Machine Learning Based Localization of LoRa Mobile Wireless Nodes Using a Novel Sectorization Method
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Micael Coutinho & Jose A. Afonso & Sérgio F. Lopes, 2023. "An Efficient Adaptive Data-Link-Layer Architecture for LoRa Networks," Future Internet, MDPI, vol. 15(8), pages 1-16, August.
- Elias Dritsas & Maria Trigka, 2024. "Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey," Future Internet, MDPI, vol. 16(9), pages 1-15, September.
- Alireza Fath & Nicholas Hanna & Yi Liu & Scott Tanch & Tian Xia & Dryver Huston, 2024. "Indoor Infrastructure Maintenance Framework Using Networked Sensors, Robots, and Augmented Reality Human Interface," Future Internet, MDPI, vol. 16(5), pages 1-23, May.
- Imran Moez Khan & Andrew Thompson & Akram Al-Hourani & Kandeepan Sithamparanathan & Wayne S. T. Rowe, 2023. "RSSI and Device Pose Fusion for Fingerprinting-Based Indoor Smartphone Localization Systems," Future Internet, MDPI, vol. 15(6), pages 1-17, June.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Tamai Ramírez-Gordillo & Antonio Maciá-Lillo & Francisco A. Pujol & Nahuel García-D’Urso & Jorge Azorín-López & Higinio Mora, 2025. "Decentralized Identity Management for Internet of Things (IoT) Devices Using IOTA Blockchain Technology," Future Internet, MDPI, vol. 17(1), pages 1-35, January.
More about this item
Keywords
wireless sensor networks; LoRa technology; machine learning; sectorization method; Extended Kalman Filtering (EKF);All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:16:y:2024:i:12:p:450-:d:1535192. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.