A Flexible, Cloud-based Sensor Data Service Platform
TimeTuesday, July 246:30pm - 8:30pm
DescriptionPlant phenotyping research has grown rapidly in the past decade. With the wide adoption of GIS enabled sensors, devices, and instruments, the amount of data collected have grown rapidly as well, especially data collected in the fields. On the other hand, the transfer and management tools for such field data are lagging behind. Many researchers still rely on the old way of saving data to disks from devices in simple text files or spreadsheets before copying them to their desktop or department server for analysis, leading to inaccurate or lost data and low level of productivity. To help filling this gap, we collaborated with a plant phenotyping sensor research group at Purdue University to develop a flexible, cloud-based data service platform for field sensor data ingestion, management, processing, and analysis. Deployed on XSEDE’s JetStream VM environment, the platform is built based on an open source software stack, including MongoDB for sensor data management, Node.js for geospatial data preprocessing and data access REST API, and an online visual analytics application implemented as a web component on a HUBzero platform. In this poster, we will describe the overall system architecture, software implementation, and how it has been used in supporting plant phenotyping sensor research in the field.