La importancia de la labor del programador. ¿Qué se espera? ¿Cómo se prepara? Análisis desde los lenguajes de programación

A partir de los datos extraídos de una encuesta realizada a través de Novática, este trabajo pretende analizar, por un lado, los principales valores que perciben los diferentes actores profesionales (empresas, PYMEs, spin-offs, y Administraciones Públicas), con respecto a los valores que poseen los actores de formación (Universidades). Por otro lado, y desde el punto de vista de los lenguajes de programación, cuales son los lenguajes de programación más demandados profesionalmente, y cuales son los lenguajes de programación que se imparten o utilizan en las universidades españolas. Creemos que este análisis, tomado como una medida de la tendencia, puede servir para poner de manifiesto las posibles discrepancias que pueden existir entre el mundo profesional y la Universidad desde el punto de vista de la formación de profesionales con respecto a los lenguajes de programación. Las principales conclusiones del estudio son dos. Por un lado la principal visión que se tiene de un programador en el ámbito profesional es la de un técnico-integrador cuya labor es percibida con una importancia similar a la del resto de profesionales que participan en el desarrollo de proyectos informáticos. Por otro lado, los lenguajes de programación demandados en el mundo profesional se orientan hacia el desarrollo de aplicaciones web (Java, VB/.Net , JavaScript y PHP), mientras que en la Universidad la orientación es hacia los lenguajes de programación orientados a objetos, siendo Java y C++ son los que cuentan con un mayor peso específico

Citizen-Centric Data Services for Smarter Cities

Smart Cities use Information and Communication Technologies (ICT) to manage more efficiently the resources and services offered by a city and to make them more approachable to all its stakeholders (citizens, companies and public administration). In contrast to the view of big corporations promoting holistic “smart city in a box” solutions, this work proposes that smarter cities can be achieved by combining already available infrastructure, i.e., Open Government Data and sensor networks deployed in cities, with the citizens’ active contributions towards city knowledge by means of their smartphones and the apps executed in them. In addition, this work introduces the main characteristics of the IES Cities platform, whose goal is to ease the generation of citizen-centric apps that exploit urban data in different domains. The proposed vision is achieved by providing a common access mechanism to the heterogeneous data sources offered by the city, which reduces the complexity of accessing the city’s data whilst bringing citizens closely to a prosumer (double consumer and producer) role and allowing to integrate legacy data into the cities’ data ecosystem.The European Union’s Competitiveness and Innovation Framework Programme has supported this work under grant agreement No. 325097

Geospatial information infrastructures to address spatial needs in health: Collaboration, challenges and opportunities

Most health-related issues such as public health outbreaks and epidemiological threats are better understood from a spatial–temporal perspective and, clearly demand related geospatial datasets and services so that decision makers may jointly make informed decisions and coordinate response plans. Although current health applications support a kind of geospatial features, these are still disconnected from the wide range of geospatial services and datasets that geospatial information infrastructures may bring into health. In this paper we are questioning the hypothesis whether geospatial information infrastructures, in terms of standards-based geospatial services, technologies, and data models as operational assets already in place, can be exploited by health applications for which the geospatial dimension is of great importance. This may be certainly addressed by defining better collaboration strategies to uncover and promote geospatial assets to the health community. We discuss the value of collaboration, as well as the opportunities that geographic information infrastructures offer to address geospatial challenges in health applications

Indoor Positioning for Monitoring Older Adults at Home: Wi-Fi and BLE Technologies in Real Scenarios

This paper presents our experience on a real case of applying an indoor localization system formonitoringolderadultsintheirownhomes. Sincethesystemisdesignedtobeusedbyrealusers, therearemanysituationsthatcannotbecontrolledbysystemdevelopersandcanbeasourceoferrors. This paper presents some of the problems that arise when real non-expert users use localization systems and discusses some strategies to deal with such situations. Two technologies were tested to provide indoor localization: Wi-Fi and Bluetooth Low Energy. The results shown in the paper suggest that the Bluetooth Low Energy based one is preferable in the proposed task

Detection of Non-Stationary Photometric Perturbations on Projection Screens

Interfaces based on projection screens have become increasingly more popular in recent years, mainly due to the large screen size and resolution that they provide, as well as their stereo-vision capabilities. This work shows a local method for real-time detection of non-stationary photometric perturbations in projected images by means of computer vision techniques. The method is based on the computation of differences between the images in the projector’s frame buffer and the corresponding images on the projection screen observed by the camera. It is robust under spatial variations in the intensity of light emitted by the projector on the projection surface and also robust under stationary photometric perturbations caused by external factors. Moreover, we describe the experiments carried out to show the reliability of the method

A domain-independent methodology to analyze IoT data streams in real-time. A proof of concept implementation for anomaly detection from environmental data

Pushed by the Internet of Things (IoT) paradigm modern sensor networks monitor a wide range of phenomena, in areas such as environmental monitoring, health care, industrial processes, and smart cities. These networks provide a continuous pulse of the almost infinite activities that are happening in the physical space and are thus, key enablers for a Digital Earth Nervous System. Nevertheless, the rapid processing of these sensor data streams still continues to challenge traditional data-handling solutions and new approaches are being requested. We propose a generic answer to this challenge, which has the potential to support any form of distributed real-time analysis. This neutral methodology follows a brokering approach to work with different kinds of data sources and uses web-based standards to achieve interoperability. As a proof of concept, we implemented the methodology to detect anomalies in real-time and applied it to the area of environmental monitoring. The developed system is capable of detecting anomalies, generating notifications, and displaying the recent situation to the user

How to implement scrum manager in the software engineering route?

Ponència presentada a 13 th International Technology, Education and Development Conference, Valencia, 11-13 març 2019.Teaching in Software Engineering has evolved in recent years at the same time that software development methodologies have. Therefore, there are a lot of good examples in the literature on how to use Agile Methods in the teaching of the subjects of this track. Most of them focused on explaining the teaching organization, the subsequent evaluation and the obtained academic results, as well as their benefits. However, there are still unanswered questions when implementing the principles of an agile methodology such as Scrum Manager in teaching practice. This paper presents the result of a teaching experience of coordination of subjects in the context of Software Engineering carried out during four academic years. This has been formulated as best practices including the improvements that teachers have achieved in teaching after gathering feedback from students and the collaborative business environment. The main objective is to offer a help guide for teachers who want to use Scrum Manager in their subjects but who sometimes find problems that are not usually collected in the literature

A study of deep neural networks for human activity recognition

Human activity recognition and deep learning are two fields that have attracted attention in recent years. The former due to its relevance in many application domains, such as ambient assisted living or health monitoring, and the latter for its recent and excellent performance achievements in different domains of application such as image and speech recognition. In this article, an extensive analysis among the most suited deep learning architectures for activity recognition is conducted to compare its performance in terms of accuracy, speed, and memory requirements. In particular, convolutional neural networks (CNN), long short‐term memory networks (LSTM), bidirectional LSTM (biLSTM), gated recurrent unit networks (GRU), and deep belief networks (DBN) have been tested on a total of 10 publicly available datasets, with different sensors, sets of activities, and sampling rates. All tests have been designed under a multimodal approach to take advantage of synchronized raw sensor' signals. Results show that CNNs are efficient at capturing local temporal dependencies of activity signals, as well as at identifying correlations among sensors. Their performance in activity classification is comparable with, and in most cases better than, the performance of recurrent models. Their faster response and lower memory footprint make them the architecture of choice for wearable and IoT devices

Magnetic field based Indoor positioning using the Bag of Words paradigm

Ponencia presentada en 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 4-7 Oct. 2016In this paper, A Bag of Words based method is presented to test a magnetic field based indoor positioning method. The Indoor positioning problem is solved as a pattern recognition problem, where each reference point is a different class. Feature vectors are constructed using a simplified bag of words methodology allowing user speed invariance. Several well known classifiers have been used to test the proposed method obtaining promising results when recognition the position of the user