R2NA: Received Signal Strength (RSS) Ratio-Based Node Authentication for Body Area Network [PDF]
Sensors, 2013 The body area network (BAN) is an emerging branch of wireless sensor networks for personalized applications. The services in BAN usually have a high requirement on security, especially for the medical diagnosis.
Yang Wu +3 more
doaj +7 more sources
Forecast-Driven Enhancement of Received Signal Strength (RSS)-Based Localization Systems [PDF]
ISPRS International Journal of Geo-Information, 2013 Real-time user localization in indoor environments is an important issue in ambient assisted living (AAL). In this context, localization based on received signal strength (RSS) has received considerable interest in the recent literature, due to its low ...
Claudio Gallicchio +3 more
doaj +6 more sources
Impact of Mobile Received Signal Strength (RSS) on Roaming and Non-roaming Mobile Subscribers. [PDF]
Wirel Pers Commun, 2023 Mobile phones have transitioned from voice-centric devices to smart devices supporting functionalities like high-definition video and games, web browsers, radio reception, and video conferencing. Mobile phones are used in telemedicine, health monitoring applications, navigation tools, and gaming devices, among other applications.
Karanja HS, Misra S, Atayero AAA.
europepmc +3 more sources
An Unsupervised Indoor Localization Method Based on Received Signal Strength (RSS) Measurements [PDF]
2015 IEEE Global Communications Conference (GLOBECOM), 2014 We propose an unsupervised, received signal strength (RSS)- based indoor localization method, which as an infrastructure uses commercial WiFi chipsets and does not require any changes in the existing hardware. The method relies on path loss model for measured RSS levels where path loss coefficient is treated as a discrete random variable which takes ...
Milutin Pajovic +5 more
openaire +2 more sources
Received-Signal-Strength (RSS) Based 3D Visible-Light-Positioning (VLP) System Using Kernel Ridge Regression Machine Learning Algorithm With Sigmoid Function Data Preprocessing Method [PDF]
IEEE Access, 2020 In this work, we propose and demonstrate a received-signal-strength (RSS) based visible-light-positioning (VLP) system using sigmoid function data preprocessing (SFDP) method; and apply it to two types of regression based machine learning algorithms; including the second-order linear regression machine learning (LRML) algorithm, and the kernel ridge ...
Yu-Chun Wu +7 more
openaire +3 more sources
Optical Fiber Communication Conference (OFC) 2022, 2022 We propose and demonstrate a received-signal-strength (RSS) pre-processing scheme to mitigate light-deficient-region occurred in visible-light-positioning (VLP) and convolutional-neural-network (CNN) to enhance VLP performance. The RSS pre-processing and CNN model are discussed.
Li-Sheng Hsu +7 more
semanticscholar +4 more sources
Sensors, 2020 In this work, the use of Machine Learning methods for robust Received Signal Strength (RSS)-based Visible Light Positioning (VLP) is experimentally evaluated.
Willem Raes +4 more
doaj +2 more sources
Jurnal Elkomika, 2023 ABSTRAK Penentuan posisi di dalam ruangan merupakan hal yang penting untuk menjadikan petunjuk di dalam ruangan. Banyak metode lain yang sudah dilakukan penelitian tetapi ada beberapa kendala seperti tidak dapat digunakan di area sensitive dan biaya ...
ISTI FASYA +2 more
doaj +2 more sources
Analysis of Received Signal Strength Quantization in Fingerprinting Localization
Sensors, 2020 In recent times, Received Signal Strength (RSS)-based Wi-Fi fingerprinting localization has become one of the most promising techniques for indoor localization.
Syed Khandker +2 more
doaj +2 more sources
Improving Visible Light Positioning Accuracy Using Particle Swarm Optimization (PSO) for Deep Learning Hyperparameter Updating in Received Signal Strength (RSS)-Based Convolutional Neural Network (CNN). [PDF]
Sensors (Basel)Visible light positioning (VLP) has emerged as a promising indoor positioning technology, owing to its high accuracy and cost-effectiveness. In practical scenarios, signal attenuation, multiple light reflections, or light-deficient regions, particularly near room corners or furniture, can significantly degrade the light quality.
Chang CM, Lin YZ, Chow CW.
europepmc +4 more sources