Title: Wireless tracking of cotton modules. Part I: Automatic message triggering Authors
|Sjolander, A. -|
|Thomasson, J. -|
|Ge, Y. -|
Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 26, 2010
Publication Date: January 21, 2011
Citation: Sjolander, A.J., Thomasson, J.A., Sui, R., Ge, Y. 2011. Wireless tracking of cotton modules. Part I: Automatic message triggering. Computers and Electronics in Agriculture. 75:23-33. Interpretive Summary: With rising costs and stagnant prices, one way agricultural producers can improve profitability is by implementing precision-agriculture practices. To do this, detailed records must be kept of the spatial and temporal variability of various aspects of production. An initial step in this process is to create a yield map of the field or area in question. For cotton production this capability has been realized with the creation of onboard yield monitoring systems. If fiber-quality maps are also available, revenue maps can be generated and help the producer to determine which parts of fields require higher or lower levels of agricultural inputs. Going one step further, profit mapping would allow cotton producers to see specific areas within their fields that are returning the highest or lowest profits. To this end, a wireless module-tracking system (WMTS) was recently developed to map profit across a cotton field, which enable producers to see where money is being made or lost on their farms and to implement precise field management practices to ensure the highest return possible on each portion of a field. But automation of the system is required before it will find practical use on the farm. The objectives of this research were (1) to make the wireless module tracking system capable of automated wireless message triggering, and (2) to make the system compatible with multiple instances of similar machinery (i.e., more than one harvester, boll buggy, and/or module builder) in a given field. Objective 1 was discussed within this article. An inclinometer and two load cells were incorporated into the wireless module-tracking system for cotton in order to achieve the first objective of this research: automating the triggering of wireless messages by the WMTS. Tests were conducted near College Station, TX and Lubbock, TX in 2008 to evaluate the performance and reliability of the automated WMTS. The final test near Lubbock proved that sensor-based wireless-message triggering worked according to design. When the harvester basket was emptied, the system automatically sent a wireless message from the harvester to the module builder in order to track the harvest location of each module. Cotton fiber-quality maps were successfully made based on module tracking done by the automated system.
Technical Abstract: The ability to map profit across a cotton field would enable producers to see where money is being made or lost on their farms and to implement precise field management practices to ensure the highest return possible on each portion of a field. To this end, a wireless module-tracking system was recently developed, but automation of the system is required before it will find practical use on the farm. In Part 1 of this report, research to develop automatic initiation of wireless messages is described. In Part 2, research to enable the system to function with multiple harvesting machines of the same type in the same field – a common situation in commercial cotton farming – is described along with testing of the entire automated wireless module-tracking system. To automate wireless-message triggering, a sensing and control system was added to a harvester to automatically indicate when the machine is dumping a basket load of cotton so that wireless messages can be automatically sent from the harvester to subsequent field machines without human intervention. This automated system was incorporated into the existing wireless module-tracking system, field tested, and it ultimately operated as designed, without human intervention. Linking data collected with this system together with cotton classing data enabled the creation of fiber-quality maps.