HYDROMET SENSING: THE NEXT GENERATION SENSOR-TO-DATA MANAGEMENT SYSTEM USING OPEN SOURCE TECHNOLOGIES (Invited)
In situ monitoring remains the only way of acquiring accurate, reliable, efficient, cost-effective high-frequency and long-term environmental data. Current in situ monitoring systems often overlook the critically important inclusion of a standard data management and publication system. Therefore, fully streamlining current commercially-available environmental monitoring systems adopting a data-from-sensor to storage-and-proper-annotation approach is not only long and arduous, but also pervaded with break-downs and omissions. This prompts the need to combine collection, transmission, management and delivery into a single package. This paper introduces an automated Sensor-to-Data Management System (SDMS) prototype using both open source software and hardware technologies. The system comprises a complete sensor-to-data-dissemination chain of software applications developed using the Python programming language. In addition, it contains a compact custom-made datalogger using the C.H.I.P microcomputer to support the software applications used in field data acquisition. The system, thus, is capable of handling the aspects of data collection, transmission, management and publication as well as network organization automatically. The developed system has been tested in both indoor and outdoor environments and it is effective in not only reducing field data acquisition workload, but also in laying the foundation of cost affordability.
PAUL CELICOURT (Primary Presenter/Author), SENSAQ, LLC, email@example.com;
Richard Sam ( Co-Presenter/Co-Author), SENSAQ, LLC, firstname.lastname@example.org;
Michael Piasecki ( Co-Presenter/Co-Author), The City College of New York, email@example.com;