This chapter explores the integration of IoT and AI technologies to optimize biomass-to-biofuel conversion processes. AI algorithms can be used to optimize process parameters such as temperature, pressure, and enzyme dosage, leading to increased biofuel yields, reduced energy consumption, and improved quality control. Sustainability assessment is also highlighted, with IoT and AI playing a crucial role in monitoring and analyzing sustainability metrics. Companies such as Pacific Ethanol, Renmatix, IOCL, and GranBio have achieved significant improvements in biofuel yield, energy efficiency, quality control, and sustainability by leveraging IoT and AI technologies. These advancements inspire potential applications and strategies in different biomass feedstock scenarios, enabling organizations to drive the transition towards cleaner and more sustainable energy sources while improving operational efficiency and competitiveness.

The chapter explores the transformative role of artificial intelligence (AI) and machine learning (ML) in shaping smart energy management systems (SEMS) and predicts innovations by 2030. It discusses AI principles in energy optimization, predictive analytics in smart grids, and renewable energy integration through AI-driven strategies. The chapter also addresses critical aspects like predictive maintenance, consumer-centric solutions, cybersecurity challenges, ethical considerations, and regulatory frameworks for responsible AI implementation. By examining challenges and prospects, it provides insights into the dynamic future of energy management driven by AI and ML advancements.

The technique of using renewable resources as the source of generating electrical energy leads to the development of sustainable ecosystem. Hybridizing, (combining more than two renewable energy sources) these resources for the efficient generation of energy in power system is rapidly increasing in the present scenario. For this generation of electrical energy, there are certain factors are to be maintained in particular levels. Finding the factors are by going through some predefined algorithms. This paper leads to summarization of Hybrid renewable energy sources (HRES) usage and co-relative study of optimization techniques.

NBA principles and technologies have significantly impacted engineering disciplines, leading to social changes and reshaping industries. NBA-inspired innovations have influenced materials science, data analytics, public health, urban design, and entertainment experiences. The study examines equity, access, and ethical dimensions of NBA-driven engineering innovations, focusing on data privacy, algorithmic bias, and commodification of athlete performance. The goal is to foster inclusivity, equity, and sustainable development, fostering collaboration between the sports industry and engineering disciplines. This approach emphasizes the transformative power of sports-driven innovation in engineering for societal betterment.