Generic system architecture for context-aware, distributed recommendation

In the existing literature on recommender systems, it is difficult to find an architecture for large-scale implementation. Often, the architectures proposed in papers are specific to an algorithm implementation or a domain. Thus, there is no clear architectural starting point for a new recommender system. This paper presents an architecture blueprint for a context-aware recommender system that provides scalability, availability, and security for its users. The architecture also contributes the dynamic ability to switch between single-device (offline), client-server (online), and fully distributed implementations. From this blueprint, a new recommender system could be built with minimal design and implementation effort regardless of the application.Electrical and Computer Engineerin

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Paving the way to collaborative context-aware mobile applications: a case study on preventing worsening of allergy symptoms

En los últimos años, la evolución de los teléfonos inteligentes y sus aplicaciones de software ha crecido exponencialmente; junto con el avance del Internet de las Cosas y las ciudades inteligentes, ha generado una gran demanda de servicios y aplicaciones en estos dominios. Aunque la amplia gama de aplicaciones móviles es incuestionable, los ciudadanos ya exigen que las aplicaciones se adapten a sus necesidades y situaciones específicas en tiempo real, es decir, que sean conscientes del contexto. Sin embargo, las aplicaciones móviles conscientes del contexto a menudo son muy limitadas y pierden la oportunidad de beneficiarse de la retroalimentación proporcionada por la colaboración ciudadana. Para llenar este vacío, este documento propone una arquitectura de software y una aplicación móvil colaborativas y conscientes del contexto. En particular, los hemos implementado en el ámbito de la e-salud, más específicamente en el área de las alergias estacionales, que causan que las personas alérgicas experimenten síntomas molestos que podrían evitarse si tuvieran acceso a información sobre el polen en tiempo real. Además, también se beneficiarán de la colaboración ciudadana a través del conocimiento de los síntomas que otras personas alérgicas con la misma alergia y en la misma ubicación están experimentando. Para ello, los usuarios podrán proporcionar sus síntomas en cualquier momento a través de su aplicación móvil y la arquitectura propuesta procesará constantemente esa información en tiempo real, enviando notificaciones a los usuarios tan pronto como se vea que los síntomas reportados superan un cierto umbral. Se han probado el rendimiento de la arquitectura, el consumo de recursos de la aplicación y una encuesta de satisfacción sobre la usabilidad y utilidad de la aplicación; todos los resultados han sido completamente satisfactorios.In recent years, the evolution of smartphones and their software applications has grown exponentially; together with the advance of the Internet of Things and smart cities, it has raised huge demand for services and applications in these domains. Although the wide range of mobile applications is unquestionable, citizens already demand that applications adapt to their specific needs and situations in real time, that is, that they are context-aware. However, context-aware mobile applications are often very limited and miss out on the opportunity of benefiting from feedback provided by citizen collaboration. In order to fill this gap, this paper proposes a context-aware and collaborative software architecture and mobile application. In particular, we have implemented them in the scope of e-health, more specifically in the area of seasonal allergies, which cause allergic people to experience annoying symptoms that could be avoided by having access to pollen information in real time. Furthermore, they will also benefit from citizen collaboration through the knowledge of the symptoms other allergic people with the same allergy and in the same location are experiencing. To this end, users will be able to provide their symptoms at any time through their mobile application and the proposed architecture will constantly process that information in real time, sending notifications to users as soon as reported symptoms are seen to exceed a certain threshold. The architecture’s perfor mance, the application’s resource consumption and a satisfaction survey of the app’s usability and usefulness have been tested; all results have been fully satisfactoryThis work was supported by the Spanish Ministry of Science and Innovation and the European Union FEDER Funds [grant numbers RTI2018-093608-B-C33, RED2018-102654-T