Chamali Sandamini

Ms. Chamali Sandamini


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 March 2023 in Electronics
Verified
Journal Article
Open access
PDF file
CSChamali Sandamini
Chamali Sandamini
MMMadduma Wellalage Pasan Maduranga
Madduma Wellalage Pasan Maduranga
VALMIK TILWARIVALMIK TILWARI
VALMIK TILWARI
JYJamaiah Yahaya
Jamaiah Yahaya
Faizan QamarFaizan Qamar
Faizan Qamar
SISiti Rohana Ahmad Ibrahim
Siti Rohana Ahmad Ibrahim
The potential of indoor unmanned aerial vehicle (UAV) localization is paramount for diversified applications within large industrial sites, such as hangars, malls, warehouses, production lines, etc. In such real-time applications, autonomous UAV location is required constantly. This paper comprehensively reviews radio signal-based wireless technologies, machine learning (ML) algorithms and ranging techniques that are used for UAV indoor positioning systems. UAV indoor localization typically relies on vision-based techniques coupled with inertial sensing in indoor Global Positioning System (GPS)-denied situations, such as visual odometry or simultaneous localization and mapping employing 2D/3D cameras or laser rangefinders. This work critically reviews the research and systems related to mini-UAV localization in indoor environments. It also provides a guide and technical comparison perspective of different technologies, presenting their main advantages and disadvantages. Finally, it discusses various open issues and highlights future directions for UAV indoor localization.

16 August 2024 in Telecom
Verified
Journal Article
Open access
PDF file
MMMadduma Wellalage Pasan Maduranga
Madduma Wellalage Pasan Maduranga
VALMIK TILWARIVALMIK TILWARI
VALMIK TILWARI
Morksha RathnayakeMorksha Rathnayake
Morksha Rathnayake
CSChamali Sandamini
Chamali Sandamini
The advent of sixth-generation (6G) networks promises revolutionary advancements in wireless communication, marked by unprecedented speeds, ultra-low latency, and ubiquitous connectivity. This research paper delves into the integration of Artificial Intelligence (AI) in 6G network applications, exploring the challenges and outlining future directions for this transformative synergy. The study investigates the key AI technologies for 6G: the potential of AI to optimize network performance, enhance user experience, and enable novel applications in diverse domains and AI-enabled applications. Analyzing the current landscape, the paper identifies key challenges such as scalability, security, and ethical considerations in deploying AI-enabled 6G networks. Moreover, it explores the dynamic interplay between AI and 6G technologies, shedding light on the intricate relationships that underpin their successful integration. The research contributes valuable insights to the ongoing discourse surrounding the convergence of AI and 6G networks, laying the groundwork for a robust and intelligent future communication infrastructure.