During this last semester in graduate school as I was *only* taking one self-paced data science course while working full-time, I came across an innovation challenge by Feed the Future. I was almost finished with the course and thought this competition sounded interesting. Added to the curiosity was my tendency to passionately pursue solving problems related to ending hunger in my lifetime. In October 2017, I focused on the coffee supply chain by looking at what disease affected the crop in the ‘Morning Joe Project’. I wrestled with whether this armyworm problem was a data science question and whether I should devote my limited free time to participating.
According to the tech challenge organizers, ‘Fall armyworm (FAW) poses a serious threat to food security in sub-Saharan Africa. Originally from the Americas, FAW outbreaks first occurred in West Africa in early 2016 and are now on the precipice of devastating food supplies across the continent, exacerbating global poverty and hunger. FAW attacks more than 80 different plant species and agriculture experts estimate the pest may cause over $13 billion in losses for crops like maize, sorghum, rice, and sugarcane. It can also fly up to 1,600 kilometers (nearly 1,000 miles) in 30 hours meaning it can easily migrate to surrounding farms and countries.’ Hmm..less than a month to come up with a feasible idea that can be prototyped by the end of June about what seems to be more of a data collection, reporting and analysis question where I have no expertise — why of course, sign me up!
I then did what anyone with no expertise does when faced with such a large task. I combed the internet doing many hours of research on existing technologies and solutions that were digital and non-digital that were being used in Africa and other places where this nasty pest lives. Apparently, the worm is difficult to control since it moves pretty quickly. I got out what I call my ‘black notebook of creativity’ and started brainstorming. I also enlisted the help of my husband who has engineering and product development experience. Over the next few weeks, we learned about the lifecycle of the fall armyworm and identified gaps in information and how to address those gaps. We tried to come up with a solution that would improve upon existing research and think of the problem from an engineering systems perspective.
Our proposed solution is proactive and uses non-digital and digital tools to help identify and alert subscribing farmers to the possibility of fall armyworms on their land before they occur. Our solution addresses the traditional information collection and distribution channels typically held by men by automating data collection and reporting. Our system is solar-powered and provides context-appropriate and timely pest forecasting information so farmers can take action to protect their crops. The system is adaptable to all types of crops and other types of pests.
Since our team has two passionate but inexperienced individuals, the likelihood of winning a prize is pretty small. However, as the old saying goes – nothing ventured nothing gained. Working on this challenge has been a tremendous learning and personal growth activity and it’s been pretty cool to see the potential artificial intelligence has for this agricultural use case. I’ll let you know if our concept is successful.