New Iron: Intelligent Machinery Technologies for 21st Century Farming
|Dr. Qin Zhang
Department of Agricultural
and Biological Engineering
Agricultural mechanization has greatly improved the productivity of crop production and helped farmers producing more foods on less farming land to feed many more people, and therefore is ranked as one of the greatest engineering accomplishments in the 20th century. Recent advances in agricultural production and agricultural machinery technologies are moving crop production from a state of broad scale mechanization to a state of mechanization with precision. In addition, wide-spread use of computers in agriculture is further evolving crop production into an information-based production era. However, such technology advancements also create new challenges for 21st century farming. Some of the most important ones are mechanization with precision, multi-task implementation, and sustainable farming.
The key to conduct large-scale mechanized farming with precision is to collect site-specific field data, process such data in real-time, then convert the obtained information into machine maneuvering instructions for mechanized field operations. To implement multi-tasks on machinery at field operations, “on-the-go” operation management is the key. Multi-tasks management, machinery automation and X-by-wire maneuvering can form automated “on-the-go” operation management. And at the bottom line, sustainable farming is the core of all new challenges because without affordable and safe new farming technologies to allow farmers to conduct profitable productions, it is unthinkable to make farming in the 21st century sustainable. To address those challenges, intelligent machinery technologies, also called “new iron” technologies, are desirable. Researchers from the Department of Agricultural and Biological Engineering have conducted leading-edge research on developing such “new iron” technologies, including on-board crop health sensing, sensor-based variable-rate nitrogen application, automated machinery guidance, active rollover prevention, condition-based equipment maintenance, and panoramic mapping of virtual field, for meeting the increasing demands on machinery functionality and performance needed to perform effective large scales of mechanized farming with precision.
For example, steering tractors following crop rows in field to perform various operations is a very tedious job. To solve this problem, UI researchers have developed automatic guidance systems to steer tractors following crop rows in performing required operations. One of the most recent accomplishments from this research was the use of a stereovision camera to find pathways for tractors travelling in the field, just as a human operator uses his/her eyes to find the way (Fig. 1). While these “two eyes” can locate crop row locations, the stereovision camera can also be used to detect the field terrain which can provide the critical information for tractor rollover prevention. Because the most effective way to eliminate tractor rollover-caused fatalities is to prevent the rollover from occurring, an ingenious “two-eye” camera to estimate both the field terrain and the tractor motion status for providing tractor rollover prevention is being investigated. Figure 2 shows how this stereovision-based tractor active rollover prevention system detects the terrain profile in front of the moving tractor to provide a safety watch to prevent tractor rollover from happening by means of limiting tractor maneuverability for safety.
Fig. 1. Illustration of a “two-eye” based crop row detection system
Fig. 2. Illustration of a stereovision-based active rollover prevention system