Manuel Castillo-Cara

TL;DR: A simple data-driven approach using available global information before the CO VID-19 pandemic, seemed able to classify countries in terms of the number of confirmed COVID-19 cases, but the model was not able to stratify countries based on COvid-19 mortality data.

TL;DR: This paper focuses on the tuning of the RSSI fingerprint to be used in the implementation of a Bluetooth Low Energy 4.0 (BLE4.0) Bluetooth localization mechanism and shows that this proposal can greatly improve the localization accuracy by setting a custom transmission power level for each BLE4.

TL;DR: A simple data-driven approach using available global information before the CO VID-19 pandemic, seemed able to classify countries in terms of the number of confirmed COVID-19 cases, but the model was not able to stratify countries based on COvid-19 mortality data.

TL;DR: This paper investigates the characterization of Bluetooth signals behavior using 12 different supervised learning algorithms as a first step toward the development of fingerprint-based localization mechanisms, and explores the use of metaheuristics to determine the best radio power transmission setting evaluated in terms of accuracy and mean error of the localization mechanism.

TL;DR: The implementation of a cost-effective assistive mobile application aiming to improve the quality of life of visually impaired people and based on open source code: a must for applications to be adapted to the cultural and social characteristics of urban areas across the world.