Search
170 articles for “AI-Driven Sustainability”
-
AI-Driven Sustainable Supply Chain Framework for Polymer Composite Production
Abstract: As polymer composite processes become more difficult and environmental concerns increase, old supply chain models that just look at cost and operations have shown significant weaknesses when it comes to sustainability. The rising demand for environmentally friendly practices throughout a product’s life cycle requires a new process that makes sustainability a key element in making supply chain choices. The proposed framework was developed in response to this need by using …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 219–235 Read article
-
AI-Driven Robotics for Sustainable Solutions in Disaster Management
Abstract: Disasters, whether natural or man-made, present significant challenges to societies worldwide. Efficient response, recovery, and mitigation strategies are crucial to minimizing human suffering, loss of life, and economic damage. Traditional disaster management strategies, while effective to some degree, often face limitations related to human resources, response time, accessibility, and safety. The integration of artificial intelligence (AI) and robotics into disaster management offers transformative potential for overcoming these challenges. This paper …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
-
AI-Driven Carbon Capture and Utilization: Advancing Sustainable Solutions for Climate Change Mitigation
Abstract: Climate change stands out as one of the biggest challenges for our planet today, as it poses a threat unprecedented to global ecosystems and human societies. This phenomenon is primarily driven by the increase in atmospheric greenhouse gases, particularly carbon dioxide (CO2), which trap heat in the atmosphere and cause rising global temperatures. These sources are largely industrial processes, transportation, and energy production, all of which rely very much on …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 40–48 Read article
-
The Impact of AI-Driven Decision-Making on Consumer Behavior and Sustainable Consumption Patterns in Modern Management
Abstract: The accelerating integration of Artificial Intelligence (AI) into business management systems has fundamentally transformed the dynamics of consumer decision-making and organizational marketing strategies. This paper investigates the multidimensional impact of AI-driven technologies, including predictive analytics, recommendation engines, chatbots, natural language processing, and machine learning algorithms, on consumer behavior and sustainable consumption patterns within contemporary management frameworks. Drawing upon a comprehensive synthesis of empirical studies, theoretical literature, and bibliometric analyses, the …
Published in Journal of Production Research & Management · Vol. 16, Issue 2, 2026 · pp. 12–19 Read article
-
Novel Strategic Framework for AI-Driven Discovery and Development of Smart and Sustainable Polymers in Healthcare
Abstract: The development of new smart and sustainable polymers is emerging as a priority of new health care innovative development, but event before it may be actualized, the usual culprit is the delay and unproductive execution of the old-fashioned R&D efforts. The current paper proposes a strategic plan which will solve all these shortcomings and speed up the material discovery process by using Artificial Intelligence (AI) and Machine Learning (ML). The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1535–1550 Read article
-
AI-Driven Inverse Design of Functionally Graded Bio-Nanocomposites for Sustainable High-Barrier Packaging
Abstract: Multilayer plastic packaging realizes high barrier performance through laminated heterogeneous structures, but the heterogeneous structure has severe end-of-life challenges caused by the interfacial incompatibility of materials and the poor recyclability. This study proposes the inverse design of functionally graded PLA-nanoclay composite films by reinforcement learning as a monolithic alternative to traditional multilayer systems. Twin-screw extrusion is designed as a continuous control Markov decision process, and proximal policy optimization (PPO) is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1547–1564 Read article
-
Green Technology Incubator for Sustainable Manufacturing Solutions
Abstract: The transition to a sustainable, low-carbon economy requires innovative approaches to industrial processes, particularly in the manufacturing sector, which is one of the largest contributors to global environmental degradation. This project proposes the creation of a Green Technology Incubator designed to accelerate the development of sustainable manufacturing solutions by nurturing startups and entrepreneurs focused on green technologies. The incubator's focus will be on promoting circular economy practices, energy-efficient manufacturing processes, …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 22–27 Read article
-
Toward Intelligent Public Transport: Review of Smart Bus Stop Systems with Real-Time Location
Abstract: The increasing demand for efficient, reliable, and sustainable public transportation has driven the evolution of smart bus stop systems worldwide. Traditional bus stops often fail to meet modern commuter expectations, such as real-time service information, accessibility, and integration with smart city frameworks. This review paper provides a comprehensive overview of the technological advancements, design approaches, and global adoption of smart bus stops. Key enabling technologies, including GPS, IoT, wireless communication, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 1–12 Read article
-
Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
-
Artificial Intelligence Enhanced Waste Sorting and Classification System for Urban Recycling
Abstract: This study explores the potential of Artificial Intelligence (AI) and Machine Learning (ML) to enhance waste management efficiency within urban environments. Rapid urbanization has resulted in a surge of municipal waste, which current systems often struggle to manage effectively. The proposed AI-enhanced waste sorting and classification system aims to optimize waste collection routes and accurately forecast waste generation trends, thereby reducing operational costs, fuel consumption, and traffic congestion. Additionally, AI-driven …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 23–32 Read article
-
AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
-
An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
-
AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
-
Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
-
Sustainable Waste Management Using AI and Robotics
Abstract: The fast increment in squander era around the world has driven to noteworthy natural and open wellbeing concerns. Conventional squander administration strategies, which depend intensely on manual labor and obsolete forms, are battling to keep up with the developing volume, driving to wasteful aspects and environmental harm. AI and Mechanical autonomy give inventive arrangements by improving effectiveness in squander collection, sorting, reusing, and transfer. AI-driven squander sorting frameworks optimize exactness, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 42–48 Read article
-
Artificial Intelligence for Sustainable Agriculture, Forestry and Rural Development: Recent Advances, Applications and Research Opportunities
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize agriculture, forestry, and rural development by enabling data-driven decision-making, resource optimization, and sustainable management practices. Rapid developments in computer vision (CV), machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics have increased the use of AI in a variety of rural industries. In agriculture, AI-driven technologies support precision farming, crop yield prediction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
-
AI-Driven IoT Ecosystems for Real-Time Thermo-Chemical Decision Making
Abstract: The efficient management of thermo-chemical processes is a critical challenge in modern industry, where maintaining precision, operational safety, and energy efficiency directly influences productivity and sustainability. The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) has transformed conventional industrial systems into intelligent, data-driven environments capable of continuous monitoring, predictive analysis, and autonomous decision-making. By integrating interconnected sensors, edge computing, cloud platforms, and advanced machine learning algorithms, industries …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 2, 2026 · pp. 10–15 Read article
-
AI-Driven Intelligent Energy Management System for Enhancing Electric Vehicle Efficiency and Range
Abstract: Electric Vehicles (EVs) are crucial in mitigating the emission of greenhouse gases and facilitating sustainable transportation. Their performance is however limited by the capacity of the battery, unpredictable weather conditions and ineffective use of energy. The paper suggests an AI-based Intelligent Energy Management System (IEMS) to increase EV efficiency and driving range. The suggested system combines machine learning (ML), model predictive control (MPC), and real-time data analytics to optimize power …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
-
Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration
Abstract: Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 25–30 Read article
-
Artificial Intelligence for Polymer and Nanocomposite Materials: Performance Prediction, Manufacturing Optimization, and Future Perspectives
Abstract: The exceptional mechanical properties, design flexibility, and lightweight nature of polymer composite and nanocomposite materials make them indispensable in a wide range of applications, including aerospace, automotive, construction, biomedical, and energy sectors. The optimization of the strength, durability, and manufacturing efficiency of polymer composite and nanocomposite materials is highly challenging because their performance depends on matrix composition, reinforcement type, fiber or nanoparticle distribution, interfacial interactions, processing conditions, and environmental factors. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article