Energy-Efficient Edge AI for Real-Time Anomaly Detection in IoT-Based Embedded Systems A Reproducible Comparison of Lightweight Detectors on Public Sensor Benchmarks
- DOI
- 10.5281/zenodo.23970573
- Published
- 2026
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- Not recorded
- Publisher
- Zenodo
- Open access
- yes
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BibTeX
@article{allodium:10.5281/zenodo.23970573,
title = {Energy-Efficient Edge AI for Real-Time Anomaly Detection in IoT-Based Embedded Systems A Reproducible Comparison of Lightweight Detectors on Public Sensor Benchmarks},
author = {Debbad, Rachit and Misra, Rishabh},
year = {2026},
doi = {10.5281/zenodo.23970573},
url = {https://doi.org/10.5281/zenodo.23970573}
}RIS
TY - JOUR TI - Energy-Efficient Edge AI for Real-Time Anomaly Detection in IoT-Based Embedded Systems A Reproducible Comparison of Lightweight Detectors on Public Sensor Benchmarks AU - Debbad, Rachit AU - Misra, Rishabh PY - 2026 DO - 10.5281/zenodo.23970573 UR - https://doi.org/10.5281/zenodo.23970573 ER -
APA
Rachit, D., & Rishabh, M. (2026). Energy-Efficient Edge AI for Real-Time Anomaly Detection in IoT-Based Embedded Systems A Reproducible Comparison of Lightweight Detectors on Public Sensor Benchmarks. https://doi.org/10.5281/zenodo.23970573