Dr. Vikramsingh Ravindrasingh Parihar – Short Profile Vikramsingh R. Parihar is an Assistant Professor in Engineering with 14+ years of teaching experience and extensive research experience. He has published 70+ research papers, with 519 citations, an h-index of 12, and an i10-index of 19 He has authored/edited 12 books, contributed 12 book chapters, holds copyrights and patents, and serves as an editor/reviewer for 30+ journals. His research interests include Artificial Intelligence, Machine Learning, Electrical Engineering, Image Processing, Power Systems, IoT, and Autonomous Systems He has received Best Researcher, Best Reviewer, Best Paper, and Outstanding Scientist Awards and has delivered an invited lecture at an international conference in Bern, Switzerland

Artificial Intelligence-Based Drones: Technologies, Research Landscape, Tools, Applications, and Future Directions Artificial intelligence (AI) is rapidly transforming unmanned aerial vehicles (UAVs) from conventional remotely controlled systems into increasingly intelligent, adaptive, and autonomous aerial platforms. This seminar provides a comprehensive overview of the evolving field of AI-based drones, with emphasis on its technological foundations, research landscape, development tools, software ecosystems, current research trends, applications, challenges, and future directions. The presentation first introduces the evolution of UAV technology and explains how machine learning, deep learning, reinforcement learning, computer vision, sensor fusion, and intelligent optimization are being integrated into drone systemsA structured review of the existing literature will highlight major research themes such as autonomous navigation, perception, object detection and tracking, path planning, swarm intelligence, decision-making, fault detection, energy optimization, and human–drone interaction. The seminar will also discuss commonly used research and development platforms, including Python, MATLAB/Simulink, ROS/ROS 2, PX4, ArduPilot, Gazebo, AirSim, Isaac Sim, OpenCV, TensorFlow, PyTorch, and various UAV simulation environments. Bibliographic and research-analysis tools used for identifying publication trends, influential studies, collaboration networks, and emerging topics will also be introduced Current developments in AI-enabled UAVs will be examined alongside their use across civil, industrial, scientific, environmental, agricultural, healthcare, infrastructure, logistics, security, and disaster-management domains. Key limitations—including computational constraints, energy consumption, communication reliability, explainability, cybersecurity, regulatory issues, data quality, safety, and sim-to-real transfer—will be critically discussed. The seminar concludes by outlining future research opportunities in trustworthy autonomous drones, edge AI, multi-UAV cooperation, foundation models, digital twins, adaptive learning, human–AI collaboration, and next-generation intelligent aerial systems