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3 articles for “Bio-hybrid UAVs”
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Olfactory Intelligence in Bio-Hybrid UAVs: Integrating Living Lepidoptera Sensors for High-Precision Environmental Monitoring
Abstract: Autonomous aerial systems still face major challenges when attempting to locate airborne volatile organic compounds because many conventional gas sensors react slowly and cannot reliably follow turbulent chemical plumes. To address this limitation, a bio-hybrid sensing approach was explored using the antenna of the silkworm moth, Bombyx mori, as a natural chemical detector. The antenna was connected to an Electroantennogram (EAG) system that converts biological nerve signals into digital signals …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 2, 2026 Read article
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An Integrated Autonomous Rover-Drone System for Intelligent Exploration and Environmental Monitoring
Abstract: This paper presents a hybrid autonomous exploration platform integrating a ground rover and aerial drone, enhanced by swarm intelligence and a custom-trained YOLO V8 object detection model. The rover is equipped with GPS, IMU, and environmental sensors (DHT11, MQ135, BMP180), while the drone performs real-time aerial mapping and obstacle prediction. A YOLO V8 model, trained on 500 annotated terrain images (six classes: rocks, pits, trees, water, animals, vegetation), achieves a …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 43–61 Read article
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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