ArticleSensors (Basel, Switzerland)2018
An RFID Indoor Positioning Algorithm Based on Support Vector Regression.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Two-stage RFID approach for localizing objects in smart homes based on gradient boosted decision trees with under- and over-sampling.Journal of reliable intelligent environments · 2023Article
- Multiple Fingerprinting Localization by an Artificial Neural Network.Sensors (Basel, Switzerland) · 2022Article
- Design and Implementation of an Indoor Warning System with Physiological Signal Monitoring for People Isolated at Home.Sensors (Basel, Switzerland) · 2022Article
- An Improved Bluetooth Indoor Positioning Method Using Dynamic Fingerprint Window.Sensors (Basel, Switzerland) · 2020Article
- Real-Time Locating System in Production Management.Sensors (Basel, Switzerland) · 2020Article
- Magnetic Field Gradient-Based EKF for Velocity Estimation in Indoor Navigation.Sensors (Basel, Switzerland) · 2020Article
- Indoor Large-Scale MIMO-Based RSSI Localization with Low-Complexity RFID Infrastructure.Sensors (Basel, Switzerland) · 2020Article
- A Review of IoT Sensing Applications and Challenges Using RFID and Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2020Review
- Intelligent Management of Chemical Warehouses with RFID Systems.Sensors (Basel, Switzerland) · 2019Article
- A Meta-Review of Indoor Positioning Systems.Sensors (Basel, Switzerland) · 2019Review
- Evaluating the Implications of Varying Bluetooth Low Energy (BLE) Transmission Power Levels on Wireless Indoor Localization Accuracy and Precision.Sensors (Basel, Switzerland) · 2019Article
- ANTspin: Efficient Absolute Localization Method of RFID Tags via Spinning Antenna.Sensors (Basel, Switzerland) · 2019Article
- Mobile User Indoor-Outdoor Detection Through Physical Daily Activities.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nowadays, location-based services, which include services to identify the location of a person or an object, have many uses in social life. Though traditional GPS positioning can provide high quality positioning services in outdoor environments, due to the shielding of buildings and the interference of indoor environments, researchers and enterprises have paid more attention to how to perform high precision indoor positioning. There are many indoor positioning technologies, such as WiFi, Bluetooth, UWB and RFID. RFID positioning technology is favored by researchers because of its lower cost and higher accuracy. One of the methods that is applied to indoor positioning is the LANDMARC algorithm, which uses RFID tags and readers to implement an Indoor Positioning System (IPS). However, the accuracy of the LANDMARC positioning algorithm relies on the density of reference tags and the performance of RFID readers. In this paper, we introduce the weighted path length and support vector regression algorithm to improve the positioning precision of LANDMARC. The results show that the proposed algorithm is effective.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.