Post-doc in Spatial Big Data (France)

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    Website Irstea (future INRAE)

    OPEN ONE YEAR POST-DOC POSITION IN: SPATIAL BIG DATA FOR STORING AND ANALYZING TRAJECTORIES of ROBOTS

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    One Year post-doc position in Spatial Big Data is available at Irstea (future INRAE), Clermont Ferrand, France.

    The position is in the context of the SupeRob project financed by CAP20-25 I-SITE University Clermont Auvergne.

    CONTEXT

    The SupeRob project aims at providing the data storage, algorithms, and tools for the management and supervision of a fleet of autonomous mobile robots in deployed in agriculture.

    SupeRob proposes to set up a model of sharing robots in an agricultural equipment cooperative. As a result, a fleet of robots that will be managed, including tasks as: (1) periodical maintenance and repairs, (2) configuration (installation, change, tools for agricultural tasks), (3) storing in a warehouse, before being deployed to work on different sites. The deployment will then consist of routing the robots to a site where local supervision will take control of the robot. The central supervisor should be informed of the progress of robots in their task, and of any hazard, or additional request of a site, which would call into question the forward planning of resources.

    The planning and control algorithms need to be deployed over a database and they must react in real-time manner to allow the decision-makers to change/stop the robots technical operations.

    Robots management will be supported by a Spatial Data Warehouse (SDW) and a Spatial OLAP (SOLAP), which are the technologies that enable the analysis and exploration of large amounts of spatial data. Warehoused spatial data come from mobile robots (locatio, guidance, and control data). Spatio-temporal data (trajectories) are associated with the context data (characteristics of the places of stops, e.g., areas of power recharge and/or maintenance), characteristics of the transition zones / trajectories to follow, e.g., linkage paths between plots and places of detention.

    GOALS

    The main objectives of this post-doc project are as follows:

    To investigate the usage of SDW to store spatial big data coming from numerous sensors embedded in robots, and its contextual data. Many proposals investigate the usage of NoSQL Database Management Systems (DBMSs) for handling sensors data. In particular, some works propose ad-hoc NoSQL DBMSs logical models to store Robot Operating System (ROS) data. These works do not benchmark the usage of spatial data in querying the SDW, and they do not address aggregation queries. Therefore, the post-dooc will propose a suitable logical model for storing trajectories data coming from ROS.

    To propose a method for answering in real-time queries over the SDW. To monitor the planning activities of the robots, the decision-makers will use the SDW. Querying in real-time the trajectories the SDW is very difficult to the complexity of trajectory data and its large volume. These queries could use historical data to find in the SDW similar scenarios and to help the decision-makers to propose a solution to the current planning problem. Therefore, the post-doc will propose a method for approximating OLAP queries, and so provide results in real-time. In particular, we will focus on data reduction using clustering methods.

    To develop SOLAP analysis on the geovisual exploration of wareoused spatial data (the SDW). The work will focus on the practical use of the space time cube geo-visualization paradigm for spatial OLAP.

    SUITABLE BACKGROUND AND REQUIREMENTS

    Applicants must have obtained a Phd in computer science before April 2020

    Preferred research and technical skills:

    • DBMS for Big Data both relational and NoSQL (e.g., Cassandra, Mongodb)
    • Data warehouse and OLAP
    • Spatial Big Data
    • Geovisualization

    SUPERVISORS

    The postdoc will be supervised by:

    • Sandro Bimonte, Irstea (future INRAE), France
    • Robert Wrembel, Poznan University of Technology, Poland

    ADMINISTRATIVE INFORMATION

    The post-doc grant duration is 12 months, its tentative start is scheduled for April – June 2020

    The post-doc will work at Irstea, 9 Avenue Blaise Pascal, Aubiere 63178 France

    CONTACT INFORMATION

    The candidates are requested to contact Sandro Bimonte, Irstea (sandro.bimonte@irstea.fr ) or Robert Wrembel (robert.wrembel@cs.put.poznan.pl ) and send a complete CV, and a recommendation letter.

    APPLICATION DEADLINE: 30 November, 2019

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    Asif Razzaq is an AI Tech Blogger and Digital Health Business Strategist with robust medical device and biotech industry experience and an enviable portfolio in development of Health Apps, AI, and Data Science. An astute entrepreneur, Asif has distinguished himself as a startup management professional by successfully growing startups from launch phase into profitable businesses. This has earned him awards including, the SGPGI NCBL Young Biotechnology Entrepreneurs Award.