The Future Fusion Of Machines, Models And Sensors In Precision Agriculture

There is a quiet, technical revolution occurring in agriculture that is going to impact the field of precision agriculture in the very near future. Lacking good terminology, I will call this revolution the “fusion” of machines, sensors and models. This fusion is being borne out of the explosion of data being realized through the integration of information, computer and communication technologies with traditional hardware and analytical thinking. It is going to affect the very nature of decision-making in crop management and every device and machine engaged in field production. Before elaborating on the “fusion,” I will briefly review the individual evolution of machines, sensors and models.

Since the beginning of agriculture, man has sought devices, such as tools, pumps and plows, to improve the efficiency of crop production while reducing labor and conserving resources. These devices were first operated by hand, later pulled by animals, and lastly powered by engines. The transformation of agriculture by machines in just the last 100 years has been truly amazing. As reported in a 2005 USDA bulletin entitled “The 20th Century Transformation of U.S. Agriculture and Farm Policy,” about 41% of the workforce — 22 million work animals and a few, newly invented, gasoline-powered tractors — were involved in agriculture at the start of the 20th century. By the start of the 21st century, slightly less than 2% of the workforce, 5 million tractors and a few work animals were active in agriculture. During this 100-year transformation, the number of farms in agriculture decreased by 63% while the average farm size increased by 67%.

Sensor Upgrades

A sensor is a device that converts a physical stimulus into an action or signal. Sensors have a history of development similar to machines. Beginning as simple devices that recorded a change in sound, motion, heat, pressure, light or other physical phenomena, sensors quickly evolved over the last 100 years into sophisticated arrays and networks. Sensors are ubiquitous in everyday life. They automatically open entrance doors in businesses, control lighting and heating in homes, detect the amount of fuel in cars and set off alarms in case of fire or gas leaks. Sensors can be placed locally or be remote, such as on aircraft or satellites.

Several recent advances have made sensors more applicable to agriculture. First, they have been coupled with radio communication. Today, a sensor placed in the field can measure some physical phenomenon, convert that measurement into an electronic signal and then transmit that signal with electromagnetic waves in the radio frequencies to a distant base station. This sensed measurement and its transmission by radiowaves can be done automatically, freeing up the need for someone to be on-site to retrieve recorded data.

The second advance in sensors is miniaturization. Sensors are gradually becoming smaller and smaller while still performing as their larger counterparts. Miniaturization is possible due to the use of new materials that require less volume, reduction in the size of electronic circuits and the exploitation of newly discovered physical, chemical and biological properties. Miniaturization, at or below the molecular scale, is called nanotechnology.

A third advance is the efficiency and cost reduction in the manufacturing of sensors. Sensors are becoming cheaper to make, which allows for more of them to be placed in the field at the same cost.

The fourth and last advance is the ability to combine sensors in networks. Sensor networks through their measurement and transmission of signals in spatial arrays over time can create a dynamic, two-dimensional and even a three-dimensional picture of some physical phenomenon.

A model is the mathematical representation of the physical world. Through parameters and equations, models mimic or “simulate” the properties and processes of some physical system. Models have existed on paper for more than 100 years, but their modern-day identity is linked to computers. Computers, through program code and machine instructions, can computationally execute the mathematical equations defining a model many times faster than a human can do by hand. Computer-based models can input and process data at mind-boggling rates. Furthermore, model-processed data or output can be presented in many visual forms, such as graphs and maps in support of management decision-making.

The Coming Fusion

With this background, it is easy to appreciate the fusion of machines, sensors and models. In the coming revolution, there will be a virtual “command” center running farm operations. Sensors flying on aircraft and satellites overhead in conjunction with those judiciously placed in fields and on tractors will measure physical, chemical and biological properties important to crop production. These sensor-based measurements will be converted to electronic signals and transmitted by radio to the command center. Base computers located in the center will receive the transmitted signals and deliver the data embodied in them via the Internet to models in the cloud. The models will process the data and pass back products in the form of tables, graphs and maps, depicting the state and changes in environmental and biological phenomena impacting crop development and growth. The same models will pass back recommendations on courses of action given status of the phenomena monitored in the field.

For example, a plant epidemiological model, inputting data collected in a field, may predict the incidence and severity of a disease important to crop yield. The model may recommend the timing and amount of a fungicide to minimize yield loss and control the spread of the disease. A farm manager would review the model-generated products and recommendation, and then choose a control tactic based on past experience and the available resources on hand.

If the choice is a fungicide as recommended by the model, a precision agriculture program could generate a variable-rate application map. This map would specify the rates of a chosen fungicide to be applied on a field according to the pattern of disease interpreted from sensor data. The variable-rate application map could be delivered wirelessly to spray equipment and, with GPS, guide the proper placement of the fungicide across a field. The fungicide application would change the progress of the disease, which would be indirectly monitored by sensor-recorded, environmental conditions. In a continuous cycle of sensed data, model processing of data and the incorporation of model products into precision agriculture programs, information would be generated to support management decision making during a growing season.

As precision agriculture evolves, it will play an important role in driving the demand for the fusion of machine, sensors and models. It will provide programs that allow a farm manager to act on model products. The same programs will support management decisions by guiding the operations of machines.

The new tech development reported in this issue represents small steps toward the realization of this fusion. With each new development, precision agriculture, along with machines, sensors and models, will increasingly provide decision-makers with information at an unprecedented scale and level of detail.

Leave a Reply

3 comments on “The Future Fusion Of Machines, Models And Sensors In Precision Agriculture

Data Management Stories
Data ManagementAgritechnica 2017: Executives Discuss Europe Ag Tech Adoption
December 6, 2017
While North American growers slog through yet another season of depressed farm incomes and commodity markets, across the pond it’s Read More
Bitcoin-for-Agriculture-Source-TheJavaCoincom
Data ManagementWill Bitcoin Work in Agriculture?
December 5, 2017
If you checked the Internet lately, you’ve probably seen the words, Bitcoin, cryptocurrency, and blockchain. I won’t describe them in Read More
Harvested-Corn-Field-Clouds
Data ManagementWeather Services Advance Precision Agriculture
December 4, 2017
Some estimates suggest over half of growers’ activities are impacted by weather conditions, from field workability to fertility management to harvest Read More
Longford-Silt-Foam-map
Data ManagementUnderstanding Precision Farming and Soil Morphology
December 4, 2017
The USDA Soil Conservation Service, now Natural Resources Conservation Service, has been charged with creating the country’s soil survey. This Read More
Trending Articles
Harvested-Corn-Field-Clouds
Data ManagementWeather Services Advance Precision Agriculture
December 4, 2017
Some estimates suggest over half of growers’ activities are impacted by weather conditions, from field workability to fertility management to harvest Read More
Wheat-an-oats-Daniel-X-ONeil
Data ManagementWill Open-Source Finally Unlock Ag Technology’s Potential?
November 28, 2017
To Aaron Ault’s eyes, ag technology right now is something like a walled garden — not unlike the Microsoft of Read More
Africa/Middle EastPERSPECTIVE: Is Bayer’s Highly Anticipated xarvio App the Next Uber for Ag?
November 22, 2017
As many of our CropLife IRON readers might know, every summer at MAGIE we award the most popular product featured Read More
Used Combine
Service ProvidersFinding New Precision Ag Opportunities in Older Equipment
November 15, 2017
Whether to buy new or used equipment has been and continues to be an important topic for growers. When it Read More
Blue River Tech See and Spray prototype in CA
Business ManagementIs the Agtech Startup Boom Over?
November 13, 2017
In the past few months there has been a flurry of acquisitions of agtech startups by major players in the Read More
Spray Drift
Business ManagementProtecting Your Business with Ag Data: What Dicamba Can Teach Us (Guest Column)
November 9, 2017
All over the country, in ag communities large and small, farmers are reporting crop damage, neighbors are fighting, lawsuits and Read More
Latest News
Claas RTK Field base
Industry NewsCLAAS Taps Syncron for Cloud-Based Spare Parts Manageme…
December 11, 2017
Syncron, a provider of cloud-based after-sales service solutions, today announced CLAAS, a manufacturer of agricultural machinery, has selected Syncron Inventory – Retail Read More
Farmer and computer
Service ProvidersPrecision Agriculture Writers Wanted To Join Our Team i…
December 10, 2017
About The Opportunity: PrecisionAg.com is looking for people to join our team in 2018 and submit original content to our Read More
american-robotics-Scout-Drone
DronesAmerican Robotics Unveils Fully Autonomous Drone System…
December 7, 2017
American Robotics, an industrial drone developer specializing in agricultural automation, has unveiled its flagship product Scout. It is a self-charging, Read More
Industry NewsJohn Deere Upgrades Generation 4 Display Capabilities
December 6, 2017
John Deere has introduced its latest advanced guidance and machine data sharing technology with the addition of three new AutoTrac Read More
Grower-Field-iPad-Connectivity-Photo-Credit-VLab
Business ManagementOpinion: Agtech Boom Is Yet To Come
December 6, 2017
Many agronomists, farmers, and VC groups monitoring the agtech world are proclaiming the startup boom is over. Investments are down, Read More
Data ManagementAgritechnica 2017: Executives Discuss Europe Ag Tech Ad…
December 6, 2017
While North American growers slog through yet another season of depressed farm incomes and commodity markets, across the pond it’s Read More
Bitcoin-for-Agriculture-Source-TheJavaCoincom
Data ManagementWill Bitcoin Work in Agriculture?
December 5, 2017
If you checked the Internet lately, you’ve probably seen the words, Bitcoin, cryptocurrency, and blockchain. I won’t describe them in Read More
Vineyard weeding Robot-Naio-Technologies
Robotics/Labor SaversRobots Are Coming for Your Crop Protection (and Other I…
December 5, 2017
The market for agricultural robotics market is small but burgeoning, and their impact is likely to be quite a bit Read More
John-Deere-Connect-Mobile
Service Providers10 New Mobile Apps for Precision Agriculture
December 5, 2017
Ag professionals continue to reap the rewards of new smartphone apps. And perhaps no segment of farming is benefitting more Read More
On-Farm-Trials-Brazil
AmericasOn-Farm Trials in Brazil: The Way to Improve Agronomic …
December 4, 2017
The idea of using on-farm trials to gather data about the performance of any crop input has been in place Read More
Harvested-Corn-Field-Clouds
Data ManagementWeather Services Advance Precision Agriculture
December 4, 2017
Some estimates suggest over half of growers’ activities are impacted by weather conditions, from field workability to fertility management to harvest Read More
Longford-Silt-Foam-map
Data ManagementUnderstanding Precision Farming and Soil Morphology
December 4, 2017
The USDA Soil Conservation Service, now Natural Resources Conservation Service, has been charged with creating the country’s soil survey. This Read More
Spensa platform
Industry NewsSpensa Adds TerrAvion Aerial Imagery
December 4, 2017
Spensa Technologies announces today its partnership with TerrAvion, a California-based start-up that provides aerial imagery for agriculture. As customers of Spensa Read More
Industry NewsCase IH Announces Updated AFS Data Transfer Capabilitie…
December 4, 2017
Case IH has announced seamless data transfer capabilities between its Advanced Farming Systems (AFS) Connect farm management system and six Read More
Data ManagementCropLife: FBN CEO Appears at ARA 2017 Conference (Recap…
December 2, 2017
Right on the heels of news it has raised $110 million in a Series D funding round, Farmer’s Business Network Read More
Farmers Business Network, FBN Procurement
Data ManagementFBN Raises Record $110 Million Series D Venture Capital…
December 1, 2017
Farmers Business Network announced a $110 million Series D funding round, led by funds and accounts advised by T. Rowe Read More
Wheat-an-oats-Daniel-X-ONeil
Data ManagementWill Open-Source Finally Unlock Ag Technology’s Potenti…
November 28, 2017
To Aaron Ault’s eyes, ag technology right now is something like a walled garden — not unlike the Microsoft of Read More
Monash-University
Australia/New ZealandNew Ag-Tech Facility in Melbourne to Explore Use of AI,…
November 27, 2017
Monash University is establishing an ag-tech facility in Melbourne’s southeast with the vision to innovate new smart farming techniques including Read More