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#edge computing Editorial Open access

Guest editorial: Advances in smart and intelligent unmanned systems: innovations, applications and future directions

Sep 2026 · International Journal of Intelligent Unmanned Systems

Abstract

Advances in smart and intelligent unmanned systems: innovations, applications and future directionsThis special issue focuses on state-of-the-art research in intelligent unmanned systems across aerial, marine, and edge computing technologies.The selected manuscripts outline cohesive advancements in autonomous technology -starting with security frameworks and path-planning strategies, integrating these competencies into industrial applications across transportation and construction, progressing to edge-computing models for field intelligence and finally extending the horizon to unmanned maritime applications and usercentric IoT environments.This special issue focused on three thematic clusters:Theme-1: UAV security and navigation 1.A Novel and Secure Approach for Real-Time UAV Video Communication Scope: Formulates a video encryption algorithm to enhance the security of unmanned aerial systems while preventing unauthorised access. Low-Altitude Urban UAV Path Planning Based on Multi-Strategy Mirage Search OptimisationScope: Proposes a path planning strategy for an unmanned aerial vehicle that is operating in complex 3D environments. Theme-2: industrial and field AI applications3. Integration of aerial photogrammetry and machine learning in the railway tracks infrastructure monitoring problem Scope: Automates the inspection of railway tracks using image processing techniques for UAV aerial captures. Aerial Innovation: A Comprehensive Review on Integration of Unmanned Aerial Vehicles in Modern Construction PracticesScope: Synthesises the application of unmanned aerial vehicles and their capabilities into modern construction sectors.5. An Intelligent Edge AI Framework for Real-Time Plant Disease Detection Using Deep Learning Under Complex Field Environments Scope: Deploys an edge-deployed AI method for disease identification in unconstrained agricultural environments.

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