Machine Learning-Based Beehive State Classification from IoT Sensor Data: A Comparative Analysis of Decision Tree, Random Forest and Logistic Regression under Edge–Cloud Deployment Constraints
- DOI
- 10.5281/zenodo.22949527
- Published
- 2026
- Container
- Not recorded
- Publisher
- Zenodo
- Open access
- yes
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BibTeX
@article{allodium:10.5281/zenodo.22949527,
title = {Machine Learning-Based Beehive State Classification from IoT Sensor Data: A Comparative Analysis of Decision Tree, Random Forest and Logistic Regression under Edge–Cloud Deployment Constraints},
author = {León Huanca, Ricardo Jonathan and Del Carpio Zuñiga, Mihaly Mizrahim and Tiznado Ubillus, José Armando and Lascano Rivera, Samuel},
year = {2026},
doi = {10.5281/zenodo.22949527},
url = {https://doi.org/10.5281/zenodo.22949527}
}RIS
TY - JOUR TI - Machine Learning-Based Beehive State Classification from IoT Sensor Data: A Comparative Analysis of Decision Tree, Random Forest and Logistic Regression under Edge–Cloud Deployment Constraints AU - León Huanca, Ricardo Jonathan AU - Del Carpio Zuñiga, Mihaly Mizrahim AU - Tiznado Ubillus, José Armando AU - Lascano Rivera, Samuel PY - 2026 DO - 10.5281/zenodo.22949527 UR - https://doi.org/10.5281/zenodo.22949527 ER -
APA
Jonathan, L. H. R., Mizrahim, D. C. Z. M., Armando, T. U. J., & Samuel, L. R. (2026). Machine Learning-Based Beehive State Classification from IoT Sensor Data: A Comparative Analysis of Decision Tree, Random Forest and Logistic Regression under Edge–Cloud Deployment Constraints. https://doi.org/10.5281/zenodo.22949527