A Ligthweight Wayfinding Assistance System for IoT Applications

Mouna Afif, Riadh Ayachi, Mohamed Atri
2021 Trends Journal of Sciences Research  
In this paper, we propose to design an indoor sign detection system for industry 4.0. In order to implement the proposed system, we proposed a lightweight deep learning-based architecture based on MobileNet which can be run on embedded devices used to detect and recognize indoor landmarks signs in order to assist blind and sighted during indoor navigation. We apply various operations in order to minimize the network size as well as computation complexity. Internet of things (IoT) presents a
more » ... ection between internet and the surroundings objects. IoT is characterized to connect physical objects with their numerical identities and enables them to connect with each other. This technique creates a kind of bridge between the physical world and the virtual world. The paper provides a comprehensive overview of a new method for a set of landmark indoor sign objects based on deep convolutional neural network (DCNN) for internet of things applications.
doi:10.31586/jaibd.2021.147 fatcat:roshkphc6zcxjdc4vcusjlqu2y