Rapid Prototyping of An Automated Sensor-to-Server Environmental Data Acquisition System Adopting A FAIR-Oriented Approach

Abstract

Most existing environmental data acquisition systems are not designed to support automatic field data streaming to a data management system, but instead involve manual data exports therein. This paper introduces a FAIR-oriented (Findable, Accessible, Interoperable, and Reusable) approach and prototype of an automated sensor-to-web services and analytics wireless sensor network in which the aspects of data collection, transmission, and management as well as network organization are implemented automatically. The Python programming language was used to develop the necessary software components. The data and metadata supplied by custom-made stations are automatically stored in an extended instance of the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI) Observations Data Model (ODM) to which a web interface is linked and makes the data available publicly in user’s preferred units via Web Services and Data Analytics at a central station. The system has been initially tested in outdoor environments and the experiments demonstrate that it is effective in not only reducing the workload of the post-deployment phase, but also has potential to reduce human errors.