specific radio equipment”. Visited: 09.02.2026. Available at: https://www.etsi.org/deliver/etsi_en/300200_300299/30022002/03.02.01_60/en_30022002v030201p.pdf
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 Ioffe, S., & Szegedy, C. (2015). Batch normalization: Accelerating deep network training by reducing internal covariate shift. Proceedings of the 32nd International Conference on Machine Learning (ICML), 448–456. https://proceedings.mlr.press/v37/ioffe15.html
+Project Repository: https://github.com/bytarikesen81/EMRP