Lorawan meets ml: A survey on enhancing performance with machine learning
The Internet of Things is rapidly growing with the demand for low-power, long-range
wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one …
wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one …
A Systematic Review of LPWAN and Short-Range Network using AI to Enhance Internet of Things
MH Widianto, A Sinaga, MA Ginting - Journal of Robotics and …, 2022 - journal.umy.ac.id
Artificial intelligence (AI) has recently been used frequently, especially concerning the
Internet of Things (IoT). However, IoT devices cannot work alone, assisted by Low Power …
Internet of Things (IoT). However, IoT devices cannot work alone, assisted by Low Power …
[图书][B] Machine Learning: Master Supervised and Unsupervised Learning Algorithms with Real Examples (English Edition)
Concepts of Machine Learning with Practical Approaches. KEY FEATURES● Includes real-
scenario examples to explain the working of Machine Learning algorithms.● Includes …
scenario examples to explain the working of Machine Learning algorithms.● Includes …
Optimizing energy efficiency of LoRaWAN-based wireless underground sensor networks: A multi-agent reinforcement learning approach
Extended battery lifetime is always desirable for wireless underground sensor networks
(WUSNs). The recent integration of LoRaWAN-grade massive machine-type …
(WUSNs). The recent integration of LoRaWAN-grade massive machine-type …
Reinforcement learning approach for SF allocation in LoRa network
LoRa technology is widely used to build wireless networks in various Internet of Things (IoT)
applications. As the increased popularity of IoT, LoRa also gains tremendous attention in …
applications. As the increased popularity of IoT, LoRa also gains tremendous attention in …
Performance analysis of MAC protocols for single-cell LoRa network with power control
In this letter, a new framework is developed for the analysis of the coverage probability and
energy efficiency of the single-cell uplink LoRa network with power control leveraging pure …
energy efficiency of the single-cell uplink LoRa network with power control leveraging pure …
A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN
A Li, I Urabe, M Fujisawa, S Hasegawa… - arXiv preprint arXiv …, 2022 - arxiv.org
The number of IoT devices is predicted to reach 125 billion by 2023. The growth of IoT
devices will intensify the collisions between devices, degrading communication …
devices will intensify the collisions between devices, degrading communication …
Adaptive wireless network management with multi-agent reinforcement learning
Wireless networks are trending towards large scale systems, containing thousands of nodes,
with multiple co-existing applications. Congestion is an inevitable consequence of this scale …
with multiple co-existing applications. Congestion is an inevitable consequence of this scale …
A comparative study of machine learning models for spreading factor selection in LoRa networks
Low power wide area networks (LPWAN) technologies offer reasonably priced connectivity
to a large number of low-power devices spread over great geographical ranges. Long range …
to a large number of low-power devices spread over great geographical ranges. Long range …
A lightweight, fully-distributed AI framework for energy-efficient resource allocation in LoRa networks
As the Internet of Things (IoT) continues to grow rapidly, efficient resource utilization is
crucial for the sustainability and performance of IoT networks. In this context, LoRa …
crucial for the sustainability and performance of IoT networks. In this context, LoRa …