Growing up, I often heard stories from my dad, mamaw, and papaw about their life on a farm in Clinton, Tennessee. They spoke of their challenges, hard work, and joy when their crops flourished. As I reflect on their experiences, I can't help but think about how modern technologies could have transformed their farming practices.
Today, the intersection of drones, the Internet of Things (IoT), computer vision, edge computing, embedded visual analytics, and large language models is revolutionizing the agriculture industry. Drones with high-resolution cameras and sensors can fly over fields, capturing detailed images and data about crop health, yield, soil moisture, bio-mass, and pest infestations. This information is transmitted to edge devices or via satellite connectivity (thanks to Starlink!) and analyzed using advanced computer vision algorithms and embedded analytics.
Farmers can now access real-time insights about their crops, enabling them to make data-driven decisions about irrigation, yield, fertilization, and pest control. They can identify areas of their fields that need attention and take targeted actions to optimize crop growth and yield. This precision agriculture approach saves time and resources and helps minimize the environmental impact of farming.
In the study "The Rise of the Drones: How Unmanned Aerial Vehicles Are Revolutionizing Agriculture" by Dmitry Arseniev, Ekaterina Shlykova, and Mikhail Zheno (1) - the benefits of drones are incredible:
"The use of drones in agriculture has the potential to increase crop yields by up to 20% while reducing water and pesticide usage by 40% and 30%, respectively. By providing farmers with real-time data on crop health, soil moisture, and pest infestations, drones enable precision agriculture practices that optimize resource utilization and minimize environmental impact."
Moreover, the use of IoT sensors in agriculture extends beyond drones. These sensors can be placed in the soil to monitor moisture levels, temperature, and nutrient content. They can also be attached to farm equipment to track usage and preventive maintenance needs. This data is collected and analyzed using cloud-based databases such as Snowflake or Databricks, elements of visual analytics, and LLMs, providing farmers with a comprehensive view of their operations.
Large language models can help reduce potential issues with data literacy. They combine research models with real-world data, providing a dedicated, personal co-farmer. They can also help translate across a multitude of languages.
Reflecting on my papaw's farming days, I can only imagine how these technologies could have helped him grow better crops. With the ability to monitor his fields remotely using drones and IoT sensors, he could have detected issues early on and taken corrective actions before they became significant problems. He could have optimized his irrigation and fertilization practices based on real-time data, ensuring that his crops received what they needed to thrive.
The intersection of drones, IoT, agriculture, computer vision, and embedded analytics transforms how we grow food. It enables farmers to work more innovatively, not more complexly, and to produce more with less. As we look to the future of agriculture, these technologies will undoubtedly play a crucial role in feeding a growing global population while protecting our planet's resources.
While chewing his favorite King Bee twist tobacco, I hear my papaw's voice say, "Well, that's pretty neat. You know Jeff, we are only in the first inning," while spitting tobacco juice on the ground. For those unfamiliar with baseball lingo "first inning" - we are in the early stages.
My family would have been amazed by the possibilities and proud to see how far we've come. They would have also loved a new source of income from their data. However, papaw and mamaw would have needed help with digital wallets!
Sources
(1) Title: "The Rise of the Drones: How Unmanned Aerial Vehicles Are Revolutionizing Agriculture" Authors: Dmitry Arseniev, Ekaterina Shlykova, and Mikhail Zhenov Journal: IEEE Access Year: 2021 DOI: 10.1109/ACCESS.2021.3079887
Inspirational Sources (articles, blogs, posts, or conversations that I had recently that had some input or idea spark for this newsletter's topic):
Barry Chaiken Bridget Cogley Bruno Aziza Donald Farmer Eric Schummer Liam Brody Phil Walton Phil Santoni David Chen Todd Talkington Denny Lee Raleigh Murch James Luby Francois Ajenstat Dad, mamaw, and papaw Huckaby
Also posted on ChangeWave: Riding the Analytics Tide to Business Evolution - a LinkedIn newsletter:
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