13 research outputs found

    Snapshots of the EYES project

    Get PDF
    The EYES project (IST-2001-34734) is a three years European research project on self-organizing and collaborative energy-efficient sensor networks. It addresses the convergence of distributed information processing, wireless communications, and mobile computing. The goal of the project is to develop the architecture and the technology which enables the creation of a new generation of sensors that can effectively network together so as to provide a flexible platform for the support of a large variety of mobile sensor network applications. This paper provides a broad overview of the EYES project and highlights some approaches and results of the architecture

    Web-based platform for evaluation of RF-based indoor localization algorithms

    No full text
    The experimental efforts for optimizing the performance of RF-based indoor localization algorithms for specific environments and scenarios is time consuming and costly. In this work, we address this problem by providing a publicly accessible platform for streamlined experimental evaluation of RF-based indoor localization algorithms, without the need of a physical testbed infrastructure. We also offer an extensive set of raw measurements that can be used as input data for indoor localization algorithms. The datasets are collected in multiple testbed environments, with various densities of measurement points, using different measuring devices and in various scenarios with controlled RF interference. The platform encompasses two core services: one focused on storage and management of raw data, and one focused on automated calculation of metrics for performance characterization of localization algorithms. Tools for visualization of the raw data, as well as software libraries for convenient access to the platform from MATLAB and Python, are also offered. By contrasting its fidelity and usability with respect to remote experiments on dedicated physical testbed infrastructure, we show that the virtual platform produces comparative performance results while offering significant reduction in the complexity, time and labor overheads
    corecore