Data-driven next-generation smart grid towards sustainable energy evolution: techniques and technology review

F Ahsan, NH Dana, SK Sarker, L Li… - … and Control of …, 2023 - ieeexplore.ieee.org
Meteorological changes urge engineering communities to look for sustainable and clean
energy technologies to keep the environment safe by reducing CO 2 emissions. The …

[HTML][HTML] Energy and sustainable development in smart cities: An overview

MGM Almihat, MTE Kahn, K Aboalez, AM Almaktoof - Smart Cities, 2022 - mdpi.com
Smart cities are an innovative concept for managing metropolitan areas to increase their
residents' sustainability and quality of life. This article examines the management and …

[HTML][HTML] The Russia-Ukraine conflict: Its implications for the global food supply chains

S Jagtap, H Trollman, F Trollman, G Garcia-Garcia… - Foods, 2022 - mdpi.com
Food is one of the most traded goods, and the conflict in Ukraine, one of the European
breadbaskets, has triggered a significant additional disruption in the global food supply …

SPOSDS: A smart Polycystic Ovary Syndrome diagnostic system using machine learning

S Tiwari, L Kane, D Koundal, A Jain, A Alhudhaif… - Expert Systems with …, 2022 - Elsevier
Abstract Polycystic Ovary Syndrome (PCOS) is a hormonal disorder that affects a large
percentage of women of reproductive age. PCOS causes imbalanced or delayed menstrual …

Smart cities and urban energy planning: an advanced review of promises and challenges

S Esfandi, S Tayebi, J Byrne, J Taminiau, G Giyahchi… - Smart Cities, 2024 - mdpi.com
This review explores the relationship between urban energy planning and smart city
evolution, addressing three primary questions: How has research on smart cities and urban …

[HTML][HTML] Self-healing in cyber–physical systems using machine learning: A critical analysis of theories and tools

O Johnphill, AS Sadiq, F Al-Obeidat, H Al-Khateeb… - Future Internet, 2023 - mdpi.com
The rapid advancement of networking, computing, sensing, and control systems has
introduced a wide range of cyber threats, including those from new devices deployed during …

Leveraging the power of machine learning and data balancing techniques to evaluate stability in smart grids

Z Allal, HN Noura, O Salman, K Chahine - Engineering Applications of …, 2024 - Elsevier
Modernizing traditional power grids into smart grids represents a significant advancement in
improving efficiency and sustainability within the energy sector. However, integrating …

[HTML][HTML] An online reinforcement learning approach for HVAC control

FM Solinas, A Macii, E Patti, L Bottaccioli - Expert Systems with Applications, 2024 - Elsevier
Abstract Heating, Ventilation and Air Conditioning (HVAC) optimization for energy
consumption reduction is becoming ever more a topic of the utmost environmental and …

A smart gas sensor using machine learning algorithms: sensor types based on IED configurations, fabrication techniques, algorithmic approaches, challenges …

A Nasri, A Boujnah, A Boubaker… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Over the past decade, machine learning (ML) and artificial intelligence (AI) have attracted
great interest in research and various practical applications. Currently, smart, fast, and high …

Intelligent modeling and optimization of solar plant production integration in the smart grid using machine learning models

M Abubakar, Y Che, M Faheem… - Advanced Energy …, 2024 - Wiley Online Library
To address the rising energy demands in industrial and public sectors, integrating zero‐
carbon emission energy sources into the power grid is crucial. Smart grids, equipped with …