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Remote Control of the Greenhouses
Below is information regarding the technological capabilities of the
Plant Growth Facilities. One advanced feature of which we are very proud
is the capability to remotely access the environmental control systems
of the facilities by laptop or wireless PDA. If a problem occurs in
a greenhouse zone, the manager can attend to the system failure from
a remote site, diagnosing the problem, changing settings and even overriding
equipment off or on. Read below for more information about advanced
features of this facility.
General Information
Using Graphing for Evaluating Environmental Control and Troubleshooting Equipment Failure
By Rob Eddy, Plant Growth Facility Manager
*Note: Graphs are MS Excel [.xls] format. Files open in new window.
Each of the twenty-four 108 m2 (1200 ft2) greenhouses at the Purdue HLA plant growth facility is
environmentally controlled using sensors, microprocessors, and weather station. A microprocessor
is dedicated to each greenhouse, and all 24 zones are networked to a host computer for remote control
and monitoring using Priva Office version 2.14 and Priva Precision Graphs version V1.10 software.
The purpose of this article is to provide curators without computerized environmental controls with
information they could use to justify such an investment. Similar data and graphs might be generated on
other environmental control systems such as Argus, Q-Com, Micro-Grow, Wadsworth and Seimens. The graphs
presented are not how they appear on our computer screen, but simplified for sake of this publication.
The graphing capability of the software has allowed us to better program the heating, cooling and shading
of our greenhouses. Greenhouse environment data, weather and equipment usage are logged and can be graphed
or displayed as in spreadsheets.
A picture does seem to be worth a thousand words. We conducted a power outage simulation in an empty
greenhouse on a very cold night (Fig. 1), allowing us to plan response time needed to avoid catastrophic
plant loss. We were able to compare motorized shade cloth closing under two programs, one using light
level as the trigger for movement, and another using greenhouse temperature (Fig. 2). We also fine-tuned
our programming based on graphs comparing changes in heating stages (Fig. 3).
Unexpected to us was how graphing helped determine equipment failure. This was sometimes obvious, as
in the case of an equipment failure that resulted in an alarm being triggered (Fig. 4), but some equipment
failures that could eventually affect plant growth do not trigger an alarm. We learned to diagnose failed
heating stages by the "signature" of the temperature graph (Fig. 5). Certain signatures became evident for
failing sensors as well (Fig. 6), such as the sudden drop in measured humidity by 30% that seemed
thermodynamically impossible. Sometimes a device is not operating correctly though it appears to work
visibly. For example, a perimeter heating valve's handle was moving as if it was closing and opening, but
a graph of water temperature showed that water was passing through it when in the closed position (Fig. 7).
These greenhouse valves are ten feet off the floor and difficult to reach; a quick scan of the graphs
allowed us to find other defective ones in literally just a minute.
Finally, the graphing allows us to confirm when irrigation and photoperiod cloth closing were performed by
slight yet measurable effect on environment (Fig. 8). This can help diagnose causes of plant stress.
Using the graphing capability, we learned how to respond to temperature alarm situations, improve
environmental control, and take better care of our facility equipment. Most importantly, it has helped
us grow better plants. This has improved our success toward our department’s research, teaching and
outreach mission.