Mejorando los sistemas rurales de alertas tempranas a través de la integración de OpenBTS y JAIN SLEE

Actualmente existe una tendencia que combina las características de los servicios Web 2.0 y los servicios de telecomunicaciones, conocida como Telco 2.0. Estos servicios convergentes se han aplicado exitosamente en sistemas de alertas tempranas, proporcionando mayor agilidad y flexibilidad en la prestación de servicios. Sin embargo, existen varias limitantes que no permiten el despliegue de servicios convergentes en las zonas rurales de países en vía de desarrollo, como la falta de disponibilidad de una ngn (Next Generation Network), la ausencia de tecnología avanzada y la falta de recursos para inversión. Este artículo propone una arquitectura de integración entre jain slee y OpenBTS para sistemas rurales de alertas tempranas. Se evalúa el prototipo implementado con un caso de estudio específico al enviar advertencias Telco 2.0 a los cafeteros colombianos cuyas plantaciones puedan verse afectadas por la roya, una de las enfermedades más peligrosas para la producción de café.Nowadays exists a trend that combines the features of Web 2.0 services and telecommunications services known as Telco 2.0. These converged services have been successfully implemented in early warning systems providing improved agility and flexibility in service delivery. However the deployment of converged services in rural zones of developing countries presents several constraints which do not allow to provide this kind of services, as the unavailability of a Next Generation Network (ngn), absence of advanced technology and lack of investment resources. This paper proposes a jain slee and OpenBTS integration architecture for early warning systems in rural zones. The implemented prototype is evaluated with a specific case study involving the deployment of Telco 2.0 warnings in Colombian coffee plantations which may be affected by coffee rust, one of the most threatening diseases in coffee production

Scaling readiness: Concepts, practices, and implementation.

Scaling Readiness is an approach that can support organizations, projects, and programs in achieving their ambitions to scale innovations and achieve impact. Scaling Readiness encourages critical reflection on how ready innovations are for scaling, and what appropriate actions could accelerate or enhance scaling

Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns

We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a low-cost mobile thermal camera integrated into a smartphone to capture thermal textures. A deep neural network classifies these textures into material types. This approach works effectively without the need for ambient light sources or direct contact with materials. Furthermore, the use of a deep learning network removes the need to handcraft the set of features for different materials. We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments. Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials. We conclude by discussing its potentials for real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing System

Mobiles and wearables: owner biometrics and authentication

We discuss the design and development of HCI models for authentication based on gait and gesture that can be supported by mobile and wearable equipment. The paper proposes to use such biometric behavioral traits for partially transparent and continuous authentication by means of behavioral patterns. © 2016 Copyright held by the owner/author(s)

5GNOW: Challenging the LTE Design Paradigms of Orthogonality and Synchronicity

LTE and LTE-Advanced have been optimized to deliver high bandwidth pipes to wireless users. The transport mechanisms have been tailored to maximize single cell performance by enforcing strict synchronism and orthogonality within a single cell and within a single contiguous frequency band. Various emerging trends reveal major shortcomings of those design criteria: 1) The fraction of machine-type-communications (MTC) is growing fast. Transmissions of this kind are suffering from the bulky procedures necessary to ensure strict synchronism. 2) Collaborative schemes have been introduced to boost capacity and coverage (CoMP), and wireless networks are becoming more and more heterogeneous following the non-uniform distribution of users. Tremendous efforts must be spent to collect the gains and to manage such systems under the premise of strict synchronism and orthogonality. 3) The advent of the Digital Agenda and the introduction of carrier aggregation are forcing the transmission systems to deal with fragmented spectrum. 5GNOW is an European research project supported by the European Commission within FP7 ICT Call 8. It will question the design targets of LTE and LTE-Advanced having these shortcomings in mind and the obedience to strict synchronism and orthogonality will be challenged. It will develop new PHY and MAC layer concepts being better suited to meet the upcoming needs with respect to service variety and heterogeneous transmission setups. Wireless transmission networks following the outcomes of 5GNOW will be better suited to meet the manifoldness of services, device classes and transmission setups present in envisioned future scenarios like smart cities. The integration of systems relying heavily on MTC into the communication network will be eased. The per-user experience will be more uniform and satisfying. To ensure this 5GNOW will contribute to upcoming 5G standardization.Comment: Submitted to Workshop on Mobile and Wireless Communication Systems for 2020 and beyond (at IEEE VTC 2013, Spring

A novel on-board Unit to accelerate the penetration of ITS services

In-vehicle connectivity has experienced a big expansion in recent years. Car manufacturers have mainly proposed OBU-based solutions, but these solutions do not take full advantage of the opportunities of inter-vehicle peer-to-peer communications. In this paper we introduce GRCBox, a novel architecture that allows OEM user-devices to directly communicate when located in neighboring vehicles. In this paper we also describe EYES, an application we developed to illustrate the type of novel applications that can be implemented on top of the GRCBox. EYES is an ITS overtaking assistance system that provides the driver with real-time video fed from the vehicle located in front. Finally, we evaluated the GRCbox and the EYES application and showed that, for device-to-device communication, the performance of the GRCBox architecture is comparable to an infrastructure network, introducing a negligible impact