INES – National Institute of Science and Technology for Software Engineering

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  • IndoLoR – Indoor Location Radar

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    Publicado em August 18th, 2014Projects

    The advent of mobile technologies and the new technological trend of connecting objects to the global computer network, also known as Internet of things, are making ubiquitous computing a reality in many corporate and residential environments. This new scenario is creating new opportunities for applications, in particular for smart environments. An application area that can take advantage of the technological capabilities provided by smart environments are the RTLS – real time location systems. Classic examples are the problem of indoor and outdoor location. Intrinsically, people are already familiar with outdoor applications that usually use location based on GPS (global positioning system) to provide LBS (Location-based services). This application is especially common in cars and on mobile devices. However, the indoor location adds new challenges, depending on a pre-existing infrastructure in the environment and a better location accuracy. In general, contextual information (checking at specific points) and the level of the received communication signal (RSSI – Received Signal Strength Indicated) are analyzed for the location of the target object, which might be a person or an object. Wireless technologies such as WiFi, RFID, Zigbee and Bluetooth are the most frequently used for indoor tracking.

    This project aims to develop, integrate and evaluate solutions of hardware, software and networks for automation of enterprise environments that enable the development of applications with high added value of indoor location. The solution called IndoLoR (Indoor Location Radar), integrates several emerging areas such as Internet of Things, Pervasive and Ubiquitous Computing, Cloud Computing, Smart Sensors Network and Context Sensitivity.

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  • HEALTHDRONES – Evaluating drones as a software platform for development of applications for monitoring epidemiological and crowd phenomena

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    Publicado em August 11th, 2014Projects

    The use of satellite data can be complemented by collected one by devices in flight (unmanned aerial vehicles called here “drones”). This provides a platform of data very close to reality and can be programmable by IOT (Internet Of Things) applications. These data can be used for monitoring environments at risk or under specific control (epidemiological or any crowd phenomena). This project will provide an overview of the software platforms available today for development of algorithms for unmanned aerial vehicles (UAVs) in autonomous flight to be used in IOT applications. We are primarily interested in their use for epidemiological monitoring of areas under risk, but these platforms can be used to monitor any kind of crowd event. In particular, in this project, images are captured and processed using NOAA and Meteosat 8 Satellites. They are operated by GOESERE-UFRPE (Laboratory of GIS and Remote Sensing of the Federal Rural University of Pernambuco) – http://www.dtr.ufrpe.br/geosere/ – and are used to compose the monitoring scenarios.  Images and other data are also captured and processed by the drones platforms and its sensors. This information will compound automatic surveillance scenarios of the phenomena.

    The development of a prototype for Schistosomiasis will provide an evaluation of the platforms used for this project. In this way, as the main outcome, this project will provide an overview of technologies available today, their ability to integrate with legacy systems and their programming capabilities. It is expected to evaluate at least five different air platforms and this project enables the acquisition of such platforms. The importance of this project for the industry takes on the aspect of evaluation of commercial platforms for UAVs to be a possible IDE for software applications in industry.

    This project is a coordinate action by researchers from GOESERE-UFRPE, CIN-UFPE, CESAR, LIKA, EPITRACK and ISI-TICs.

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