Kuldeep Singh Kulhar

Urbanization’s relentless advance intensifies the quest for sustainable energy sources, with smart cities leading the shift toward sustainability. In these innovative urban landscapes, wind power is pivotal in the clean energy paradigm. Efficient wind energy utilization hinges on accurate wind power forecasting, essential for energy management and grid stability. This review explores the use of neural network models for wind power forecasting in smart cities, driven by wind power’s growing importance in urban energy strategies and the expanding role of artificial neural networks (ANNs) in wind power prediction. Wind power integration mitigates greenhouse gas emissions and enhances energy resilience in urban settings. However, wind’s inherently variable nature necessitates precise forecasting. The surge in ANN use for wind power forecasting is another key driver of this review, as ANNs excel at modelling complex relationships in data. This review highlights the synergy between wind power forecasting and neural network models, emphasizing ANNs’ vital role in enhancing the accuracy of wind power predictions in urban environments. It covers neural network fundamentals, data preprocessing, diverse neural network architectures, and their applicability in short-term and long-term wind power forecasting. It also delves into training, validation methods, performance assessment metrics, challenges, and prospects. As smart cities champion urban sustainability, neural network models for wind power forecasting are poised to revolutionize urban energy systems, making them cleaner, more efficient, and more resilient.

This article focuses on the crucial role of predictive modeling, particularly powered by artificial intelligence (AI), in optimizing power consumption in machining, a vital facet of modern manufacturing. Highlighting the growing significance of power utilization in machining operations due to economic, environmental, and equipment-related implications, the article underscores the importance of this area. It proceeds to discuss the contributions of predictive modelling , elucidating its capacity to predict and manage variability, optimize tool selection and cutting parameters, reduce downtime, enable energy-efficient scheduling, and enhance sustainability, all while reducing costs. AI, with its data-driven capabilities, is presented as a transformative force, providing real-time adaptability, predictive maintenance, and energy-efficient scheduling, aligning with sustainability and cost-efficiency goals. While acknowledging the current limitations of AI models, the article outlines future opportunities such as advanced machine learning, IoT integration, sensor monitoring, digital twins, hybrid models, industry standards, and the growing emphasis on explainable AI. These advancements are poised to shape a more sustainable, efficient, and data-informed future for the manufacturing industry.

Smart cities are pioneering sustainability by integrating renewable energy sources. This review explores the dynamic interplay between renewables, sustainability challenges, and climate solutions in smart cities. Urban populations’ demands for energy efficiency are met by adopting renewables like solar, wind, and hydroelectric power, reducing reliance on fossil fuels and fostering economic growth. Sustainable building materials and green designs are promoted, along with electric vehicles for enhanced mobility and reduced emissions. Challenges include technological adoption, economic constraints, and effective regulation. Despite these, smart cities remain committed to sustainable urban development. The future holds promise with the expansion of renewables, the adoption of circular economy principles, and the prevalence of electric vehicles in urban transit. Emerging technologies like AI and IoT will optimize energy use, provide real-time insights, and enhance governance. Smart cities lead the way towards a more sustainable urban future.

This short review article, titled “Harnessing Nanotechnology and Artificial Intelligence for Precision Agriculture in Smart Cities,” delves into the fusion of nanotechnology, artificial intelligence (AI), and precision farming to drive sustainable agriculture in alignment with the United Nations’ 2030 Sustainable Development Goals. It spotlights the transformative potential of nanotechnology, encompassing both natural and man-made nanoparticles, to enhance crop growth and mitigate environmental impacts. Nano-fertilizers and nano-pesticides are unveiled as promising strategies for optimizing nutrient availability while minimizing harm to ecosystems. The integration of AI into precision farming, supported by cutting-edge nanoinformatics, emerges as a linchpin for the establishment of safe and sustainable agricultural practices, enabling smart and resilient agriculture. However, as this integrated approach accelerates progress and provides vital insights for addressing contemporary agricultural challenges, it also underscores the paramount importance of scrutinizing nanotechnology’s effects on soil microbial communities and plant health. The phytotoxicity of nanoparticles, contingent upon size, concentration, and plant species, necessitates further examination. In conclusion, this comprehensive article calls for interdisciplinary collaboration to fully exploit the potential of nanotechnology and AI in transforming agriculture, all the while ensuring the preservation of environmental and human health and advancing the global sustainability agenda for agriculture in smart cities by 2030.

As the quest for intelligent and eco-friendly urban progress gains momentum, the integration of renewable energy resources within smart city infrastructures becomes increasingly pivotal. This comprehensive review article delves into the confluence of data-driven methodologies and renewable energy solutions within the realm of smart cities. We embark on an exploration of the intricate frameworks devised to enhance the efficiency of renewable energy generation, distribution, and meticulous management in these urban ecosystems. By elucidating the multifaceted strategies and techniques underpinning this synergy, we shed light on the transformative potential it holds for the sustainable and intelligent evolution of our cities, paving the way for a greener and smarter urban future.

This perspective article explores the dynamic landscape of solar energy adoption in developing countries, particularly within the framework of smart cities. Developing nations face a compelling need to bridge the energy gap, reduce emissions, foster economic growth, and enhance energy security. Solar energy offers potential solutions to these challenges. Despite the promise of solar energy, obstacles exist. Financial constraints, outdated infrastructure, grid instability, technical expertise gaps, and regulatory hurdles hinder widespread adoption. However, technological advances in solar panels, energy storage, smart grids, and data analytics present avenues for overcoming these challenges. Collaborative initiatives, consistent policies, and public-private partnerships offer support for sustainable development. Smart cities play a crucial role in this transition. Sustainable urban planning, smart infrastructure, and digitalization contribute to the efficient use of solar power. Case studies from India, Rwanda, and Brazil exemplify successful integration of solar energy within smart city projects. Balancing challenges with opportunities is the key to success. By addressing obstacles and seizing available prospects, developing countries can lead the charge toward a sustainable energy future.

The urgency of sustainable urban development has propelled wind energy and hydropower to the forefront of smart city initiatives. This article explores the strategic integration of wind energy and hydropower in urban settings, emphasizing their potential to mutually reinforce each other. Wind energy, derived from atmospheric kinetic power, and hydropower, generated by the gravitational force of flowing water, offer distinct advantages. When thoughtfully combined, they enhance energy stability, grid reliability, and peak energy demand fulfillment. The primary advantage of this integration lies in the natural synchronicity of wind and hydropower, addressing the intermittent nature of renewable energy sources. This collaboration reduces greenhouse gas emissions, environmental impact, and enhances energy security, economic growth, and urban resilience. Through case studies and innovations, this review underlines the promising future of wind-hydropower integration in smart cities, underscoring the need for continued innovation, policy support, education, awareness, and partnerships. In summary, strategic wind and hydropower integration has the potential to be a cornerstone of smart city development and the global shift to cleaner, more resilient energy sources.

This paper presents a meticulous review of the solar energy markets and their instrumental role in driving the growth of smart cities. Drawing from extensive research, the review delves into urban metamorphoses spurred by the burgeoning growth of megacities, highlighting the significance of sociotechnical systems, evolved institutional practices, and energy material flows. The study identifies seven pivotal models for smart city energy governance, encompassing distributed energy resources, energy storage, microgrids, demand response, smart measuring systems, energy harvesting, and green technological innovations. A comparative analysis of urban developments in cities such as Singapore, Shanghai, and the greater Jakarta area reveals diverse trajectories in energy system evolution and business model shifts. The surging growth of solar energy, underpinned by technological breakthroughs, cost efficiencies, and robust governmental policies, is also explored. Although solar energy has been bolstered by a myriad of fiscal and regulatory incentives, it faces persistent challenges like technical impediments, financial barriers, and regulatory obstacles. The paper also introduces an innovative compound Real Options Approach (ROA) for appraising solar energy projects within smart cities, arguing its efficacy over the traditional Expected Net Present Value methods by recognizing managerial adaptability. In summation, this review accentuates the imperative of enduring policy support to amplify solar energy adoption worldwide, setting the stage for a sustainable smart city future.

In the context of escalating urbanisation and climate change, smart cities emerge as a beacon of sustainable urban development, leveraging cutting-edge technology and data analytics to enhance municipal services and the well-being of residents. This review article, focusing on industrial energy efficiency within smart cities, underscores the pivotal role of these urban environments in mitigating climate change impacts. It highlights the industrial sector’s substantial contribution to global greenhouse gas emissions, driven by energy-intensive processes predominantly fuelled by fossil fuels. The study presents a comparative analysis of emissions across continents, revealing the industrial activities’ significant environmental footprint. It advocates for energy efficiency as a strategic imperative to reduce energy consumption, curb emissions, and foster sustainability. The paper concludes by recommending policy interventions that incentivise eco-friendly industrial practices, endorse the circular use of materials, and promote sustainable economic models. These recommendations are contextualised within Iceland’s CAP 2020 initiative, which aims for a significant reduction in emissions by 2030, underscoring the need for sustainable material management, particularly in metallic ores and fossil fuels, to align with environmental sustainability goals. The article calls for a global collaborative effort, beyond individual national policies, to address the urgent challenges posed by climate change, advocating for international cooperation, investment in renewable energy, and a transition towards a more sustainable future.