@inproceedings{b50490feb15d4f2dba5e2f586ef81f24,
title = "Optimization of LoRa for Distributed Environments Based on Machine Learning",
abstract = "In the rapidly evolving Internet of Things (IoT) field, wireless communication technologies have revolutionized industries by connecting smart devices for extensive data sharing and automation. However, distributed wireless communication systems often face limited signal coverage and high maintenance costs. This paper introduces optimization techniques based on machine learning in a distributed environment, aiming to design a low-power and long-range LoRa network for indoor and outdoor IoT applications. The orthogonal combinations of transmission parameters and the K-means approach effectively address the avalanche effects and maximize the throughput of its data collision avoidance algorithm (ALOHA protocol) for improving the network's overall performance.",
keywords = "ALOHA, distributed IoT, K-means, LoRa",
author = "Khan, \{Malak Abid Ali\} and Luo Senlin and Hongbin Ma and Shaikh, \{Abdul Khalique\} and Ahlam Almusharraf and Mirani, \{Imran Khan\}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2024 ; Conference date: 28-11-2024 Through 30-11-2024",
year = "2024",
doi = "10.1109/APWiMob64015.2024.10792952",
language = "English",
series = "Proceedings of 2024 IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "137--142",
booktitle = "Proceedings of 2024 IEEE Asia Pacific Conference on Wireless and Mobile, APWiMob 2024",
address = "United States",
}