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🚀 Our research paper by Patrick McEnroe has been accepted for presentation at the prestigious 2024 IEEE 21st Consumer Communications & Networking Conference (CCNC) in Las Vegas, USA, scheduled for January 2024. 🌟📚 We extend our heartfelt congratulations to Patrick J McEnroe, a dedicated PhD student who has played a pivotal role in shaping this research. 📝 Title: "Revolutionizing UAV Obstacle Avoidance with Edge AI: Towards Faster DRL Training in Complex Environments" 📘 Brief Abstract: In an era where autonomous Unmanned Aerial Vehicles (UAVs) are increasingly integrated into our daily lives, equipping them with robust obstacle-avoidance capabilities is of paramount importance. Edge AI, a paradigm that leverages on-device (e.g., on-UAV) or edge server AI processing, offers numerous advantages over traditional cloud-based AI when addressing the challenge of UAV obstacle avoidance. The literature demonstrates that applying deep reinforcement learning (DRL) to robotics, particularly UAVs, is an effective approach for obstacle avoidance. However, a significant challenge associated with DRL in robotics is the substantial time required for training, especially in complex environments. In response to this challenge, our paper introduces a novel DRL-based UAV obstacle avoidance system empowered by edge AI. Our innovative system tackles this issue by breaking down large and intricate environments into smaller, manageable segments, effectively distributing the training and inferencing processes of DRL. Our primary objective is to accelerate DRL training, making it more feasible and efficient within relatively large and complex environments. We are thrilled to report that our system's effectiveness has been validated through 3D simulations. Furthermore, we are proud to announce that all of our code is open-sourced on GitHub, fostering collaboration and advancements in this critical area of research. 🌐 For those eager to delve deeper into the details of our research, you can access the full paper using the following link: https://lnkd.in/dBvDtgMC #IEEE #CCNC2024 #EdgeAI #UAVObstacleAvoidance #DeepReinforcementLearning #Research #AcademicExcellence #OpenSource #Collaboration #netslab #ucd #connect #sfi #mllabs @ML-labs CONNECT Centre Science Foundation Ireland University College Dublin UCD School of Computer Science with Shen Wang

✨ AI Copilot Enhances Human Precision for Safer Aviation The Air-Guardian system, developed by MIT CSAIL, enhances aviation safety by creating a symbiotic partnership between human pilots and AI. It uses eye-tracking for humans and saliency maps for AI to understand where attention is focused, allowing early risk identification. Air-Guardian's adaptability and differentiability make it suitable for various situations, ensuring a balanced collaboration between humans and machines. Field tests showed reduced flight risks and increased navigation success rates, indicating its effectiveness. The technology's foundational components include optimization-based cooperative layers and VisualBackProp algorithms for attention mapping. Refinements are needed for the human-machine interface to make the system's control more intuitive. Air-Guardian represents a step towards safer aviation by combining human expertise and machine learning, offering earlier interventions and enhancing trust between humans and AI. This AI copilot system not only benefits aviation but also suggests potential applications in other fields like cars, drones, and robotics. https://lnkd.in/eSNf46cZ

Drones are taking machine learning to new heights! 🚀 The integration of machine learning in drone technology is revolutionizing the way we collect and analyze data. By leveraging algorithms that improve with experience, drones can now autonomously navigate complex environments, making them invaluable for tasks like agricultural monitoring, search and rescue operations, and infrastructure inspection. These smart drones adapt to changing conditions in real-time, ensuring more efficient and accurate data collection. What's particularly exciting is the application of convolutional neural networks, a class of deep learning models that are exceptionally good at processing visual information. This allows drones to recognize objects and patterns from images captured during flight, enabling them to make instant decisions based on visual data. The synergy between drones and machine learning is not just enhancing the capabilities of these flying marvels but is also opening up a myriad of possibilities across various industries. Consider checking out MLNOW.ai if you're learning this stuff, and follow me for more! #machinelearning #ai #datascience

Imagine a future where humans and machines collaborate seamlessly in the cockpit, ensuring safer skies for all. This is where the Air-Guardian, a groundbreaking system developed by MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) Science and Artificial Intelligence Laboratory, comes in. Air-Guardian is more than just 🤖 autopilot; it's a proactive copilot, working in harmony with 👨✈️ human pilots to reduce operational errors and enhance aviation precision. How does it work? Using 👁️ eye-tracking for humans and "saliency maps" for the neural system, Air-Guardian monitors where attention is focused. It identifies potential risks early, making aviation ✈️ safer by design, not just during emergencies. This innovation extends beyond aviation. Imagine similar systems in 🚗 cars, 🚁 drones, and 🤖 other robotics, revolutionizing safety across industries. Air-Guardian is adaptable and can be trained to meet the demands of various situations, ensuring a 🔄 balanced partnership between humans and machines. Field tests have shown that it reduces risk levels and increases navigation success rates 📊, ultimately improving aviation safety. The true strength of Air-Guardian lies in its foundational technology, using cutting-edge neural networks 🧠 and visual attention 👩💻 metrics to provide a safety net for moments when human attention wavers. Join us in welcoming a new era of aviation safety with Air-Guardian, where human expertise and machine learning work hand in hand. 🤝 Want to read more? Visit 👇 https://lnkd.in/eZz29j66 #MIT #ArtificialIntelligence #AI #Technology #Innovation Massachusetts Institute of Technology

Harnessing the Power of AI for Safer Skies: The Rise of Air-Guardian ✈️ Picture this: both the human pilot and the AI system, monitoring the skies and the aircraft's parameters. The human leads, but if they falter, Air-Guardian swiftly steps in, guaranteeing precision and safety. The magic lies in attention mapping. Air-Guardian employs eye-tracking for humans and "saliency maps" for its neural system. Unlike traditional autopilots that intervene only in emergencies, this system proactively identifies potential risks, ensuring timely interventions. Beyond aviation, imagine its transformative potential across automobiles, drones, and advanced robotics! Dr. Lianhao Yin from MIT CSAIL emphasizes its adaptability, "Air-Guardian isn’t rigid; it adjusts to situation demands, ensuring a harmonious human-machine partnership." Real-world tests have been promising: with both the human pilot and AI system navigating based on identical raw images, Air-Guardian has notably reduced flight risks. Ramin Hasani, from MIT CSAIL, highlights, "Our innovative approach ensures the AI complements, not replaces, human judgment, fostering enhanced collaboration in the skies." As we stand at the dawn of a new era, where human expertise synergizes with machine learning, Air-Guardian epitomizes the pinnacle of safe and efficient aviation. Hats off to the brilliant minds at MIT CSAIL for pioneering this! Here's to safer, AI-enhanced skies. 🌟🛫 https://lnkd.in/g3ueV3qM #AI #aviation #AirGuardian #saferskies #MITCSAIL #futuretech #aviationinnovation

Understanding #Swarm Intelligence in #AI What is swarm intelligence in AI? It is a technique miming insect colonies’ collective behaviour, like ants and bees, in solving complex optimisation problems using AI development services. This method has made significant progress in various fields, including healthcare analytics, where it has been used to detect medical conditions such as blood cancer, lung diseases, and COVID-19. AI swarm intelligence is also increasingly popular in data science, where it helps manage and analyse vast data sets, providing solutions to optimisation problems while ensuring flexibility and scalability. Swarm Intelligence in Deep Learning Swarm intelligence has also contributed to advancements in deep learning, a subset of machine learning, by fostering collaboration among agents within an AI system. This has led to enhanced learning capabilities and problem-solving skills, opening the door to future AI innovations. Swarm Intelligence Application AI swarm intelligence is not limited to static data problems. It is also suitable for real-time dynamic environments such as unmanned aerial vehicle systems. Swarm intelligence’s adaptability and decentralised decision-making make it ideal for the complex tasks and uncertain operational environments of UAVs. AI swarm intelligence is a promising field that applies the principles of natural swarm behaviour to solve problems that require quick, adaptive, and robust solutions across various disciplines. https://lnkd.in/ePGG9ZAH #consultants #artificialintelligence #decisionmaking #bigdata #DataScience #web3 #machinelearning #future #technology #cloud #DataAnalytics #LinkedIn #innovation #Business #Sales #creativity #Swarmai

✈️ 🤖 Air-Guardian: AI Elevates Aviation Safety MIT's Air-Guardian is changing the game in aviation. This innovative system acts as a co-pilot, understanding pilot attention through eye-tracking and "saliency maps". It identifies risks early, ensuring safer skies. Beyond aviation, it has broader applications in robotics. Read the full article here 👇 https://lnkd.in/eZz29j66 Follow Silver Brain AI AG today for the latest breakthroughs and latest trends in the world of GenAI 🚀 #AI #AviationSafety #Innovation

MIT researchers have developed Air-Guardian, a human-machine cooperative system for aviation, using eye-tracking and saliency maps to improve attention management and safety in flight, with potential applications in cars and robotics. Read on 👇 #mit #aviation #aicopilot #tracking #research #researchers #safety #artificialintelligence #aviationindustry #efficiency #applications

#ArtificialIntelligence takes over the sky 🛩 As modern #pilots grapple with an overwhelming amount of informations from multiple monitors, the #AirGuardian takes on the role of a proactive copilot. Developed by researchers at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) this system can determine attention with the help of #EyeTracking and #SaliencyMaps. That way, #AirGuardian can identify early signs of potential risks and step in if the pilot gets distracted or is not able to command the plane anymore. This foundational #technology doesn't merely replace human judgement but complements it which could have broad implications on other #machines in the future, such as cars or drones. Read more about it here: https://lnkd.in/eZz29j66 #aviation #robotics #data #ComputerScience #MachineLearning #algorithms #HumanComputerInteraction #research #MIT #RoboticAutomation #adaptability"