Technologies and techniques of location and navigation are advancing, allowing greater precision in locating people in complex and challenging conditions. These advances have attracted growing interest from the scientific community in using indoor positioning systems (IPSs) with a higher degree of precision and fast delivery time, for groups of people such as the visually impaired, to some extent improving their quality of life. Much research brings together various works that deal with the physical and logical approaches of IPSs to give the reader a more general view of the models. These surveys, however, need to be continuously revisited to update the literature on the features described. This paper presents an expansion of the range of technologies and methodologies for assisting the visually impaired in previous works, providing readers and researchers with a more recent version of what was done and the advantages and disadvantages of each approach to guide reviews and discussions about these topics. Finally, we discuss a series of considerations and future trends for the construction of indoor navigation and location systems for the visually impaired.
Additionally, it was funded by Samsung Electronics of Amazonia Ltda, under the terms of Federal Law n • 8.387/1991, according to for in Article 48 of Decree n • 6.008/2006, through grant agreement n • 004, signed with CETELI (Center for Research and Development of Electronic Technology and Information) supporting the graduate program of Electrical Engineering-at UFAM.
In this paper, we present an approach to assess the schedulability and scalability of Cyber-Physical Systems (CPS) Networks through an algorithm that is capable of estimating the load of the network as its utility grows. Our approach evaluates both the network load and the laxity of messages, considering its current topology and real-time constraints while abstracting environmental specificities. The proposed algorithm also accounts for the network unreliability by applying a margin-of-safety parameter. This approach enables higher utilities as it evaluates the load of the network considering a margin-of-safety that encapsulates phenomena such as collisions and interference, instead of performing a worst-case analysis. Furthermore, we present an evaluation of the proposed algorithm over three representative scenarios showing that the algorithm was able to successfully assess the network capacity as it reaches a higher use.
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