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2013 ASHS Annual Conference

15068:
Accessing Real-Time Data from Sensor Networks

Thursday, July 25, 2013: 11:30 AM
Desert Salon 13-14 (Desert Springs J.W Marriott Resort )
John D. Lea-Cox, University of Maryland, College Park, MD
David Kohanbash, Carnegie Mellon University, Pittsburgh, PA
George Kantor, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA
As part of the SCRI–Managing Irrigation and Nutrition via Distributed Sensing (MINDS) project (http://smart-farms.net), we have developed advanced software which provides layers of information for growers to both monitor crop data and control irrigation events in nursery and greenhouse production environments.  This software is accessed through a dedicated website that is setup for each farm, thereby enabling the information to be accessed over the internet from a smart-phone or tablet.  The homepage provides instantaneous information from each sensor node in the farm network, by simply color coding the status of each node. Tapping or hovering on a node shows the latest data from the sensors and grower tools attached to that node.  Color-coding is linked to sensor ranges, which are setup by the grower, e.g. average soil moisture from 27% to 30% volumetric water content.  When the average readings from those sensors deviates from those ranges, the node will change color on the homepage (green–amber–red); the software can also be set up to send a text or email alert.  The software is designed to provide much deeper levels of customized capability for automatic irrigation control. Throughout the development of this system, continuous grower feedback and interaction ensured that the functionality and use of the system focused on the needs of the end-user.  One of the primary requirements was the ability to check the status, or make an informed decision (action) within a 5-minute window, by quickly reviewing data through the homepage or charts.  The charting tools were designed to be dynamic and allow the user to work with charts from a smart-phone or tablet.  This software was used extensively by a number of growers in 2012, and by researchers to access and control irrigation decisions from locations across the United States.  We have also integrating this functionality into local greenhouse and greenroof networks for student directed research and demonstration projects.