In recent years, smartphones have become the main computing tool for most of the population, making them an ideal tool in many areas. Most of these smartphones are equipped with cutting-edge hardware on their digital cameras, sensors and processors. For this reason, this paper discusses the possibility of using smartphones as an accessible and accurate tool, focusing on the measurement of light, which is an element that has a high impact on human behavior, which promotes conformance and safety, or alters human physiology when it is inappropriate. To carry out this study, three different ways to measure light through smartphones have been checked: the ambient light sensor, the digital camera and an external Bluetooth luxmeter connected with the smartphone. As a result, the accuracy of these methods has been compared to check if they can be used as accurate measurement tools.

Street lighting has a big impact on the energy consumption of Spanish municipalities. To decrease this consumption, the Spanish government has developed two different regulations to improve energy savings and efficiency, and consequently, reduce greenhouse-effect gas emissions. However, after these efforts, they have not obtained the expected results. To improve the effectiveness of these regulations and therefore to optimize energy consumption, a study has been done to analyze the different devices which influence energy consumption with the intention of better understanding their behavior and performance. The devices analyzed were lamps, ballasts, street lamp globes, control systems and dimmable lighting systems. To improve their performance, they have been analyzed from three points of view: changes in technology, use patterns and standards. Thanks to this study, some aspects have been found that could be taken into account if we really wanted to use energy efficiently.

Street lighting installations are an essential service for modern life due to their capability of creating a welcoming feeling at nighttime. Nevertheless, several studies have highlighted that it is possible to improve the quality of the light significantly improving the uniformity of the illuminance. The main difficulty arises when trying to improve some of the installation’s characteristics based only on statistical analysis of the light distribution. This paper presents a new algorithm that is able to obtain the overall illuminance uniformity in order to improve this sort of installations. To develop this algorithm it was necessary to perform a detailed study of all the elements which are part of street lighting installations. Because classification is one of the most important tasks in the application areas of artificial neural networks, we compared the performances of six types of training algorithms in a feed forward neural network for analyzing the overall uniformity in outdoor lighting systems. We found that the best algorithm that minimizes the error is “Levenberg-Marquardt back-propagation”, which approximates the desired output of the training pattern. By means of this kind of algorithm, it is possible to help to lighting professionals optimize the quality of street lighting installations.

Modern handheld devices and wireless communications foster new kinds of communication and interaction that can define new approaches to teaching and learning. Mobile learning (m-learning) seeks to use them extensively, exactly in the same way in which e-learning uses personal computers and wired communication technologies. In this new mobile environment, new applications and educational models need to be created and tested to confirm (or reject) their validity and usefulness. In this article, we present a mobile tool aimed at self-assessment, which allows students to test their knowledge at any place and at any time. The degree to which the students' achievement improved is also evaluated, and a survey on the students' opinion of the new tool was also conducted. An experimental group of 20- to 21-year-old nursing students was chosen to test the tool. Results show that this kind of tool improves students' achievement and does not make necessary to introduce substantial changes in current teaching activities and methodology.