AUAV Tech Inc.’s Post

Great to see this amazing technology, Emesent, being integrated into an American made drone, Freefly Systems. We, as contractors, need to see more of this as federal jobs do not allow for the use of Chinese made drones. #americanmade #drones #lidar #lidartechnology #constructiontechnology #dronetechnology #dronesforgood #generalcontractor #dronemapping #dronesurvey #technologyinnovation #technology

📣 Exciting Updates! 📣 We're proud to share that our Auterion operating system allows manufacturers like Freefly Systems to build BlueUAS certified systems like Astro Prime, powered by AuterionOS! AuterionOS ensures a cyber-secure, interoperable, and NDAA-compliant system, empowering drone manufacturers like Freefly to deliver top-notch, blue-certified systems. The latest AuterionOS update also enhances support for the Sony ILX-LR1, optimizing performance, video recording, and streaming quality, ensuring top-notch image quality for industrial UAV applications. Read the blog post to learn more about these updates: https://hubs.ly/Q02H6w3F0

The authors developed a low cost system for detecting and classifying consumer drones. Abstract The proliferation of #drones, or unmanned aerial vehicles (#UAVs), has raised significant safety concerns due to their potential misuse in activities such as espionage, smuggling, and infrastructure disruption. This paper addresses the critical need for effective drone detection and classification systems that operate independently of UAV cooperation. We evaluate various convolutional neural networks (#CNNs) for their ability to detect and classify drones using spectrogram data derived from consecutive Fourier transforms of signal components. The focus is on model robustness in low signal-to-noise ratio (SNR) environments, which is critical for real-world applications. A comprehensive dataset is provided to support future model development. In addition, we demonstrate a low-cost drone detection system using a standard computer, software-defined radio (SDR) and antenna, validated through real-world field testing. On our development dataset, all models consistently achieved an average balanced classification accuracy of >= 85% at SNR > -12dB. In the field test, these models achieved an average balance accuracy of > 80%, depending on transmitter distance and antenna direction. Our contributions include: a publicly available dataset for model development, a comparative analysis of CNN for drone detection under low SNR conditions, and the deployment and field evaluation of a practical, low-cost detection system.

Learn how a recent collaboration between Exyn Technologies and Dundee Precious Metals Inc. shows how drone technology can improve safety, efficiency, and accuracy in cave monitoring and mapping operations. https://lnkd.in/gBfGvpjz #drones #uav #uas #uncrewed #dronemapping #mining #cavemonitoring #goldmining #coppermining #minesafety

This development integrates the high efficiency, ease of operation, and accuracy of WingtraOne GEN II #drones with an advanced #LIDAR sensor engineered by @Wingtra https://lnkd.in/eJtjA7S9

This development integrates the high efficiency, ease of operation, and accuracy of WingtraOne GEN II #drones with an advanced #LIDAR sensor engineered by @Wingtra https://lnkd.in/eiwc3tFg

#Dronesensors, from #LiDAR to thermal and beyond, are revolutionizing industries by expanding the capabilities of unmanned aerial vehicles. With advancements in diverse sensor technologies, drones are now equipped to tackle tasks ranging from environmental research to industrial inspections, heralding a new era of #innovation and problem-solving. #RDive #DroneTechnology #DroneSensors #UAV #LiDAR #ThermalSensors #Multispectral #Hyperspectral #GasSensors #ChemicalSensors #ObstacleAvoidance #GPS #NavigationSystems #CameraSensors #Innovation #Technology #EnvironmentalMonitoring #IndustrialInspections https://lnkd.in/eK_BEw5U

Publication Alert =========== Drones and UAVs play multiple roles as task-execution enablers. Discover these and more in our new book release, "Application of Machine Learning in UAV N Networks." The chapter contribution is Chapter 9: Machine Learning in UAV-Assisted Smart Farming Further details can be accessed via: https://lnkd.in/g3j2rSYU

Nice endorsement of UAV LiDAR potential -- Minimum average absolute differences of 1.1 cm, 1 cm, and 0.7 cm were recorded for all profiles (from 1 m left to 1 m right of the road centerline) in the comparisons between UAV drone – RST, UAV drone – RLL, and RST – RLL methods, respectively.

UAV-based remote sensing for the petroleum industry and environmental monitoring: State-of-the-art and perspectives Common platforms/sensors and application examples are reviewed and highlighted. • Six broad areas are recognized for drone remote sensing in the petroleum industry. • The UAV technology increases the data collection agility, resolution, and efficiency. An unmanned aerial vehicle (UAV), popularly known as a drone, is an aircraft without a human pilot aboard. Recent developments in sensor technology and navigation systems have made drones a powerful and reliable basis for professional data acquisition. Today, the use of UAVs has expanded massively in the civil and commercial sectors and this technology has found its way into almost every industrial sector including the petroleum industry. Drone technology offers great potential to revolutionize the mapping, monitoring, inspection, and surveillance procedures of the petroleum industry by providing a faster, safer, and more cost-efficient way of mass data collection. This article offers a review of the common UAV platforms and sensor systems and highlights the state-of-the-art and application examples of drone remote sensing in the oil and gas industry. Six broad areas are recognized comprising offshore oil spill detection, oil leakage detection, pipeline monitoring, gas emission sensing, remote facility inspection, petroleum exploration (i.e., land surveying, geologic mapping, and petroleum exploration), and environmental monitoring. Research gaps and open issues along with opportunities for further developments in each of these areas are highlighted.