The Robots are coming
Robotics in Ag is now, not the future – Are you keeping up?
This is the third post of five about the “Alien Invasion” of Agriculture by outside enterprises with useful technology.
Electronics in field crop agriculture addresses very common issues:
1) “Where” – are crops, unwanted plants (“weeds”), and boundaries
2) “When” – is a good time for tasks and decisions
3) “How” – can tasks be performed throughout a crop cycle (and the land)
4) “Who” – can do what needs to be done
5) “What” – leverage from data and rules
In our last release we answered “Why” – because it makes economic and cultural sense.
Let look at an example of Precision Agriculture for field crops in an actual product offering and it’s answers to the issues. Most of the examples come from John Deere’s 8$ field equipment series with other features coming from competitors.
“Where” is an extension of existing automation that helps extend farmers’ productivity. In current driving automation having plotted a field the vehicle can drive itself with a farmer in the cab as oversight and control. This has extended staff availability because older, disabled, or inexperienced staff can operate the equipment with less skill. Now this is extended to automation understanding “where” (are crop plants, unwanted plants, geographic features) so that seeds can be placed in precisely the correct spacing, fertilizer/weed killer only goes where/when needed, and harvesting/hauling can be directed autonomously. The values of “where” (seeds, crop, weeds) is economically valuable to increase yield by dense planting, reduce inputs (water, fertilizer, herbicide, chemicals) by up to 80% (claimed), remove weeds (multiple methods), and reduce passes to prepare/clean land.
“When” is critically important to productivity. Automation is frequently effective day or night (weather and terrain permitting). Autonomous equipment can carry its own light, operate until human refills are needed (fuel, seed, chemicals, emptying), and extend the farming ‘day’. Sensors can look at soil, plant, and product conditions to act when needed. For a high value crop the fuel and equipment time for highest value harvest may require multiple passes – previously impossible during only daylight. Missing a critical timing window to plant or harvest can yield (thus money) by 1% per day. Running autonomously day and night at harvest can improve yield (sensing what’s at peak desirable ripeness), volume (more hours of operation), and information (what grew where and how well).
“How” is a change to millennia of farm practices. Each time period of the farm crop cycle has many different tasks performed first by hand and now by machine. The basic task of weeding (eliminating competition from other plants to the current crop (including undesirable volunteers from last year’s crop)) goes from manual labor/chemical mass spraying to automation (some hauled behind the John Deere equipment that is navigating as needed). The future automation might be pulling by mechanical hands to zapping with laser light. A basic task that is performed efficiently (no new labor input), consistently (rules and processing work the same every time unlike people), and tirelessly (within the limits of fuel, chemicals, and electrical power). A scale for this is the 30-meter wide attachments to extend the reach of a single pass down a field.
“Who” is an issue answered in unexpected ways. Agriculture has always been a capital (investment in land, crop, growing) and labor dependent industry. Farm equipment increased the productivity of labor and reduced peaks and valleys of demand. Electronics (“self-driving”) has more nuanced implementation. Unlike self-driving road vehicles farm field equipment is on very well known plats of land with few dynamic obstacles and a constrained set of objects in view. The “who” is No one. The John Deere product autonomously drives a field with No one in the equipment. If the equipment’s vision features don’t understand/recognize the objects in view the option to automatically connect the view with a remote call-center that takes action (or continues) without involving the farm. If something requiring local action an outbound notification to a smartphone is used. To increasing the productivity of labor the John Deere automation is directed to timeliness, efficiency, and improving the quality of life of farmers.
“What” is a new exploitation of data. A farmer intimately knows fields and conditions local to the crop. John Deere’s product gathers data (on activities, inputs, and outputs) and sends it off to “The Cloud” for processing as process data into management information, rules (for controlling and managing the equipment on a specific data), and recommendations (what and how to do it). Highly specific data can be combined with highly specific “Big Data” experiences to determine when, how, where, and who needs to take what actions. The productivity from deep knowledge of the farmer and county extension agent are codified into actionable plans. The plans can be performed with rules with different skill levels and rules. Just as ERP software can work schedules in factories the future “what” represented by farm data will change and operate farm operations. Shared utilization of expensive equipment is accomplished by schedule optimization across multiple properties and crops. Data and rules enable sharing equipment Instead of each farm or farmer needing its own set of equipment. This is a throwback to many operations of almost a century ago when farm equipment for land preparation or harvesting was simply too expensive for individual operations. From an environmental standpoint if automated tillage eliminates burning off land after harvest many benefits flow from the expense of automation on many crops.
The Industrial Revolution changed work from a skilled craft with large amounts of labor into the global production supply chains we have today. The Precision Farming future will focus the same styles of productivity improvements at an accelerated rate into field agriculture. In our next release we’ll consider the implications.
If you’re interested in more examples of EkaLore’s Alien Invaders – www.ekalore.com/alien-invaders
If you’d like to talk with us, set up a short call with a Senior Analyst – www.ekalore.com/contact
Comments