Inam Ul Haq

Generative AI-driven frameworks are transforming the forecasting and optimization of wind energy systems by overcoming the limitations of traditional statistical and deterministic models that struggle with the nonlinear and variable nature of wind resources. By leveraging advanced models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models, these frameworks facilitate the creation of synthetic data, enhance scenario simulation, and enable robust probabilistic forecasting, significantly reducing uncertainty and improving operational resilience. Integrating generative AI with optimization algorithms and digital twin architectures supports intelligent turbine placement, adaptive energy dispatch, and predictive maintenance, thereby increasing energy yield, reliability, and economic viability. This approach enables real-time decision support, rapid scenario analysis, and improved grid integration, accelerating the transition toward sustainable energy systems.

Quantum computing and AI could change biomedical engineering by enabling smart biomedical applications. Quantum computing and artificial intelligence for smart biological applications are thoroughly explained in this chapter. Combining quantum computing with AI promotes personalised healthcare, disease diagnosis, and medication discovery. The authors begin with a hardware and software review of both systems before discussing AI and quantum computing. Quantum computing and AI in personalised healthcare are then considered. The authors discuss quantum computing and AI-powered telemedicine, precision medicine, and smart wearable and medical devices. They also note that reliable qubit technologies, effective error-correction methods, and scalable quantum computing and AI architectures are needed to fully exploit quantum computing and AI for smart biomedical applications. In conclusion, quantum computing and AI could revolutionise biomedical engineering and enable intelligent biomedical applications that improve patient outcomes. Request access from your librarian to read this chapter's full text.

Wireless sensor networks are the self-configuring varieties of networks whereby the sensor nodes are put in such a way that they can join or leave the network whenever they wish. Due to the decentralized nature of this type of network, it is possible for many malicious nodes to join the network. Attacks of both the active and passive variety may occur as a result of the presence of such malicious nodes. The term “DDoS form of attack” refers to an attack where a flood of raw packets is sent to the victim node. It's a much more active type of attack. The DDoS attack reduces the network's lifespan and increases its energy consumption when it occurs inside the network. Therefore, a novel technique is going to be suggested in this research effort to find the malicious nodes from the community that are responsible for the DDoS attack.