INES – National Institute of Science and Technology for Software Engineering

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June 2015
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  • A SW platform for mathematical processing of satellite imaging (in real-time)

    Publicado em June 19th, 2015Uncategorized


    Researchers acquire 56% of the equipment provided in the DESERT-MAP project. The equipment is being used in the construction of a plataform for satellite imaging capture, mathematical processing compartmentalization of images and providing them as a platform for application development.

    First results

    To validate the platform researchers built a risk assessment map to desertification of an area of the northeastern semi-arid (Floresta-PE).

    The first image read by Geosere satellites and processed by the platform can be found here:

    (Red is desert, yellow is risk of desertification and green is free of desertification and blue is water resources)

    Next steps

    The complete process used to it will be described and submitted to a scientific journal.

    A web layer is underconstruction. We will call this app for risk of desertification, “desert-maps” like “google-maps”. This is not coincidence.


    Publicado em June 19th, 2015News, Projects

    Logo HealthDrones

    Researchers acquire 40% of the equipment according to project HEALTHDRONES. The equipment is to improve the simulation infrastructure to test algorithms used to assess the degree of programmability of the software platform developed for UAVs.

    The first results

    Some autonomous simulation test flight controlled by our “API” in a Parrot Elite model and without GPS or GPRS or any kind of manufacturer facility have been done. They can be found here:

    Some photos are also available illustrating how we use Arduino to control the UAV. Thus, we became independent of the trading platform.

    The next steps

    The entire process will be documented in a dissertation to be completed in August 2015 ( and subsequently published in a scientific journal in the area.

    Another dissertation is underway (first results even in 2015). This tests the degree of programmability platform developed when applied to control outbreaks in populations.

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