A survey on scalable LoRaWAN for massive IoT: Recent advances, potentials, and challenges
Long-range (LoRa) technology is most widely used for enabling low-power wide area
networks (WANs) on unlicensed frequency bands. Despite its modest data rates, it provides …
networks (WANs) on unlicensed frequency bands. Despite its modest data rates, it provides …
The applicability of reinforcement learning methods in the development of industry 4.0 applications
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …
problems. Our article gives a systematic overview of major types of RL methods, their …
[HTML][HTML] Distributed artificial intelligence: Taxonomy, review, framework, and reference architecture
Artificial intelligence (AI) research and market have grown rapidly in the last few years, and
this trend is expected to continue with many potential advancements and innovations in this …
this trend is expected to continue with many potential advancements and innovations in this …
Decentralized adaptive spectrum learning in wireless iot networks based on channel quality information
In the Internet of Things (IoT) context such as low power wide area network (LPWAN), it is
essential to reduce the packet losses, eg, to save energy. Decentralized artificial intelligence …
essential to reduce the packet losses, eg, to save energy. Decentralized artificial intelligence …
Combinatorial MAB-Based Joint Channel and Spreading Factor Selection for LoRa Devices
I Urabe, A Li, M Fujisawa, SJ Kim, M Hasegawa - Sensors, 2023 - mdpi.com
Long-Range (LoRa) devices have been deployed in many Internet of Things (IoT)
applications due to their ability to communicate over long distances with low power …
applications due to their ability to communicate over long distances with low power …
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 …
Distributed artificial intelligence: review, taxonomy, framework, and reference architecture
Artificial intelligence (AI) research and market have grown rapidly in the last few years and
this trend is expected to continue with many potential advancements and innovations in this …
this trend is expected to continue with many potential advancements and innovations in this …
Energy-Aware Spreading Factor Selection in LoRaWAN Using Delayed-Feedback Bandits
RE Navas, G Dandachi… - 2023 IFIP Networking …, 2023 - ieeexplore.ieee.org
LoRaWAN networks can involve large numbers of wireless devices relying on batteries to
sense the environment and send data to gateways. A critical trade-off for transmission …
sense the environment and send data to gateways. A critical trade-off for transmission …
A top-down survey on securing IoT with machine learning: goals, recent advances and challenges
The Internet of Things (IoT) has seen it all from being just another innovation to a leading
technology; it is now a binding force that interconnects various aspects of our lives. The IoT's …
technology; it is now a binding force that interconnects various aspects of our lives. The IoT's …
Opportunistic data gathering in IoT networks using an energy-efficient data aggregation mechanism
E Afonso, MEM Campista - Annals of Telecommunications, 2024 - Springer
Abstract Internet of Things (IoT) applications rely on data collection and centralized
processing to assist decision-making. Nevertheless, in multi-hop Low Power and Lossy …
processing to assist decision-making. Nevertheless, in multi-hop Low Power and Lossy …