Artificial Intelligence-Driven Framework for Decentralized Multi-Drone Network Coordination

International Journal of Electrical and Electronics Engineering

© 2026 by SSRG - IJEEE Journal

Volume 13 Issue 2

Year of Publication : 2026

Authors : T. Meena, Mong-Fong Horng, Siva Shankar S, Chun-Chih Lo

10.14445/23488379/IJEEE-V13I2P105

How to Cite?

T. Meena, Mong-Fong Horng, Siva Shankar S, Chun-Chih Lo, "Artificial Intelligence-Driven Framework for Decentralized Multi-Drone Network Coordination," SSRG International Journal of Electrical and Electronics Engineering, vol. 13,  no. 2, pp. 71-82, 2026. Crossref, https://doi.org/10.14445/23488379/IJEEE-V13I2P105

Abstract:

The drone in a swarm acts as a primitive agent, and is a part of an advanced networking, which produces cooperative or group behaviors. To achieve this property, a drone swarm will generally be self-organized or centrally managed. Multi-rotor drones should not be used in large-scale aerial mapping, long-endurance monitoring, and long-distance inspection of pipelines, highways, and electricity lines because they have low endurance and speed. To be able to disobey gravity and keep on flying, they require a lot of power, which makes them fundamentally extremely inefficient. Thus, an AI-based multi-drone network coordination, which is decentralized, was proposed in this research. Multi-UAV Benchmark Data Collection. In the first stage, Multi-UAV Benchmark Data has been collected to have Artificial Intelligence used in the coordination of a network of multiple drones on a decentralized network.

Keywords:

Adaptive Weighted Kalman Filter, Optimizing, Environmental Monitoring, Flying Ad-hoc Networks.

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