Deep Learning Applications in the Resilience Critical Infrastructure Systems—A Systematic Review DOI Creative Commons

H L Gururaj

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Янв. 31, 2025

Abstract Technological advancements like AI, blockchain, and IoT are merging to bring about a new level of digital change. Critical infrastructure systems (CISs) vital modern society, as they support crucial social functions, economic organization, national defense. Recently, the resilience CISs has garnered attention in academic policy fields, particularly light increased natural technological disasters. However, assessing CIS remains challenging, its practical application operational risk management. Integrating advanced technologies with critical (CI) can significantly enhance quality life boost productivity. Nevertheless, lack robust cybersecurity CI given rise threats vulnerabilities, undermining these potential benefits. The paper explores cyber vulnerabilities dangers various structures, including financial, agricultural, energy, health systems. Moreover, we examine positive aspects artificial intelligence provide rich taxonomy solutions that show how well AI-based approaches deal different types cyberattacks on infrastructure.

Язык: Английский

Advanced Deep Learning Algorithms for Energy Optimization of Smart Cities DOI Creative Commons
Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas

и другие.

Energies, Год журнала: 2025, Номер 18(2), С. 407 - 407

Опубликована: Янв. 18, 2025

Advanced deep learning algorithms play a key role in optimizing energy usage smart cities, leveraging massive datasets to increase efficiency and sustainability. These analyze real-time data from sensors IoT devices predict demand, enabling dynamic load balancing reducing waste. Reinforcement models optimize power distribution by historical patterns adapting changes real time. Convolutional neural networks (CNNs) recurrent (RNNs) facilitate detailed analysis of spatial temporal better usage. Generative adversarial (GANs) are used simulate scenarios, supporting strategic planning anomaly detection. Federated ensures privacy-preserving sharing distributed systems, promoting collaboration without compromising security. technologies driving the transformation towards sustainable energy-efficient urban environments, meeting growing demands modern cities. However, there is view that if pace development maintained with large amounts data, computational/energy costs may exceed benefits. The article aims conduct comparative assess potential this group technologies, taking into account efficiency.

Язык: Английский

Процитировано

2
Deep Learning Applications in the Resilience Critical Infrastructure Systems—A Systematic Review DOI Creative Commons

H L Gururaj

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Янв. 31, 2025

Abstract Technological advancements like AI, blockchain, and IoT are merging to bring about a new level of digital change. Critical infrastructure systems (CISs) vital modern society, as they support crucial social functions, economic organization, national defense. Recently, the resilience CISs has garnered attention in academic policy fields, particularly light increased natural technological disasters. However, assessing CIS remains challenging, its practical application operational risk management. Integrating advanced technologies with critical (CI) can significantly enhance quality life boost productivity. Nevertheless, lack robust cybersecurity CI given rise threats vulnerabilities, undermining these potential benefits. The paper explores cyber vulnerabilities dangers various structures, including financial, agricultural, energy, health systems. Moreover, we examine positive aspects artificial intelligence provide rich taxonomy solutions that show how well AI-based approaches deal different types cyberattacks on infrastructure.

Язык: Английский

Процитировано

0