Dynamic carbon emissions optimization method for HIES based on cloud-edge collaborative CBAM-BiLSTM-PSO network

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 2, 2025

To achieve the low carbon optimization in hydrogen-based integrated energy system(HIES), this paper proposes a dynamic emissions method for HIES based on cloud-edge collaborative CBAM-BiLSTM-PSO network. Firstly, theory of emission flow, are converted from source to multiple load nodes, and reduction model is established. The coordinated achieved by setting edge objective function at cloud function. And noise sources correlate relationship between input variables decision variables, uncertainty embedding achieved. Then, computing network established prediction new power output multi-energy consuming as well scheduling plan solving. Convolutional block attention module (CBAM) used strengthen key feature data fuse heterogeneous data. particle swarm algorithm (PSO) combined with bidirectional long short-term memory (BiLSTM) form solving algorithm, which realizes solution plan. Finally, proposed was validated using actual running an example. results showed that can effectively extract operating characteristics equipment within HIES, reduction, reduce HIES. Compared other models, training time shortened accuracy improved, providing feasible data-based low-carbon operation

Language: Английский

Human-Centered Digital Twins in IoT

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 189 - 210

Published: May 2, 2025

The integration of Human-Centered Digital Twins (HCDTs) and the Internet Things (IoT) is revolutionizing industries by allowing personalized, real-time decision-making through use continuous data streams. These systems utilize IoT sensors AI-driven models to produce digital copies individuals, environments, or systems, providing improved predictive capabilities in healthcare, smart cities, industrial applications. increasing HCDTs sparks significant ethical issues, such as privacy, confidentiality, discriminatory practices, consent based on complete information. A gap persists research, particularly establishment uniform frameworks implementation dependable AI that safeguard user autonomy while optimising advantages twins. purpose this investigation investigate consequences personalization suggest a framework for reconciling data-driven with privacy cybersecurity environments.

Language: Английский

A Comprehensive Analysis of Privacy-Preserving Solutions Developed for IoT-Based Systems and Applications

Electronics, Journal Year: 2025, Volume and Issue: 14(11), P. 2106 - 2106

Published: May 22, 2025

In recent years, a large number of Internet Things (IoT)-based products, solutions, and services have emerged from the industry to enter marketplace, improving quality service. With wide adoption IoT-based systems/applications in real scenarios, privacy preservation (PP) topic has garnered significant attention both academia industry; as result, many PP solutions been developed, tailored systems/applications. This paper provides an in-depth analysis state-of-the-art (SOTA) recently developed for systems applications. We delve into SOTA methods that preserve IoT data categorize them two scenarios: on-device cloud computing. existing privacy-by-design (PbD), such federated learning (FL) split (SL), engineering (PESs), differential (DP) anonymization, we map IoT-driven applications/systems. further summarize latest employ multiple techniques like ϵ-DP + anonymization or blockchain FL (rather than employing just one) PES PbD categories. Lastly, highlight quantum-based devised enhance security and/or real-world scenarios. discuss status current research within scope established this paper, along with opportunities development. To best our knowledge, is first work comprehensive knowledge about topics centered on IoT, which can provide solid foundation future research.

Language: Английский