Microsoft - Farmbeats
Creating a system that enables farmers to monitor and analyze crop growth in real-time, ensuring optimal crop health and crop management.
Duration
3 months
Project Type
Sponsored Project
Mobile Design
Role
UX Designer
Researcher
Team
Grace Rao
Xinran Cheng
Scope
Personas, User Flow, Info. Architecture, Wireframe,
Design System, Hi-fi Prototype, Usability Testing.
OVERVIEW
About Farmbeats
Microsoft FarmBeats is a platform that uses data and AI to enhance agricultural productivity. It collects real-time data from IoT sensors, drones, and satellites, helping farmers make informed decisions, optimize practices, and improve crop yields.
The Problem
1. Farmers and agronomists face significant challenges in efficiently managing crop health and productivity due to a lack of real-time data and automated tools.
2. A unified system for efficiently collecting, analyzing crop data, and managing farm tasks is currently missing.
The Problem
1. Farmers and agronomists face significant challenges in efficiently managing crop health and productivity due to a lack of real-time data and automated tools.
2. A unified system for efficiently collecting, analyzing crop data, and managing farm tasks is currently missing.
The Solution
In 10 weeks, we partnered with Microsoft FarmBeats to develop a platform that automates crop recognition, health monitoring, and task management, providing real-time data through a mobile app. The system is designed to help farmers monitor crops in real-time, enhancing decision-making and boosting productivity.
UNDERSTAND THE PROBLEM
User Research
To understand farmers' workflows and identify essential app features, we employed three user research methods to uncover their challenges, pain points, and goals.
Research Methods:
Secondary Research
Reviewed over 20 articles to analyze existing challenges and technological advancements in agriculture.
4 Qualitative Research
Conducted four 30-minute semi-structured interviews to identify constraints in users’ current user experience.
20 Quantitative Research
Administered surveys to farmers to uncover users’ pain points and validate insights derived from prior research.
General Insights
Users struggle with timing agricultural operations like irrigation and fertilization, leading to yield reductions of up to 50% if mistimed.
Users respond that disease and pests are responsible for destroying up to 40% of crop production each year and causing economic losses.
Users find that identifying the precise growth stage of their crops is challenging, which can significantly influence yield.
Users frequently encounter significant delays in detecting changes in crop health.
Users report significant concerns about the impact of diseases and pests on their crops.
Users said that real-time nutrient monitoring can lead to a 15% increase in crop yield.
Pain Points
Based on our analysis of user research data, we have identified three major pain points in the current agricultural sector:
PAIN POINT 1:
Insufficient Monitoring of Growth Rates:
Farmers often struggle to accurately assess the growth speed and stages of crops, which is crucial for determining optimal times for fertilization and irrigation. Lack of real-time and precise growth data can lead to resource wastage and suboptimal yields.
PAIN POINT 2:
Difficulty in Early Detection of Diseases and Pests:
Farmers typically fail to detect early signs of pest infestations and diseases until significant damage is apparent. This delay in detection makes it difficult to apply control measures in a timely manner, potentially leading to severe crop losses.
PAIN POINT 3:
Inefficient Task Management:
Farmers often struggle with managing and prioritizing the numerous tasks required to maintain crop health and productivity. The lack of an integrated system to track, schedule, and monitor tasks leads to inefficiencies and missed opportunities, ultimately impacting overall farm productivity.
KNOW USER
Personas
From our user research, we identified three key user groups: small-scale farmers needing real-time data for efficient crop management, agronomists requiring precise tools for expert analysis, and product managers focused on developing user-centered agricultural solutions. These personas guided the design to meet the specific needs and challenges of each group.
Competitive Analysis
To better understand the product landscape and identify market opportunities, we conducted an analysis of 5 competing products. We assessed key features, including those we plan to implement, against common industry standards.
Our analysis revealed gaps in the market, specifically the absence of features like crop growth rate tracking, task management, and AI assistance, which we aim to emphasize in our product.
Design Goals
Based on user research insights, personas, and competitive analysis, we identified key features required by our target users and uncovered market opportunities, leading to the establishment of 4 strategic design goals to effectively meet user needs.
Proactive Monitoring and Alert
Develop a mobile app with AI tools to detect early signs of diseases and pests, providing timely alerts and recommendations.
Integrated Real-Time Data Platform
Combine IoT sensors, satellite imagery, soil sensors, weather stations, and plant health monitors into a single platform for real-time crop growth and health data.
Comprehensive Decision Support System
Designed an intuitive crop management dashboard, integrating data analytics and historical tracking to enhance decision-making.
Automated Task Management
Implement an IoT-based system to automatically record agricultural operations, track activities, and manage tasks efficiently.
THE FRAMEWORK
Information Architecture
To ensure a seamless user experience and clear navigation, we developed a comprehensive information architecture that organizes key features such as onboarding, AI assistant, dashboard, task management, and sensor integration. This structure helps guide users through the application, ensuring that all functionalities are easily accessible and logically connected.
User Flow
To better understand how users interact with the product, I broke down the user flow by individual features instead of mapping the entire app at once. This approach helped clarify the logic behind user actions and how each page interacts within specific features. By creating these detailed user flows, I also identified and corrected design flaws in the information architecture.
START DESIGN
Lo-fi Wireframe
Building on the information architecture and user flow, we created a lo-fi wireframe to outline the basic design layout and structure of the interface.
Hi-fi Prototype
After ensuring that all user needs and key features were addressed in our design, we refined the hi-fi prototype, focusing on the design details and interactions between pages. This preparation was essential for the upcoming usability testing.
THE REFINEMENT
Usability Testing
Conducted 6 remote usability tests with small-scale farmers, agronomy students, and farm-related product managers to gather feedback and refine the design.
Iteration 1: Redesigned crop cards to display more information at a glance, reducing interaction costs.
4/6 users wanted dashboard cards to show more crop status, reducing the need to click into detail pages.
Iteration 2: Redesigned crop detail page
5/6 users felt that the crop detail information was cluttered, presenting a lot of data that required careful scrutiny to understand.
Iteration 3: Redesigned the map view page
All users mentioned that the map view interaction felt awkward, and the crop information was not clearly presented.
Iteration 4: Redesigned the interaction for viewing field crops
Design System
Before finalizing the design, I established basic design tokens, such as colors, typography, and grid, based on the hi-fi prototype. As I iterated on the final design, I created components and design guidelines to ensure consistency and enhance user experience, making future iterations more efficient.
Final Design - Microsoft Farmbeats
FEATURES
Monitor Crop Growth
The homepage crop card now displays the crop growth rate directly.
On the crop detail page, additional growth-related information is provided, along with a linear growth chart to help users better monitor plant development.
Pain-point 1 Addressed: Efficient monitoring growth rate
Detect Pests
Implemented pest detection notifications to alert users immediately. Enhanced the map view to clearly display the location of detected pests, accompanied by AI-driven pest control and prevention suggestions to help users address the issue efficiently.
Pain-point 2 Addressed: Early detection of pest
Task Management
the task management feature helps users make better decisions and improve crop productivity. Additionally, the AI assistant provides plant-specific suggestions that can be directly added to tasks.
Pain-point 3 Addressed: Efficient task management
AI Assistant
The AI assistant is seamlessly embedded throughout the app, providing targeted suggestions for crops, sensors, and tasks, enhancing the overall user experience.
Also, a floating button allows users to interact with the AI assistant from any page.
Map View
Designed dedicated map views for both crops and sensors, allowing users to easily visualize their locations within the fields.
REFLECTION
Takeaways
Deep Understanding of User Needs: Conducted thorough user research to identify key pain points, resulting in a design that directly addresses the real needs of farmers and agronomists.
Validation Through Testing: Used usability testing to validate design decisions, leading to a more intuitive and effective user experience.
Empathy in Research: Gained valuable insights by engaging directly with end-users, allowing for a design that truly resonates with their daily workflows.