You do not have permission to edit this page, for the following reason:
Image: Upload an image that represents the content of the chapter. This should be a jpg or png image 600x200 pixels.
Upload file
Social Media Image: Optionally you can upload a large svg, jpg or png image that will represent this project on social media. The image should ideally be 1.91:1 ratio (1200 x 627 pixels).
Point of Contact: Enter the name of the point of contact for this chapter. This field will autocomplete with the names of people known to the system. If not known add them.
Josh Seidemann
Authors: enter all the authors and contributors to this chapter separated by comas.
Blueprint: enter the blueprint under which this chapter is listed
Agriculture
NIST Sectors: list all the NIST sectors where this chapter is relevant
Buildings Cybersecurity and Privacy Data Education Public Safety Rural Smart Region Transportation Utility Wellbeing Wireless Agriculture Broadband Resilience Introduction Informational Cybersecurity Privacy Energy Waste Water Smart Buildings
Summary: Provide a summary of the chapter
Precision farming is a type of smart agriculture that uses technology such as GPS, sensors, and mapping tools to gather data on soil conditions, weather patterns, and crop growth. This data can then be used to make more informed decisions about planting, fertilization, and harvesting. The goal of precision farming is to increase yields while minimizing waste and environmental impact by applying inputs such as seeds, fertilizer, and pesticides at the right time and in the right amount. Precision farming can also include the use of precision farming equipment such as auto-steer tractors, yield monitors and variable rate application equipment which helps farmers to apply inputs in a more precise and efficient way. Overall, precision farming is a data-driven approach to farming that uses technology to optimize crop production and improve efficiency.
Free text: Write the chapter using Mediawiki markup language.
==Technologies== Precision farming uses a variety of technologies, including: *'''[[Geographic Location Systems]]''': These technologies are used to map fields and track equipment in real-time, allowing farmers to precisely plan and execute planting and harvesting operations. *'''[[Sensor Technology]]''': Various types of sensors, such as soil moisture sensors and crop sensors, are used to collect data on soil conditions and crop growth, which can then be used to optimize irrigation and fertilization. *'''Drones and aerial imaging''': Drones equipped with cameras and other sensors are used to gather detailed information on crop health and growth, as well as to survey fields for pests and diseases. *'''Variable rate technology''': This technology allows farmers to apply inputs (such as fertilizer, seed, and pesticides) at different rates across a field, based on data gathered by sensors and other technologies. *'''Automation and robotics''': Automated tractors, self-driving vehicles and other forms of automation and robotics are increasingly being used in precision farming, allowing farmers to more efficiently and effectively manage their operations. *'''Artificial Intelligence and Machine Learning''': AI and ML are increasingly being used to analyze the data generated by precision farming technologies, to help farmers make more informed decisions and optimize their operations.