A livestock management tool might seem like an odd choice for a Baltimore Hackathon project. Other than the occasional escape, cattle aren't frequently seen in the area. However, cattle and beef production has a significant impact on the US economy. According to the Cattlemen’s Beef Board and National Cattlemen’s Beef Association, there are more than 1 million beef producers in the United States who added more than $66 billion to the US economy in 2008.

Garrett Bladow, who lives in Federal Hill, is one of those beef producers. He is a co-owner of L7 Ranch, which has over 1,500 head of cattle, and is responsible for the ranch's genetic breeding program and land sequestration efforts. The quality of L7 Ranch beef has been widely recognized. The genetic traits have been sought after and recognized by the Yorkshire Agricultural Society and the Professional Bull Riding Association, among others. Additionally, over 60 percent of the Wagyu beef exported from Japan to the United States has been bred using genetic material from the L7 Ranch.

Garrett is frustrated by the current state of livestock management software. Most packages are dated, don't take advantage of newer technologies, don't allow data to be easily imported, exported, or shared, and aren't attuned to the workflow of the farmers. In addition, most don't incorporate tools to help farmers improve their herds, yields, and revenue. This is especially important since most beef producers have small operations with very thin margins and, again according to the Cattlemen’s Beef Board and National Cattlemen’s Beef Association, they have the lowest income of any type of farm (in 2007 an average gross cash income of $63,000). For most farmers beef production is not their primary occupation.

This industry needs a software package that has a modern and easy-to-use interface that accounts for the fact that a lot of data needs to be collected in fast-paced, dangerous environments. It also needs to support the average farmer, who is nearly 60 years old but fairly well educated. (Almost 89 percent are high school graduates and over 20 percent have a college degree.) It also should be integrated with any RFID tracking systems used on farms.

What it does

At the Baltimore Hackathon, a team of developers came together to explore an initial solution for managing livestock and making recommendations to improve yields. The resulting application allows for stockmen

  • to upload data about their herd and add additional data throughout the lifecycle of that herd, including births and vaccinations,
  • to use the inputted data to get recommendations that improve their breeding profiles and cattle production yields,
  • to improve their breeding program through knowledge about birth defects and other progeny risks, and
  • to understand how their herd compares to average breeding profiles.

How we built it is a native React application, so that it can be ported to mobile and web platforms. The data is stored in a Neo4j database. The two are connected via middleware driven by Node.js and Express.js.

All team members contributed to the code, although three focused on constructing and populating the data model, one person wrote the API, and one person developed the user interface.

Challenges we ran into

  • Learning and using new tools and libraries within a limited timeframe.
  • Narrowing the scope of a large project.
  • Having only one subject matter expert and exploring a subject with a lot of nuances.

Accomplishments that we're proud of

  • We learned a lot about the problem space and about the technologies we chose to use. For many of us, this was the first time using Neo4j.
  • We have an initial app.
  • We thought through the user experience & talked about how stockmen will need to use the software in unusual conditions. (For example, limited wifi, cold, dirty, dangerous.)

What we learned

  • This is a big problem with a fair number of permutations.
  • Neo4j is fun.

What's next for mobull

The Baltimore Hackathon project is a part of a larger idea. The overarching idea of is a livestock management system that integrates livestock RFID tracking tags. By combining mobile platforms and synchronized online data services with a portable and cost-effective RFID reader, the system will provide four functional components, aimed at different places in the livestock production chain:

  • managing records (animal characteristics, vaccinations, and so on) for stockmen,
  • maximizing feed potential for stockmen and feed lot operators,
  • processing records for meat packers and inspection agencies (USDA), and
  • tracking "pasture to table" lifecycle for consumers.

To accomplish these goals the system will have to work in several scenarios including

  • livestock chute systems, which a used by stockmen to safely secure animals while they are examined, marked, or given veterinary treatment,
  • transportation systems, where loading and unloading of the livestock needs to be recorded,
  • feed delivery systems, and
  • the fields where operators check stock.
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