Optimizing UAV Path for Disaster Management in Smart Cities Using Metaheuristic Algorithms

Nature-inspired optimization approaches play a vital role in fostering smart cities by adopting natural system efficiency. These approaches, which are founded on phenomena in biology, ecology, and physical science, optimize resource use, energy and transportation systems. They offer new possibilities for intelligent cities to mimic naturally occurring processes, which may lead to sustainable development. Besides renown for resilience, they possess high problem-solving capabilities that are critical in addressing in-city unforeseen challenges. The most recent publications explore opportunities for using such methods to optimize energy grids, traffic flows, waste recycling, and resources in smart cities. By combining AIML techniques with these algorithms, researchers are developing more powerful and adaptive models to address the evolving needs of modern urban environments. This study presents an overview of these innovative approaches in shaping the future of smart cities and promoting sustainability, efficiency, and resilience in urban infrastructure and services.

show abstract

Optimizing UAV Path for Disaster Management in Smart Cities Using Metaheuristic Algorithms

Cited by 3 publications

References 43 publications

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

Optimized Real Time Single-Drone Path Planning for Harvesting Information from a Wireless Sensor Network

An Overview of Nature-Inspired Optimization Techniques for Smart Cities

Contact Info

Product

Resources

About