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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Samuel Johnson

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Review Open access 2022

Trends in Sustainable Energy Storage for Urban Infrastructures

It is the result of the increased urbanization levels and the simultaneous development of the metropolitan infrastructures that have resulted in the unprecedented growth of global energy demands. The current cities consume over 75 percent of the total energy being produced globally leading to the critical challenges related to peak-load management, grid resilience, carbon emissions, and integration of renewable energies. Green technologies of energy storage have become the key facilitators of dealing with these issues in order to enable effective capture, storage, and redistribution of energy. The paper will critically review the neo trends in sustainable energy storage of urban infrastructures with an analysis of electrochemical, mechanical, thermal, and hybrid energy storage models. The paper also assesses how smart grids, urban microgrids and decentralized energy networks can help increase resilience levels to energy at the urban level. In the review, there is a lot of literature to map the development of storage technologies, and method frameworks are built to analyze the performance, lifecycle viability, and integration capability. On the one hand, experimental outcomes and comparative modeling demonstrate the differences in the performances of different technologies in relation to energy density, environmental impact, expenses, and scalability. Based on the analysis, it is shown that, although the use of lithium-ion batteries will remain in the short-term storage, the long-term storage will be characterized by flow batteries, compressed-air energy storage (CAES), hydrogen storage, and thermal batteries, which are expected to dominate in the future city-scale application. It is shown in a multi-criteria analysis that hybrid storage architectures are the best to use with smart urban grids. The paper wraps up by giving the main policy considerations, technical challenges, and gaps in research, which should be resolved to achieve fully sustainable, scalable, and smart energy storage ecosystems in new urban city settings of the next generations.

Grace Ndlovu, Samuel Johnson · 0 citations
Open access 2025

Agent-Based Machine Learning Frameworks for Autonomous Predictive Decision Systems

Artificial Intelligence (AI), Machine Learning (ML), and autonomous intelligent systems are transforming predictive decision-making across industries such as manufacturing, healthcare, finance, transportation, cybersecurity, and smart cities. Traditional centralized machine learning models often struggle to adapt to dynamic and uncertain environments. This paper proposes an Agent-Based Machine Learning Framework for Autonomous Predictive Decision Systems (ABML-APDS) that integrates distributed intelligent agents, collaborative learning, reinforcement learning, predictive analytics, and explainable AI into a unified architecture. The framework enables autonomous agents to collect data, engineer features, exchange knowledge, optimize predictions, and continuously improve decision-making with minimal human intervention. It incorporates explainable decision mechanisms to enhance transparency, trust, and interpretability while supporting supervised, unsupervised, deep, and reinforcement learning models. Continuous learning and decentralized agent collaboration improve adaptability, scalability, fault tolerance, computational efficiency, and real-time responsiveness. The proposed framework provides an intelligent and scalable foundation for next-generation autonomous predictive systems supporting Industry 5.0, cyber-physical systems, IoT, smart manufacturing, precision healthcare, and AI-driven digital transformation.

Grace Ndlovu, Samuel Johnson · 0 citations
Open access 2023

Digital Mental Health Apps: Effectiveness and Limitations

Stronger regulations, improved design, and better clinical validation are recommended to enhance digital mental health applications effectiveness, and the most effective approach is a hybrid model combining digital tools with professional care.

Grace Ndlovu, Samuel Johnson · 0 citations

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