Drone-Assisted Network Maintenance as a Revolutionizing Telecom Infrastructure

Alshareefi, Hamid; H. Habib, Bassam; Imetkul Dzhanybaevich, Ismailov; Hashim Qasim, Nameer; Alsaidi, Jamal

doi:10.22034/jipm.2025.728428

Drone-Assisted Network Maintenance as a Revolutionizing Telecom Infrastructure

Document Type : Original Article

Authors

Hamid Alshareefi ¹

Bassam H. Habib ²

Ismailov Imetkul Dzhanybaevich ³

Nameer Hashim Qasim ⁴

Jamal Alsaidi ⁵

¹ Al-Turath University, Baghdad 10013, Iraq

² Al-Mansour University College, Baghdad 10067, Iraq

³ Osh State University, Osh City 723500, Kyrgyzstan

⁴ Al-Rafidain University College Baghdad, Iraq,10064

⁵ Madenat Alelem University College, Baghdad 10006, Iraq

10.22034/jipm.2025.728428

Abstract

ABSTRACT
Background: Telecommunication infrastructure requires regular maintenance and upkeep for its networks’ matrices, but existing approaches have been associated with issues such as time consumption and concern costs, as well as safety hazards. Newer developments in drone technology present progressive opportunity through the improvement of current maintenance processes by means of automation, predictability, and real time computation.
Objective: The article seeks to assess whether the use of drone in telecommunication maintenance enhances the operational productivity through increasing the efficiency, reducing cost, safety, environmental and scalability and in different terrains.
Methods: The methods followed included the conduct of experimental surveys with drone operations in five different telecommunication settings. These areas of interest were inspection efficiency, the accuracy of condition-based maintenance, signal received signal power, delay reduction through edge computing, and energy consumption. Sophisticated numerical computations, like Kalman filters and various frameworks of edge computing, were used in this context to draw analytical insights on the collected data.
Results: The methods that used drones lowered the time needed for inspections by ¾ and cut the expenses by 49.3% and increased safety and quality of the coverage. Predictive maintenance was found to have achieved 89.7% accuracy with the system response time being 246ms at different site. The results of energy consumption model depicted the errors under 2% confirming this approach’s suitability for operational planning.
Conclusion: By evaluating the applicability of drones in telecoms maintenance, the paper shows that the notion of drones in this context is promising both now and in the future. These results signal existing and potential applications of drones is to incorporate drone technology into infrastructural management solutions to address emerging needs in the industry.

Keywords

KEYWORDS: Drones

Telecommunications

Network Maintenance

UAV

Infrastructure

Automated Inspection

Cost Reduction

AI Integration

Predictive Maintenance

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