![]() ![]() Thus, the present work aims to develop a system for indoor localisation prediction using Bluetooth-based fingerprinting using Convolutional Neural Networks (CNN). Many of the services provided by the applications are based on knowledge of the localisation and profile of the end user. The growing interest in the use of IoT technologies has generated the development of numerous and diverse applications. The results reported in this work are close to 94% of accuracy, which clearly shows the great potential of this novel technique to the development of more accurate indoor localisation systems. Finally, an evolutionary algorithm has been implemented to configure and optimize our solution with the combination of different transmission power levels. ![]() Our proposal also includes the use and a comparative analysis of two dimensional reduction algorithms, PCA and t-SNE. For this transformation, we have used the technique used in painting known as blurring technique, simulating the diffusion of the signal spectrum. For this purpose, a novel technique has been developed that simulates the diffusion behaviour of the wireless signal by transforming tidy data into images. ![]()
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