The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from improving economic sustainability for farmers and autonomously identifying business cases for collaborative farming through sourced-out jobs that can be more effectively done by other farmers for a number of reasons such as proximity to job sites and availability of resources. The market currently focuses on the efficiency of equipment and inputs utilization for precision farming to improve profits. The proposed project will boost profits further by optimizing end-to-end farm processes that implicitly drive the efficient usage of equipment, labor, and fuel. The proposed project can potentially save 213 million gallons of fuel burn per year across the US (covering 253 million acres), which in turn will reduce emissions and improve air quality. The fuel savings will result from optimizing the idle, load, unload and drive times of the equipment. Broadly, farmers today consider process variability of farming as part of the business due to a lack of process and financial impact measurement systems, which results in failing to capture unrealized profits of $100K-$300K on a typical 10,000 acre farm lot. Healthcare and manufacturing are example industries that have controlled process variability by using process and performance measurement systems. The proposed innovation will enhance scientific and technological understanding of controlling process variability in agriculture by autonomously measuring the time and cost of end-to-end farm processes and identifying common root causes and cost drivers. The innovation will provide win-win economic sustainability for both small and large farmers. This Small Business Innovation Research (SBIR) Phase I project identifies hard to track operating inefficiencies, with a financial impact that results in capturing unrealized profits for farmers. Today, farmers use averages to track operating spend and are not able to track the actual spend allocation to services and activities by field and per acre. Farmers today do not have a full view of actual operating performance across the on-farm supply chain, which in turn prevents them from analyzing the financial impact of how they work. Due to process variability, farmers often ignore operating inefficiency instead of measuring and analyzing the financial impact of such operating inefficiency and putting in place contingency plans and operating controls to mitigate operating losses. The research objective of Phase I is to show farm managers their unrealized profits due to operating inefficiency, and automatically identify root causes for farmers to manage cost drivers through better planning and controls to capture unrealized profits of $100K-$300K for every 10,000 acres. The proposed research will quantify the benefits of process measurement, provide live tracking of equipment of any make, model, and age in a single view, provide live visibility of actual operating spend by activities and services by field and per acre, and reconcile actuals against target performance metrics. It will also identify root causes and cost drivers that, when controlled, can boost profits. The anticipated results will typically improve profits for farmers by 2-5% and create economic opportunities for small farmers through collaborative farming. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
