Creating farmer-friendly software for Precision Agriculture using Variable Rate Application (VRA) to boost yields, cut chemical usage, and safeguard the environment.
In the realm of agriculture, Precision Agriculture and Variable Rate Application (VRA) technologies, mainly adopted by large farms, are on the brink of transformation. This case study explores the UI/UX design journey aiming to make these advanced tools more accessible, simpler, and user-friendly, bridging the gap between cutting-edge technology and the traditions of farming practices for a wider audience.
Photo by no one cares on Unsplash.
Precision Agriculture, a revolutionary approach, leverages technology to optimize agricultural practices. By performing precise interventions at the right time and place, this method aims to elevate yields while minimizing inputs. The process involves real-time monitoring for instant data collection, intelligent data analysis that suggests strategic actions, and Variable Rate Application (VRA) for the exact application of inputs where needed on the fields.
Diagram that I created using isometric Illustrations by macrovector on Freepik.
My UI/UX contributions were centered on immersing myself in the future of agriculture, exploring the intricacies of sophisticated software designed to facilitate the adoption of Precision Agriculture. With a focus on increasing agricultural yield and promoting eco-friendly practices by optimizing resource use, my goal was to streamline the UI for seamless data-driven decision-making.
Exploring precision agriculture software offerings revealed a varied landscape, with diverse solutions targeting different farm sizes. Despite a robust comparative matrix, no significant innovation gaps were apparent. However, a few crucial insights emerged: collaboration is often overlooked, many platforms lack proactive action suggestions, and a substantial portion lacks efficient before/after comparison modes to measure the impact of Precision Agriculture interventions.
The desk research I conducted revealed that Affordability is the primary obstacle to Precision Agriculture adoption, with high costs and risk challenges for small plots. Larger farms benefit from economies of scale, driving higher adoption rates. Additional barriers include a lack of awareness, reluctance to change customary practices, limited digital infrastructures in remote areas, and the complexity associated with tech adoption.
Data from the USDA (United States Department of Agriculture) – Report “Farm Computer Usage and Ownership” August 2021.
Blasch, Julia, Francesco Vuolo, Laura Essl, and Bianca van der Kroon. 2021. "Drivers and Barriers Influencing the Willingness to Adopt Technologies for Variable Rate Application of Fertiliser in Lower Austria" Agronomy 11, no. 10: 1965.
In conversations with South African farmers (not using precision agriculture software), I uncovered their reliance on gut feelings, experience, and direct field observation for decision-making. This highlights the need for technology that aligns with more traditional farming approaches and diverse experiences.
Interviews revealed that direct observation (crop scouting) remains a cornerstone of crop farming, and is perceived as essential by farmers. While precision agriculture automates scouting, it poses challenges for traditional small farmers who value hands-on observation. This method excels in assessing crop health and interventions but faces limitations in scalability and resource constraints, especially for large farms. Then, striking a balance between tradition and technology appear to be crucial to increase the adoption of new Precision Agriculture technologies by farmers.
Scouts employ X, W, or V patterns for accurate field health assessment, occasionally walking along edges and outside rows for pest inspection. Patterns vary between trips and sections. Scouts choose three to five sample points, inspecting 10–20 plants or approximately 10 m2 at each location.
Photo by Erik 🖐 on Unsplash
Two key challenges surfaced during research, pivotal for driving precision agriculture technology adoption and refining software UX:
Photos by Scott Goodwill & Tim Mossholder on Unsplash.
The final solution I designed seamlessly integrates human intuition and direct observation with cutting-edge monitoring technologies and analytics, ensuring optimal data-driven efficiency.
In the solution I crafted, farmers effortlessly record field observations using the mobile version of the precision agriculture software. Geolocalized insights, enriched with images and descriptions, are intelligently grouped for a comprehensive view of farmers' observations in the fields. This approach harnesses farmers' wisdom, extracting valuable insights from their experience and intuition.
Mobile content from this fieldwise project & integrated into the photo by jcomp on Freepik.
Scouting reports are rapidly shared within the team, promoting collaborative decision-making. The interface encourages team engagement through effortless commenting and task assignment, fostering seamless teamwork for efficient and informed crop management.
The solution guarantees continuous monitoring with smart sensors and satellite analysis, offering automated early issue detection. Insights are categorized and delivered via dedicated map explorer tabs for each field and sensor, providing a real-time view of crucial parameters like crop growth, water stress, nutrients, weather conditions, and pest presence.
I designed the platform architecture with a focus on map layer categorization, providing farmers with easy access to main insight types: crop growth, water stress, nutrients, weather, and pest presence.
Empowering farmers to track field changes and make informed decisions for improved yields, I designed a Map Explorer with user-friendly comparison modes like browser tabs, multi-window maps, multi-layer maps, and a handy comparison slider.
Leveraging collected data, the system suggests Prescription Maps, facilitating Variable Rate Application (VRA) for targeted agricultural interventions. Users can also seamlessly generate custom maps, including specific care areas, ensuring precision in their farming practices.
Transitioning from Prescription Maps to precision actions, each VRA application automatically generates a report for post-application impact measurement. Users are provided with tools to track and evaluate the efficiency of interventions, enabling a comprehensive assessment of decisions' impact on crop yields and resource utilization.
The platform offers tailored reports and analytics for a detailed analysis of farm productivity, allowing farmers to estimate costs, assess ROI, and gain insights into field potential, crop performance, and soil quality.
Fieldwise embodies “smart” decision-making in crop farming, reflected in its name and logo. I designed the logo by combining the shape of a plant with the letter W, representing wisdom. The color palette, dominated by green and grey tones, naturally associates the platform with agriculture while maintaining a subtle touch of technology through cool green hues.
The UI of the Fieldwise platform is structured using a design system derived from IBM's free and open-source "Carbon Design." I customized and extended this existing system to align with the unique requirements of this precision agriculture project, ensuring a cohesive and user-friendly interface.
Fieldwise caters to user preferences and varied contexts by offering both light and dark themes. The dark theme is particularly suited for screens emphasizing map visualizations, ensuring that controls seamlessly blend with data visualizations and displayed information.
A notable feature of the UI design in this project is the incorporation of various data visualizations. From overlaid heatmaps on maps to interactive charts, I specifically crafted these visual elements to enhance the understanding of complex agricultural data, providing users with valuable insights at a glance.
Through this project, I explored agriculture's future and software complexities for expert farmers, highlighting UX's pivotal role in advancing precision agriculture.
