This month marks the completion for summer internships around the United States. For me, as we speak, I’m gearing up for my final year at Monmouth University as I finish my Bachelor’s Degree in Computer Science (and continue playing as much tennis as I can).
Summers tend to fly by, whether you’re spending the time on self-care or project deliverables. I couldn’t be happier than to have spent my summer on the latter, focusing on a Climate FieldView™ feature project that will deliver a ton of value to farmers around the world by streamlining a small, but critical, part of the planting process.
I’m thankful that a number of our interns had the opportunity to get together several times over the course of the season. Seeing what other interns are up to broadens perspective and leads to insights on how to develop even more value for the business!
Most of what we talk about within Climate related to the value that FieldView™ and digital farming can provide is related to BIG data that comes from fields. When, how, and what was planted? When did you apply an input, and how much, and when and how much did you harvest?
These are important considerations, and it’s our job as computer scientists, engineers, and data scientists to dive deeper and find ways to answer pain points that our customers might not even know they have yet. Something that works okay as is, but if changed could drastically improve experiences across the board.
The above is what’s called a bag tag. This small piece of paper contains some really critical information that farmers need to keep track of. Information on the hybrid or seed planted – and other bits of data related to how the hybrid performs – is among the most important data a farmer can gather, and the basis for a lot of future insights that can impact future seasons.
Using Apple Vision technology, upcoming releases of the FieldView app for iOS will be able to automatically recognize much more information on these bag tags. This new service focuses on scanning bag tag barcodes first, rather than using optical character recognition to gather and input data. This is going to make the seed data management and hybrid inputting process so much easier, leading to a better experience with FieldView for our customers.
Higher quality data leads to more consistent and better insights on that data, too. We’ve found that data input using the new feature is 85% more accurate than the current process, leading to less manual data entry and less customization. Not only is the experience consistent and organized from a farmer’s perspective, but removing that manual data aspect leads to higher data quality for our agronomic modeling efforts.
There’s so much that goes into even small tweaks (from a farmer’s perspective) to the way they use FieldView; by necessity, releases and feature improvements are intricately coordinated operations. Over the course of the summer, I’ve gone from being a junior undergrad Computer Science major to quickly learning and utilizing complex iOS skills in an agile work environment.
The practical experience I’ve gained has been immense, flexing critical skills in navigating larger-scale projects in a test-driven development environment, strengthening my source control abilities, and having been exposed to really complex iOS skills like implementing Apple Vision, Decorator pattern, and multithreading, to name a few.
Who knew that enabling farmers to scan a barcode with a picture could do so much?