A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems by Devinder Kaur (264278)

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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System by Ameema Zainab (16864263)

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Next-generation energy systems for sustainable smart cities: Roles of transfer learning by Yassine Himeur (14158821)

“…However, training machine learning algorithms to perform various energy-related tasks in sustainable smart cities is a challenging data science task. …”

Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects by Mohamed Massaoudi (16888710)

“…Further, we taxonomically delve into the mechanism behind some of the trending DL algorithms. We then showcase the DL enabling technologies in SG, such as federated learning, edge intelligence, and distributed computing. …”

Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters by Sakib Mahmud (15302404)

“…In this study, we introduce the multimodal feature fusion for non-intrusive occupancy monitoring (MMF-NIOM) framework, which leverages both classical and deep machine learning algorithms to achieve state-of-the-art occupancy detection performance using smart meter data. …”

Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review by Mohamed Sadok Massaoudi (17984071)

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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

“…Statistical analysis and machine learning can play a vital role in detecting the anomalies in the data, which enhances the security level of the smart home IoT system which is the goal of this paper. …”

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring by Muhammad E.H. Chowdhury (17151154)

IoT-Based Sustainable Parking Lot by Binmahfooz, Abdullah

“…This paper aims to eliminate the loophole that unregistered vehicles abuse to avoid fines and park illegally by devolving an IoT-based smart parking access control system. The proposed system utilizes a single-board computer with a set of sensors, cameras and actuators. …”
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Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices by Aya Hasan Alkhereibi (17151070)

“…This study aims to classify the highest 50 global smart cities based on key livability and technology indices, using advanced <u>machine learning</u> (ML) models to assess city performance comprehensively. …”

A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation by Kfouri, Ronald

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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices by Neder Karmous (19743430)

“…This SDN-ML-IoT uses a Machine Learning (ML) method in a Software-Defined Networking (SDN) environment in order to protect smart home IoT devices from DDoS attacks. …”