Publications
Journal Articles¶
Jaradat, A., Alarbi, M., Haque, A., & Lutfiyya, H. (2024).
HYDROSAFE: A Hybrid Deterministic-Probabilistic Model for Synthetic Appliance Profiles Generation.
Sensors, 24(17), 5619.
https://doi.org/10.3390/s24175619
Alarbi, M., Jaradat, A., Lutfiyya, H., & Haque, A. (2023).
SCOPE: Smart Cooperative Parking Environment.
IEEE Access, 11, 120346–120361.
https://doi.org/10.1109/ACCESS.2023.3324374
Jaradat, A., Lutfiyya, H., & Haque, A. (2022).
Smart Home Energy Visualizer: A Fusion of Data Analytics and Information Visualization.
IEEE Canadian Journal of Electrical and Computer Engineering, 45(1), 77–87.
https://doi.org/10.1109/CJECE.2022.3148333
Conference Proceedings¶
Alarbi, M., Jaradat, A., Haque, A., & Lutfiyya, H. (2025).
Intent-Aware Task Chain Scheduling Across the Cloud-Edge Continuum: An Agentic AI Approach.
Submitted to the 21st International Conference on Network and Service Management (CNSM).
Jaradat, A., Alarbi, M., Lutfiyya, H., & Haque, A. (2024, February).
Synthetic Power Consumption Data Generation for Appliance Operation Modes.
In Proceedings of the 2024 International Conference on Computing, Networking and Communications (ICNC) (pp. 689–694). IEEE.
Jaradat, A., Alarbi, M., Lutfiyya, H., & Haque, A. (2023, July).
Appliances Operation Modes Identification Using States Clustering.
In Proceedings of the International Conference on Smart Applications, Communications and Networking (SmartNets) (pp. 1–6). IEEE.
Jaradat, A., Lutfiyya, H., & Haque, A. (2023, March).
Density and Dynamic Time Warping Based Spatial Clustering for Appliance Operation Modes.
In Proceedings of the IEEE PES Conference on Innovative Smart Grid Technologies – Middle East (ISGT-ME) (pp. 1–5). IEEE.
Jaradat, A., Lutfiyya, H., & Haque, A. (2020, June).
Demand Response for Residential Uses: A Data Analytics Approach.
In Proceedings of the IEEE 6th World Forum on Internet of Things (WF-IoT) (pp. 1–6). IEEE.
Preprints¶
Jaradat, A., Lutfiyya, H., & Haque, A. (2021).
Appliance Operation Modes Identification Using Cycles Clustering.
arXiv preprint arXiv:2101.10472.
https://arxiv.org/abs/2101.10472