Integration of wireless sensor networks into automatic irrigation scheduling of a center pivot

Authors: O`Shaughnessy, Susan; Evett, Steven - Steve

Submitted to: Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE)
Publication Type: Proceedings
Publication Acceptance Date: 6/10/2008
Publication Date: 6/29/2008
Citation: Oshaughnessy, S.A., Evett, S.R. Integration of wireless sensor networks into moving irrigation systems for automatic irrigation scheduling. Proceedings of the American Society of Agricultural and Biological Engineers International (ASABE).June 29-July 2, 2008 Providence, Rhode Island. Paper No.083452. Available: http://asae.frymulti.com/azdez.asp?search=1&JID=5&AID=24796&CID=prov2008&v=&i=&T=1.

Interpretive Summary: Two wireless sensor networks were installed in a cotton field and on a center pivot to test the feasibility of using wireless infrared thermocouples as part of an integrated system to automatically schedule irrigations. Each wireless network contained a base coordinator that was physically linked with an embedded computer installed at the pivot. The sensor network on the pivot arm was able to mesh-network or use the other sensors on the same network as routers to establish a pathway to send and receive data to and from the base coordinator. Communication for the sensor network located on masts in the field, above the crop canopy, was only directed from the coordinator to the targeted sensor and back to the coordinator (non-mesh networking). The reliability, advantages, and disadvantages of both networks were compared to one another. Temperature readings of the crop canopy, sensor body, and the ambient air were briefly analyzed in the context of providing adequate temperature ranges for calibrating purposes. The non-mesh network performed more reliably than the network on the pivot, however, without mesh-networking capabilities, the sensors on the pivot arm demonstrated degraded performance due to interference from the pivot's steel towers and trusses. Data loss due to interference and calibration methods affected irrigation scheduling. However, recent upgrades to the radiofrequency modules by the manufacturer, improvements in calibration methods, and an algorithm to interpolate "lost" data have the potential to improve the reliability of mesh-networking sensors in areas located among farm machinery.

Technical Abstract: A six-span center pivot system was used as a platform for testing two wireless sensor networks (WSN) of infrared thermometers. The cropped field was a semi-circle, divided into six pie shaped sections of which three were irrigated manually and three were irrigated automatically based on the time temperature threshold method. One network was mounted on masts fixed to the pivot arm (Pivot-WSN) and was programmed with mesh networking firmware. The second wireless network was comprised of sensors programmed with non-mesh firmware and was deployed in the field (Field-WSN). Our objectives were to:(1) compare the performance of a mesh and non-mesh networking system of wireless sensors on a center pivot platform; (2) investigate the relationships between crop canopy, sensor body and air temperature; and (3) investigate automatic irrigation scheduling using data from wireless sensor networks. The Field-WSN outperformed the Pivot-WSN; data packet retrieval was more than 90% successful for 93% of the growing season using the non-mesh networking firmware for the WSN established in the field, but the Pivot-WSN performed only 70% of the time at this same level of success. Temperature differences between the body temperature of the infrared thermometer and crop canopy varied as much as -5.1 and 7.6 degrees C. Transmission loss and incorrect calibrations of the wireless sensor modules affected irrigation scheduling throughout the season. However, post-experiment improvements¬software upgrades and memory expansion of the RF module (by the manufacturer), changes to the calibration protocol, and an algorithm to interpolate the values of non¬captured data are expected to improve the overall performance of the wireless network systems and automatic irrigation scheduling for the upcoming growing season.