Deep Learning and Artificial Intelligence in Sustainability: A Review of SDGs, Renewable Energy, and Environmental Health

Sustainability, Journal Year: 2023, Volume and Issue: 15(18), P. 13493 - 13493

Published: Sept. 8, 2023

Artificial intelligence (AI) and deep learning (DL) have shown tremendous potential in driving sustainability across various sectors. This paper reviews recent advancements AI DL explores their applications achieving sustainable development goals (SDGs), renewable energy, environmental health, smart building energy management. has the to contribute 134 of 169 targets all SDGs, but rapid these technologies necessitates comprehensive regulatory oversight ensure transparency, safety, ethical standards. In sector, been effectively utilized optimizing management, fault detection, power grid stability. They also demonstrated promise enhancing waste management predictive analysis photovoltaic plants. field integration facilitated complex spatial data, improving exposure modeling disease prediction. However, challenges such as explainability transparency models, scalability high dimensionality with next-generation wireless networks, ethics privacy concerns need be addressed. Future research should focus on developing scalable algorithms for processing large datasets, exploring addressing considerations. Additionally, efficiency models is crucial use technologies. By fostering responsible innovative use, can significantly a more future.

Language: Английский

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Smart waste management: A paradigm shift enabled by artificial intelligence

Waste Management Bulletin, Journal Year: 2024, Volume and Issue: 2(2), P. 244 - 263

Published: May 9, 2024

Waste management poses a pressing global challenge, necessitating innovative solutions for resource optimization and sustainability. Traditional practices often prove insufficient in addressing the escalating volume of waste its environmental impact. However, advent Artificial Intelligence (AI) technologies offers promising avenues tackling complexities systems. This review provides comprehensive examination AI's role management, encompassing collection, sorting, recycling, monitoring. It delineates potential benefits challenges associated with each application while emphasizing imperative improved data quality, privacy measures, cost-effectiveness, ethical considerations. Furthermore, future prospects AI integration Internet Things (IoT), advancements machine learning, importance collaborative frameworks policy initiatives were discussed. In conclusion, holds significant promise enhancing practices, such as concerns, cost implications is paramount. Through concerted efforts ongoing research endeavors, transformative can be fully harnessed to drive sustainable efficient practices.

Language: Английский

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Harnessing Artificial Intelligence

Advances in finance, accounting, and economics book series, Journal Year: 2024, Volume and Issue: unknown, P. 89 - 117

Published: April 5, 2024

Science increasingly acknowledges technology's environmental impact. Artificial intelligence has the greatest transformational potential. This study uses AI to provide sustainable, eco-friendly solutions. The report covers climate change, pollution, and resource depletion worldwide. These difficulties inspire chapter suggests using invent Numerous case studies demonstrate how may help sustainability. Waste management, energy efficiency, biodiversity natural catastrophe prediction are examples. Each explores principles, problems, In next section, discusses AI's ethical practical implications. concerns include data privacy, inclusion, automation-related job loss. It provides well-defined legal frameworks integration with other tech societal finishes future in sustainable development. Governments, developers, public must collaborate achieve

Language: Английский

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How to efficient and high-value recycling of electronic components mounted on waste printed circuit boards: Recent progress, challenge, and future perspectives

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 415, P. 137815 - 137815

Published: June 15, 2023

Language: Английский

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The Role of 6G Technologies in Advancing Smart City Applications: Opportunities and Challenges

Sustainability, Journal Year: 2024, Volume and Issue: 16(16), P. 7039 - 7039

Published: Aug. 16, 2024

The deployment of fifth-generation (5G) wireless networks has already laid the ground-work for futuristic smart cities but along with this, it also triggered rapid growth a wide range applications, example, Internet Everything (IoE), online gaming, extended/virtual reality (XR/VR), telemedicine, cloud computing, and others, which require ultra-low latency, ubiquitous coverage, higher data rates, extreme device density, ultra-high capacity, energy efficiency, better reliability. Moreover, predicted explosive surge in mobile traffic until 2030 envisioned potential use-cases/scenarios city context will far exceed capabilities 5G was designed. Therefore, there is need to harness 6th Generation (6G) capabilities, not only meet stringent requirements megacities can open up new applications. Other crucial concerns that be addressed are related network security, privacy, interoperability, digital divide, other integration issues. In this article, we examine current emerging trends implementation 6G arena. Firstly, give an inclusive comprehensive review communication technologies find use cities. discussion each technology covers its benefits, challenges future research direction. Secondly, explore promising applications these technologies, such as, grids, healthcare, waste management, etc. conclusion part, have highlighted suggestions possible directions. So, single paper, attempted provide wider perspective on 6G-enabled by including both their This paper help readers gain holistic view ascertain opportunities bring diverse, massive

Language: Английский

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Assessing sustainable waste management practices in Rajshahi City Corporation: an analysis for local government enhancement using IoT, AI, and Android technology

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: April 6, 2024

Language: Английский

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Analyzing mixed construction and demolition waste in material recovery facilities: Evolution, challenges, and applications of computer vision and deep learning

Resources Conservation and Recycling, Journal Year: 2025, Volume and Issue: 217, P. 108218 - 108218

Published: Feb. 28, 2025

Language: Английский

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IoT-Based Automated Dust Bins and Improved Waste Optimization Techniques for Smart City

Advances in environmental engineering and green technologies book series, Journal Year: 2024, Volume and Issue: unknown, P. 167 - 194

Published: May 29, 2024

Effective waste management systems are essential for maintaining sustainability, environmental health, and cleanliness in the age of smart cities. This chapter provides a thorough analysis combination cutting-edge minimization techniques with deployment an internet things-based automatic dust bin. The suggested system optimizes garbage collection, lowers operating costs, has less effect by combining creative use proximity sensors, real-time data analytics, bin technologies. Remote monitoring administration made possible linked ecosystem that is created integration things (IoT). In order to further promote environmentally friendly urban life, study also examines waste-to-energy technology, circular economy ideas, sustainable techniques. results provide insightful information scholars, decision-makers, planners looking ground-breaking solutions today's

Language: Английский

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Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 19(24), P. 16798 - 16798

Published: Dec. 14, 2022

The immense growth of the population generates a polluted environment that must be managed to ensure environmental sustainability, versatility and efficiency in our everyday lives. Particularly, municipality is unable cope with increase garbage, many urban areas are becoming increasingly difficult manage. advancement technology allows researchers transmit data from municipal bins using smart IoT (Internet Things) devices. These bin can contribute compelling analysis waste management instead depending on historical dataset. Thus, this study proposes forecasting models comprising 1D CNN (Convolutional Neural Networks) long short-term memory (LSTM), gated recurrent units (GRU) bidirectional (Bi-LSTM) for time series prediction public bins. execution evaluated by Mean Absolute Error (MAE), Percentage (MAPE), Coefficient determination (R2) Root Squared (RMSE). For different numbers epochs, hidden layers, dense RSME values measured CNN, LSTM, GRU Bi-LSTM 1.12, 1.57, 1.69 1.54, respectively. best MAPE value 1.855, which found LSTM model. Therefore, findings indicate used emptiness or fullness improved planning due its proven resilience increased forecast accuracy.

Language: Английский

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Employing Technological Innovation for Eco-Friendly Waste Disposal at a Global Scale

Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 135 - 152

Published: Jan. 16, 2025

In the current era of heightened environmental consciousness, addressing issue waste disposal demands innovative solutions through cutting-edge technologies. This chapter explores pivotal role Artificial Intelligence (AI), Geographic Information System (GIS) with Global Positioning System(GPS) integration in establishing eco-friendly management strategies. AI excels tackling ambiguous issues practical exposure and predictive modelling using artificial neural networks, genetic algorithms, expert systems, fuzzy logic. GPS-GIS facilitates real-time spatial analysis for monitoring patterns, identifying illegal dumping site selection. Through synergistic application technologies, study elucidates a paradigm shift towards sustainable practices developing circular economy paving way greener future.

Language: Английский

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