Smart Agriculture Platform
AI-Powered Computer Vision Platform for Smart Agriculture Pest Monitoring
ROLE
UX Designer
EXPERTISE
UX/UI Design
YEAR
2024
An AI-powered computer vision platform for SGCAN to enhance pest monitoring across Bolivia, Colombia, Ecuador, and Peru, processing satellite, drone, and mobile imagery for early detection.
Researchers
Monitor pest activity, analyze AI predictions, and validate detection results.
Field Officers
Record field observations, review affected locations, and plan intervention activities.
Shared Goal
Detect pest outbreaks early, improve response time, and support data-driven agricultural decisions.
This category details the step-by-step approach taken during the project, including research, planning, design, development, testing, and optimization phases.
Research & Planning
Conducted market research to identify existing scheduling challenges and user preferences. Defined target audience segments and outlined key features based on user needs and market trends.
Design & Prototyping
Collaborated with designers to create intuitive user interfaces and interactive prototypes. Iteratively refined designs based on user feedback to enhance usability and visual appeal.
Implementation
Leveraged agile development methodologies to build the scheduling app from the ground up. Prioritized feature development based on user feedback and technical feasibility. Implemented AI algorithms to analyze user behavior and optimize scheduling recommendations.
Testing & Optimization
Conducted rigorous testing across various devices and platforms to ensure compatibility and performance. Gathered user feedback through beta testing and iteratively optimized the app based on usability metrics and user satisfaction.
Interactive Monitoring Dashboard
Designed a centralized dashboard displaying pest alerts, crop statistics, affected regions, and AI detection summaries in one place.
AI-Powered Map Visualization
Integrated interactive maps with satellite imagery, drone data, and AI-generated detection points, allowing users to monitor pest activity geographically.
Field Data Management
Created workflows for viewing inspection reports, updating observations, and tracking intervention progress directly from the platform.
Actionable Reports
Designed comprehensive reporting features with downloadable summaries, trend analysis, and historical comparisons to support decision-making.
Highlighting how the platform improved Agriculture experience
Faster Pest Detection
The redesigned workflow enables users to identify affected regions more efficiently through AI-assisted visualization.
Improved Decision Making
Clear dashboards and map-based insights reduce the effort required to interpret agricultural data.
Better Workflow Efficiency
Simplified navigation and organized information reduce the number of steps needed to complete common monitoring tasks.
