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Precision Agriculture Technology Survey

Key technologies

Precision agriculture, also known as precision farming or precision ag, leverages modern technology to optimize crop yield and efficiency. This approach is rooted in the use of various technologies to monitor and manage agricultural operations with a high degree of specificity, down to individual plants or square feet of soil. The following is a survey of some key technologies used in precision agriculture:

Geographic Information Systems (GIS)


GIS is a key set of tools for preciison agriculture. It is a tool for gathering, storing, verifying, and displaying information about positions on the surface of the Earth. With the help of this technology, which combines different types of data, users can view, comprehend, query, interpret, and visualize data in ways that reveal relationships, patterns, and trends using maps, reports, and charts. Farmers can use remote sensing technologies to map their fields in great detail and use GIS platforms to overlay different types of data (like crop yield and soil composition) to understand spatial patterns and relationships. GIS technologies lay the groundwork for better decision-making. Farmers can enhance processes and outcomes by improving the accuracy and resolution of GIS data and by reducing the time between data collection and action.

Global Positioning System (GPS)


GPS technology is crucial for many precision agriculture applications. It allows machinery to follow pre-determined paths with high accuracy, facilitates precise mapping of fields and crop yields, and enables targeted application of fertilizers and pesticides. These systems reduce operator fatigue, increase precision in field locations, save money by reducing over- and under-application of sprays, and improve the seeding of field crops.

Global Positioning System (GPS) is a satellite-based navigation system made up of a network of 24 satellites placed into orbit by the U.S. Department of Defense. GPS was originally intended for military applications, but in the 1980s, the government made the system available for civilian use.

GPS works in any weather conditions, anywhere in the world, 24 hours a day, with no subscription fees or setup charges. The U.S. Department of Defense (USDOD) originally put the satellites into orbit for military use, but they were made available for civilian use in the 1980s.

GPS (Global Positioning System) and GNSS (Global Navigation Satellite Systems) are terms often used in the field of geolocation technology, but they represent different concepts. GPS is a specific system of satellites and ground stations developed by the United States to provide geolocation and time information to GPS receivers anywhere on Earth where there is an unobstructed line of sight to at least four GPS satellites. On the other hand, GNSS is a general term that encompasses all global satellite positioning systems, including not only the United States' GPS but also Russia's GLONASS, the European Union's Galileo, China's BeiDou, and others.

BeiDou is China's contribution to the GNSS family. Initially designed as a regional system, BeiDou expanded its reach to provide global coverage. The system offers two kinds of services - an open service, available to anyone and providing a positioning accuracy of about 10 meters, and an authorized service for higher accuracy, mainly used for government and military applications.

GLONASS, Russia's GNSS, was fully operational as early as 1995. Like BeiDou, GLONASS offers a standard precision service for civilian use and a high precision service for military and government use. The standard service provides a positioning accuracy between 5 and 10 meters.

In addition to these systems, the European Union has developed its own GNSS known as Galileo. Operational since 2016, Galileo was designed to provide a high-precision positioning system upon which European nations could rely independently from American GPS, Russian GLONASS, or Chinese BeiDou systems. Galileo offers a basic service for civilian use, and a more precise, controlled service for military and official purposes.

The integration of multiple GNSS, including GPS, BeiDou, GLONASS, and Galileo, improves overall accuracy and reliability by increasing the number of satellites available to users, especially in challenging environments where the view of the sky is obstructed. Many modern GNSS receivers are capable of using data from multiple systems simultaneously.

There are two primary categories of GPS technology

Standard GPS: Standard GPS is the most basic type and it's what most consumer devices use. It uses the data from the GPS satellites directly and can provide an accuracy of about 10-20 meters. Many modern devices like drones can access multiple GNSS systems to improve the accuracy and reliability of standard gps

Differential GPS (DGPS): This improves the accuracy of standard GPS by using ground-based reference stations to correct the satellite data. DGPS can provide accuracy within a few meters.


The two primary DGPS systems are:

Real-Time Kinematic (RTK) GPS: RTK, or Real-Time Kinematic, is a technique used to enhance the precision of position data derived from satellite-based positioning systems, primarily GPS. It uses measurements of the phase of the signal's carrier wave, rather than the information content of the signal, and relies on a single reference station to provide real-time corrections, providing up to centimeter-level accuracy.

Post-Processing Kinematic (PPK) is another high-precision GPS technology similar to RTK. However, instead of performing corrections in real-time, PPK stores the raw GPS data for post-processing after the data has been collected.

RTK solutions are often used in applications requiring high precision, such as surveying and precision agriculture. In precision agriculture, for example, they can be used for accurate mapping of fields, automated steering of farm machinery, and precise application of fertilizers and pesticides.

RTK functions as follows

  1. Signal Correction: Each GPS satellite sends out a signal that includes its location and the time the signal was transmitted. These signals are affected by atmospheric conditions, satellite and receiver clock errors, and orbital errors.

  2. Base Station: In an RTK setup, there's a base station (also known as a reference station) that stays in a fixed location. This base station receives the same signals from the same satellites as the roving GPS receiver (the one attached to the equipment you want to track). Because the base station knows its exact location (it's fixed), it can calculate the error in the signals it receives from the satellites.

  3. Correction Information: The base station then sends these error calculations to the roving GPS receiver. This is usually done over a radio link, but can also be done via the internet or a cellular network.

  4. Position Calculation: The roving GPS receiver applies these corrections to the signals it's receiving from the satellites, resulting in a much more accurate calculation of its position.

To set up an RTK system, the user needs the following:

  1. Base Station: This is a receiver placed in a known location. The base station calculates the error in the GPS signal and transmits this correction to the rover unit.

  2. Rover Unit: This is the receiver that moves around (e.g., on a tractor or drone) and uses the corrections from the base station to calculate its precise location.

  3. Data Link: This is the method used to transmit corrections from the base to the rover. Common data links include radios operating in the UHF band, the internet (via NTRIP), or a cellular network.

A user has multiple options for configuring an RTK system. They may use:

  1. Own Base Station: The user configures his or her own base station. This requires the purchase and maintenance of a base station and a data link (typically a radio), but it can be utilized at any time without requiring an external service. This is particularly useful in rural areas without cell service.

  2. Network RTK: An individual subscribes to a service that offers RTK corrections. Typically, this is provided by a network of base stations covering a wide area (a whole country or state, for example). This has the advantage that the user does not need to maintain their own base station and can frequently use cellular data for the data link. This service, however, requires a subscription fee and may not be accessible everywhere


Automation, Guided Tractors, and Robotics


From autonomous tractors to robotic harvesters and weeders, automation and robotics are becoming increasingly prevalent in precision agriculture. These technologies can improve efficiency, reduce labor needs, and perform tasks with a level of precision that would be challenging for human workers. Autonomous machinery and robotics are increasingly being used for tasks such as planting, irrigation, and harvesting. They can work around the clock, are highly accurate, and reduce the need for manual labor.


Autonomous Tractors


These are tractors that can operate without a driver in the cab. Companies like John Deere, Case IH, and New Holland have demonstrated autonomous tractors. These tractors use a combination of GPS, LiDAR (Light Detection and Ranging), and other sensors to navigate fields, avoid obstacles, and carry out tasks like planting, fertilizing, and harvesting.


GPS Guided Tractors


These tractors use GPS signals and auto-steering technology to follow pre-planned paths across a field with great precision, minimizing overlap and thereby saving fuel and time. Auto-steering systems can be retrofitted to existing tractors or included as part of a new tractor. Companies such as Trimble, Topcon, and Ag Leader offer GPS guidance systems for tractors.


Unmanned Ground Vehicles (UGVs)


These are smaller, specialized robots designed for specific tasks. Examples include Naio Technologies' weeding robots, which can mechanically remove weeds in row crops, and the Small Robot Company's three robots Tom, Dick, and Harry, which are designed for planting, weeding, and monitoring crops, respectively.


Robotic Harvesters


These robots are designed to automate the harvesting process. For example, companies like Abundant Robotics have developed robots capable of harvesting apples, while Agrobot has developed a strawberry harvester.


Crop Monitoring Robots


These robots monitor crop growth, health, and yield using a variety of sensors. For example, the TerraSentia robot developed by EarthSense can navigate through fields, collecting high-resolution data about crop health and development.

Variable Rate Technology (VRT)


VRT allows inputs such as seeds, fertilizers, and pesticides to be applied at variable rates across a field, based on the specific needs of different areas. This technology, often used in conjunction with GPS, can significantly enhance efficiency and reduce waste. VRA seeding technology allows farmers to adjust the amount of seed they plant based on the specific conditions of different areas within their fields. This can lead to more efficient use of seeds and higher crop yields. This technology allows farmers to customize the application of fertilizer, chemicals, and pesticides using GPS data. It can even be used to plant different types of seeds at different locations in a single pass of the tractor. VRT has relatively low ease of use and functionality because of the high cost of installing and maintaining equipment, and the specialized machinery required.


Yield Monitors


These technologies help farmers understand changing field conditions better. For instance, yield monitors mounted on combines can collect GPS coordinates, which can then be color-coded and mapped to show changes in crop yield across the field. Soil maps, meanwhile, collect core samples to show soil types, nitrate levels, and pH acidity readings.

Internet of Things (IoT)


IoT refers to the network of physical devices, vehicles, and other items embedded with electronics, software, sensors, and network connectivity which enable these objects to collect and exchange data. In agriculture, this could mean the connectedness of soil sensors, weather data, and irrigation systems, leading to more informed decision-making. IoT devices, such as smart sensors and connected machinery, generate real-time data about a wide range of parameters. This data can be analyzed to inform decision-making and enable predictive maintenance of equipment. Wireless sensors can gather data on a range of factors, from soil fertility to weather conditions, allowing for more precise management of crops.

Data Analytics and Machine Learning


Tools for data analytics play a crucial role in precision agriculture, transforming vast quantities of collected data into insights that farmers can use. These tools, which include software platforms and applications, analyze data from various sources, such as soil sensors, weather stations, satellite and drone imagery, and machinery telematics, using advanced algorithms and machine learning techniques. Among other parameters, they can interpret data on soil composition, plant health, microclimate conditions, and machine performance. These insights enable farmers to make informed decisions regarding seeding, irrigation, fertilization, pest control, and harvesting, thereby optimizing yields, reducing expenses, and minimizing environmental impact. Companies such as Farmers Edge, Granular, and The Climate Corporation provide precision agriculture with robust data analytics platforms. These platforms frequently offer user-friendly dashboards and can integrate with diverse farm hardware to facilitate precise, real-time decision making. As precision agriculture develops, so will these tools, which will incorporate increasingly complex algorithms, predictive modeling, and AI capabilities.

Conclusion


The adoption rates and benefits vary among these technologies, largely due to their ease-of-use and functionality. For instance, GPS guidance systems have high ease-of-use, while yield and soil maps have high functionality. VRT, on the other hand, appears to be low in both categories.


However, the adoption of these precision agriculture technologies is growing. In particular, VRT adoption has been increasing in corn, soybean, rice, and peanut production, indicating that the technology's ease of use and functionality might improve in the future. Large farms seem to adopt VRT more frequently, as it proves more cost-effective when applied to a greater number of crop acres.

Precision agriculture technologies are playing an increasingly important role in farm production. They provide valuable data on changing field conditions, allowing farmers to adjust their production practices accordingly. As these technologies continue to evolve and become more user-friendly, they are expected to become more widely adopted, leading to more efficient and sustainable farming practices.

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