Indoor navigation systems incorporating augmented reality allow users to locate places within buildings and acquire more knowledge about their environment. However, although diverse works have been introduced with varied technologies, infrastructure, and functionalities, a standardization of the procedures for elaborating these systems has not been reached. Moreover, while systems usually handle contextual information of places in proprietary formats, a platform-independent model is desirable, which would encourage its access, updating, and management. This paper proposes a methodology for developing indoor navigation systems based on the integration of Augmented Reality and Semantic Web technologies to present navigation instructions and contextual information about the environment. It comprises four modules to define a spatial model, data management (supported by an ontology), positioning and navigation, and content visualization. A mobile application system was developed for testing the proposal in academic environments, modeling the structure, routes, and places of two buildings from independent institutions. The experiments cover distinct navigation tasks by participants in both scenarios, recording data such as navigation time, position tracking, system functionality, feedback (answering a survey), and a navigation comparison when the system is not used. The results demonstrate the system’s feasibility, where the participants show a positive interest in its functionalities.

A universal pH indicator is used to fabricate a fiber optic ammonia sensor. The advantage of this pH indicator is that it exhibits sensitivity to ammonia over a broad wavelength range. This provides a differential response, with a valley around 500 nm and a peak around 650 nm, which allows us to perform ratiometric measurements. The ratiometric measurements provide not only an enhanced signal, but can also eliminate any external disturbance due to humidity or temperature fluctuations. In addition, the indicator is embedded in a hydrophobic and gas permeable polyurethane film named Tecoflex^®. The film provides additional advantages to the sensor, such as operation in dry environments, efficient transport of the element to be measured to the sensitive area of the sensor, and prevent leakage or detachment of the indicator. The combination of the universal pH indicator and Tecoflex^® film provides a reliable and robust fiber optic ammonia sensor.

In this work we demonstrate efficient quality control of a variety of gasoline and ethanol (gasohol) blends using a multimode interference (MMI) fiber sensor. The operational principle relies on the fact that the addition of ethanol to the gasohol blend reduces the refractive index (RI) of the gasoline. Since MMI sensors are capable of detecting small RI changes, the ethanol content of the gasohol blend is easily determined by tracking the MMI peak wavelength response. Gasohol blends with ethanol contents ranging from 0% to 50% has been clearly identified using this device, which provides a linear response with a maximum sensitivity of 0.270 nm/% EtOH. The sensor can also distinguish when water incorporated in the blend has exceeded the maximum volume tolerated by the gasohol blend, which is responsible for phase separation of the ethanol and gasoline and could cause serious engine failures. Since the MMI sensor is straightforward to fabricate and does not require any special coating it is a cost effective solution for real time and in-situ monitoring of the quality of gasohol blends.

In the last few years, the growing demand for electric vehicles (EVs) in the transportation sector has contributed to the increased use of electric rechargeable batteries. At present, lithium-ion (Li-ion) batteries are the most commonly used in electric vehicles. Although once their storage capacity has dropped to below 80–70% it is no longer possible to use these batteries in EVs, it is feasible to use them in second-life applications as stationary energy storage systems. The purpose of this study is to present an embedded system that allows a Nissan^® LEAF Li-ion battery to communicate with an Ingecon^® Sun Storage 1Play inverter, for control and monitoring purposes. The prototype was developed using an Arduino^® microcontroller and a graphical user interface (GUI) on LabVIEW^®. The experimental tests have allowed us to determine the feasibility of using Li-ion battery packs (BPs) coming from the automotive sector with an inverter with no need for a prior disassembly and rebuilding process. Furthermore, this research presents a programming and hardware methodology for the development of the embedded systems focused on second-life electric vehicle Li-ion batteries. One second-life battery pack coming from a Nissan^® Leaf and aged under real driving conditions was integrated into a residential microgrid serving as an energy storage system (ESS).