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11 articles for “AI-driven autonomy”
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Next-generation Operating Systems: AI-driven Autonomy, Quantum Integration, and Edge Computing
Abstract: The rapid evolution of computing paradigms is driving the need for next-generation operating systems that seamlessly integrate artificial intelligence, quantum computing, and edge processing. Traditional operating systems, while efficient for classical computation, lack the necessary capabilities to handle real-time AI-driven decision-making, quantum processing, and decentralized edge networks. This study explores how future operating systems will incorporate AI-driven autonomy to enhance resource management, quantum integration to leverage superior computational power, and …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 25–36 Read article
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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
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The Impact of AI-Driven Real-Time Feedback Systems on Students’ Self-Regulated Learning and Academic Persistence in Secondary Schools, Nigeria
Abstract: Self-regulated learning (SRL) is essential for secondary school students to achieve academic success and lifelong learning competencies, particularly in contexts requiring greater learner autonomy. This expository article examines the potential of Artificial Intelligence (AI)-driven real-time feedback systems to support SRL processes—planning (forethought), monitoring (performance/control), and reflection—within Nigerian secondary education. Grounded in Zimmerman’s cyclical SRL model and Bandura’s Social Cognitive Theory, the paper conceptualises AI tools (e.g., intelligent tutoring systems, learning …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 Read article
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Adaptive Machine Learning Framework for Navigation Control of Autonomous Drones
Abstract: The rise of autonomous drones has expanded UAV applications across sectors like surveillance, delivery, agriculture, and rescue operations. However, traditional navigation systems face limitations in adapting to dynamic environments. This study proposes an AI-driven adaptive navigation framework that leverages real-time sensor data, reinforcement learning, and adaptive control strategies to enhance drone autonomy, scalability, and security. The system processes mission inputs, environmental data (from LiDAR, cameras, GPS, and weather sensors), and …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 1–7 Read article
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Ethical Considerations in AI-Driven Rehabilitation Robotics: Balancing Innovation and Responsibility
Abstract: Artificial intelligence (AI) is transforming robotics rehabilitation by introducing advanced capabilities such as adaptive therapy, real-time feedback, and personalized assistance, significantly improving outcomes for individuals with neurological and physical impairments. These AI-powered systems offer high levels of precision and consistency in therapy delivery, making them especially beneficial in pediatric and adult rehabilitation settings where engagement and tailored interventions are crucial. However, the integration of AI in healthcare also presents critical …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 24–29 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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A Review Paper of Automated Driving & ADAS Technologies
Abstract: Automated driving and Advanced Driver Assistance Systems (ADAS) are transforming road mobility, promising enhanced safety, improved traffic efficiency, and greater accessibility. This review presents a comprehensive synthesis of core technologies, system architectures, sensor modalities, perception and decision-making algorithms, and evaluation methodologies underpinning contemporary ADAS and automated driving. We provide a detailed discussion of the functional components—sensors (camera, radar, LiDAR, ultrasonic), localization, perception, prediction, planning, control, and human–machine interfaces—and how these …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–7 Read article
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Trends, Challenges, and the Future of Unmanned Aerial Systems
Abstract: The rapid evolution of unmanned aerial vehicles (UAVs), commonly referred to as drones, has transformed numerous domains — from military surveillance and logistics to precision agriculture and atmospheric research. This paper examines the current state of drone technology, industry trends, regulatory frameworks, socio-economic impacts, ethical considerations, and future research directions. With contributions from multidisciplinary studies, this review emphasizes emerging technologies, performance metrics, risk factors, and opportunities for innovation. In recent …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 27–33 Read article
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Evolution of Kinematic and Dynamic Design in Robotic Mechanisms: A Systematic Overview
Abstract: The field of robotics has experienced significant advancements in both kinematic and dynamic design, driven by the growing need for precision, adaptability, and autonomy in mechanical systems. Early robotic mechanisms were predominantly rigid and operated based on simple serial architectures, offering limited degrees of freedom and relying heavily on analytical formulations for motion planning and control. Over time, the demand for greater dexterity and operational versatility led to the development …
Published in Trends in Machine design · Vol. 12, Issue 2, 2025 · pp. 38–43 Read article
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Neural Implants & Brain–Computer Interfaces: Enhancing Human Intelligence or Violating Free Will?
Abstract: The integration of neural implants with artificial intelligence creates opportunities to develop new implants and enhance current nanotechnologies. Although these advances hold significant potential for restoring neurological functions, they also introduce important ethical concerns. The rapid advancements in neural implants and brain–computer interfaces [BCIs] are revolutionizing human cognition, enabling enhanced intelligence, communication, and even thought-driven control of external devices. Although these technologies offer great promise in enhancing human abilities, they …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 13–18 Read article
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AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article