Location Based Indoor and Outdoor Lightweight Activity Recognition System

In intelligent environments one of the most relevant information that can be gathered about users is their location. Their position can be easily captured without the need for a large infrastructure through devices such as smartphones or smartwatches that we easily carry around in our daily life, providing new opportunities and services in the field of pervasive computing and sensing. Location data can be very useful to infer additional information in some cases such as elderly or sick care, where inferring additional information such as the activities or types of activities they perform can provide daily indicators about their behavior and habits. To do so, we present a system able to infer user activities in indoor and outdoor environments using Global Positioning System (GPS) data together with open data sources such as OpenStreetMaps (OSM) to analyse the user’s daily activities, requiring a minimal infrastructure

Design and implementation of an open framework for ubiquitous carbon footprint calculator applications

As climate change is becoming an important global issue, more and more people are beginning to pay attention to reducing greenhouse gas emissions. To measure personal or household carbon dioxide emission, there are already plenty of carbon footprint calculators available on the web. Most of these calculators use quantitative models to estimate carbon emission caused by a user\u27s activities. Although these calculators can promote public awareness regarding carbon emission due to an individual\u27s behavior, there are concerns about the consistency and transparency of these existing CO2 calculators. Apart from a small group of smart phone based carbon footprint calculator applications, most of the existing CO2 calculators require users to input data manually. This not only provides a poor user experience but also makes the calculation less accurate. The use of a standard framework for various carbon footprint application developments can increase the accuracy of overall calculations, which in turn may increase energy awareness at the individual human level. We aim for developing a carbon footprint calculation framework that can serve as a platform for various carbon footprint calculator applications. Therefore, in this paper, we propose a platform-agnostic Open Carbon Footprint Framework (OCFF) that will provide the necessary interfaces for software developers to incorporate the latest scientific knowledge regarding climate change into their applications. OCFF will maintain a clouded knowledge base that will give developers access to a dynamic source of computational information that can be brought to bear on real-time sensor data. Based on the OCFF platform, we developed a Ubiquitous Carbon Footprint Calculator application (UCFC) that allows the user to be aware of their personal carbon footprint based on their ubiquitous activity and act accordingly. The major contribution of this paper is the presentation of the quantitative model of the platform along with the entire design and implementation of UCFC application. We also present the results, analysis, and findings of an extensive survey that has been conducted to find users’ awareness of increased carbon footprint, feature requirements, and expectations and desires to alleviate CO2 emissions by using a footprint calculator. The design of UCFC application incorporates the analysis and inferences of the survey results. We are also developing a fuel efficient mobile GPS application for iPhone suggesting the greenest/most fuel efficient route to the user. In this paper, we also point out some important features of such an application

Horizon Report 2009

El informe anual Horizon investiga, identifica y clasifica las tecnologías emergentes que los expertos que lo elaboran prevén tendrán un impacto en la enseñanza aprendizaje, la investigación y la producción creativa en el contexto educativo de la enseñanza superior. También estudia las tendencias clave que permiten prever el uso que se hará de las mismas y los retos que ellos suponen para las aulas. Cada edición identifica seis tecnologías o prácticas. Dos cuyo uso se prevé emergerá en un futuro inmediato (un año o menos) dos que emergerán a medio plazo (en dos o tres años) y dos previstas a más largo plazo (5 años)

An energy-saving model for service-oriented mobile application development

The development of mobile applications that combine Web Services from different providers --also referred as mashup applications-- is growing as a consequence of the ubiquity of bandwidth connections and the increasing number of available Web Services. In this context, providing higher maintainability to Web Service applications is a worth of matter, because of the dynamic nature of the Web. EasySOC (1) solves this problem by decoupling mashups from application components. However, mobile devices have energy constraints because of the limitations in the current battery capacities. This work proposes a model that builds on the benefits of the EasySOC approach and improves this latter by assisting developers to select Web Service combinations that reduce energy consumption. We evaluated the feasibility of the model through a case study in which we compare the estimations provided by the model against real energy measurements. The results indicated that our model had an efficacy of 81% for the analyzed case study.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Decision support system for collaborative freight transportation management: a tool for mixing traditional and green logistics.

In recent years, freight transportation emerged as a key factor in the development and dynamicity of countries, although it has a considerably impact on urban areas, due to the environmental issues. In this context, several stakeholders have implemented City Logistics solutions in order to make transportation more sustainable and efficient. This paper proposes a case study concerning the collaborative transportation system involving traditional and green couriers, in the city of Turin. This freight pooling is supported by a decision support system that combines the ERP “Odoo” with an algorithm for the optimization planning of routes. This decision support system is described in the second section and finally, some results obtained from its application are discussed

Toxic Chemicals Transported by Rail and Public Health Safety using GIS in Montgomery County, Ohio

Hazardous chemicals transported by rail pass directly through urban cities and pose a safety and health threat to the community. Some of these chemicals can be in large quantities, extremely toxic, devastating to the environment and have the potential to cause mass casualties and death. Thousands of people could be in harm’s way. While there is always the possibility for accidental chemical release, they also have the potential to be used in acts of sabotage and terrorism. Evaluation of the rail line in Montgomery County, Ohio using standards in the 2008 Emergency Response Guidebook using geographic information systems (GIS) at designated evacuation distances showed that many people, schools, hospitals, nursing homes and public venues are at risk in the event of a chemical release. Using GIS for modeling can help emergency management better coordinate evacuation and shelter in place procedures with the public, plan evacuation routes, and decrease the morbidity and mortality of the exposed. The data collected, by use of GIS, can help give a more inclusive picture of those impacted by a train tanker toxic chemical release and provide evidence for policy review

"Whose data is it anyway?" The implications of putting small area-level health and social data online

International audienceThe planetary exospheres are poorly known in their outer parts, since the neutral densities are low compared with the instruments detection capabilities. The exospheric models are thus often the main source of information at such high altitudes. We present a new way to take into account analytically the additional effect of the radiation pressure on planetary exospheres. In a series of papers, we present with an Hamiltonian approach the effect of the radiation pressure on dynamical trajectories, density profiles and escaping thermal flux. Our work is a generalization of the study by Bishop and Chamberlain (1989). In this second part of our work, we present here the density profiles of atomic Hydrogen in planetary exospheres subject to the radiation pressure. We first provide the altitude profiles of ballistic particles (the dominant exospheric population in most cases), which exhibit strong asymmetries that explain the known geotail phenomenon at Earth. The radiation pressure strongly enhances the densities compared with the pure gravity case (i.e. the Chamberlain profiles), in particular at noon and midnight. We finally show the existence of an exopause that appears naturally as the external limit for bounded particles, above which all particles are escaping

Advanced Location-Based Technologies and Services

Since the publication of the first edition in 2004, advances in mobile devices, positioning sensors, WiFi fingerprinting, and wireless communications, among others, have paved the way for developing new and advanced location-based services (LBSs). This second edition provides up-to-date information on LBSs, including WiFi fingerprinting, mobile computing, geospatial clouds, geospatial data mining, location privacy, and location-based social networking. It also includes new chapters on application areas such as LBSs for public health, indoor navigation, and advertising. In addition, the chapter on remote sensing has been revised to address advancements