Search
75 articles for “data fusion”
-
Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
-
Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
-
VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion
Abstract: Road safety for bike riders remains a significant concern, with accident rates highlighting the need for advanced solutions to ensure rider protection and awareness. This paper presents “VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion”, a voice-activated, continuously operating assistance system designed to provide real-time, intelligent solutions for various riding scenarios. VERONICA integrates accident detection, low-traffic route navigation, traction control advisories, and weather updates …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 09–17 Read article
-
Smart City Based Manhole Monitoring System
Abstract: Urban environments are increasingly reliant on complex underground infrastructure networks, with manholes serving as critical access points for maintenance, inspection, and drainage. However, traditional manhole monitoring methods, often manual and labour-intensive, can be inefficient and prone to human error. This can lead to serious safety and health hazards, such as accidents caused by open manholes, exposure to harmful gas leaks, and infrastructure damage from overflows due to undetected blockage This …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 27–34 Read article
-
AI and Machine Learning Approaches for Estimating Depression Severity: Techniques, Trends, and Applications
Abstract: Depression is a very common mental health disorder that results in a disorder of a person’s behavior, emotions, and cognitive abilities. Depression can be caused by environmental factors or hereditary factors. The person suffering from depression might have symptoms of suicidal thoughts, altering food patterns as well as sleeping issues. Depression is a global issue that has impacted millions of people globally having more effect on women worldwide. The complexity …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
-
IoT-Based Structural Health Monitoring and Damage Detection in Fiber Reinforced Polymer Composite Structures
Abstract: Applications of fiber-reinforced polymer (FRP) composite in the aerospace, civil infrastructure and renewable energy systems are increasing due to the fact that the composite possesses high ratio of strength to weight and can resist corrosion. However, processes of internal damages such as the cracking of the matrix, delamination and fiber fracture, are likely to take place without being visible on the surface and therefore a periodic check of the structure …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1076–1100 Read article
-
Enabling Intelligent Interoperability: Advancing Sensor Networks Through the Semantic Sensor Web (SSW)
Abstract: The Semantic Sensor Web (SSW) is an evolution of the traditional Sensor Web, integrating semantic web technologies to enhance the discovery, interpretation, and integration of heterogeneous sensor data. By embedding semantic annotations into sensor observations and metadata, SSW enables automated reasoning, improved interoperability, and more sophisticated querying capabilities across diverse sensor networks. This approach addresses key challenges in handling large-scale, distributed, and dynamic sensor data, particularly in domains such as …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 21–37 Read article
-
Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
-
AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article
-
A Next-Generation IoT-Enabled Smart Cane for the Visually Impaired: Integration of Advanced Navigation, Context-Aware Obstacle Detection, and Real-Time Voice Guidance
Abstract: The rapid growth of Internet of Things (IoT) technologies, combined with advances in embedded systems and artificial intelligence, has opened new possibilities for developing assistive mobility solutions tailored to the needs of individuals with visual impairments. This paper introduces an IoT- enabled smart cane designed to enhance independent mobility through intelligent environmental interpretation and context-aware navigation. Unlike traditional canes that rely solely on tactile feedback, the proposed system incorporates multiple …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 12–17 Read article
-
Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
-
A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
-
Technical Advances in Drone Applications for Environmental Surveillance
Abstract: Unmanned Aerial Vehicles (UAVs), or drones, have rapidly evolved into essential tools for environmental monitoring and conservation due to their advanced sensor integration, real-time data acquisition, and autonomous operational capabilities. This review explores the multidisciplinary convergence of drone technologies with environmental science, emphasizing the technical and engineering aspects that drive these applications. The study outlines key UAV system components—including multispectral and hyperspectral imaging, LiDAR, thermal sensing, and real-time GPS-AI integration—highlighting …
Published in International Journal on Drones · Vol. 1, Issue 2, 2025 · pp. 14–20 Read article
-
Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
-
Design and Implementation of an IoT-Enabled Autonomous Hexapod Robot for Enhanced Navigation and Remote Operations
Abstract: This system develops an autonomous hexapod robot using an ESP32 microcontroller and IoT technology. This robot can move on its own, avoiding obstacles without human help. It's equipped with various sensors like distance and ground slope sensors. These sensors provide data to the microcontroller, helping it control the robot's movements and steer clear of obstacles. The robot runs on a battery, ensuring it can operate for extended periods without human …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
-
Enhancing Space Safety: A Review of CubeSat Constellations for Tracking Orbital Debris
Abstract: Space debris includes any human-made object in orbit or idle. Debris reentering the atmosphere or orbiting the Earth are examples of these things. Debris can include satellites or launch vehicles, dysfunctional spacecraft, remains from rockets and airplanes from crashes or explosions, debris from spacecraft and vehicles that were purposefully expelled during separation or operation, etc. The danger of collisions rises as the number of items in the path increases. Over …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 3, 2024 · pp. 27–43 Read article
-
Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
-
A Review on Integrated Acoustic Emission and Piezoelectric Sensing for Real-Time Damage Characterization of Polymer Composite-Enhanced Concrete: Advances, Challenges, and Future Perspective
Abstract: Polymer composite reinforced concrete has been identified as an efficient material system that can enhance the mechanical properties, durability, and service life of modern structures. The combination of fiber reinforced polymers (FRPs), polymer modifiers, and hybrid composite reinforcements increases structural effectiveness. However, these systems are still vulnerable to damage processes, including matrix cracking, fiber breaking, interfacial debonding, and delamination. Thus, there is a need for structural health monitoring (SHM) strategies …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 930–939 Read article
-
Enhancing Road Safety: A System for Vehicular Accident Detection, Prevention, and Rescue Alerts
Abstract: The Vehicular Accident Detection, Prevention, and Rescue Alert System is a comprehensive solution aimed at bolstering road safety by integrating multiple advanced technologies. It merges drowsiness detection, alcohol level monitoring, and instant emergency alerts to mitigate accidents and expedite rescue efforts. Modern computer vision and machine learning techniques are used by the Drowsiness Detection Alarm to track driver conduct and spot drowsiness indicators. Upon detecting drowsiness, an immediate alarm is …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 7–11 Read article
-
Fusion of deep learning autoencoders with random forest for wetland classification using Sentinel-2A data: A case study on Sirpur wetland
Abstract: Present study analyses the performance of deep leaning algorithm-autoencoder to reduce data dimension as compared to conventional models. Classification accuracies of Sirpur wetland using Sentinel 2A dataset with different inputs have also been studied. These inputs sets comprise the reconstructed data through compression of original 13 bands into 4 bands using decoder algorithm, first four Principal Components, all spectral bands, and spectral indices. Random Forest classifier (RF) is used to …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 25–35 Read article