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Agrox

Autonomous & Chemical-Free Pest Management

[ Hero Image / Product Render Placeholder ]
Team
Yuchen Zhang
Yi He
Role
UX/UI Design
Hardware Concept
Timeline
Academic Project
2024
Domain
AgriTech
Robotics
01 — Research

Understanding the
core challenges.

Our goal was to understand the challenges small-scale farmers face during the growing process—and how they currently detect and respond to these problems in their day-to-day farming practices.

4
Farms at Forsyth Park
Farmers Market
1
Farm in
South Carolina
02 — The Problem

The burden of
organic pest control.

Organic farms face persistent pest threats, but manual monitoring and traditional control methods are time-consuming and inefficient, leading to crop losses and higher costs.

There is an urgent need for an automated, eco-friendly, and easy-to-deploy pest management solution that enables accurate detection, control, and data tracking.

Interview Insights

  • Lack of Systematic ID: Farmers lack systematic pest identification and record-keeping.
  • High Pressure Failure: Organic pest control methods present challenges in high pest pressure situations.
  • Software Complexity: The complexity of farm management software can hinder adoption.
03 — Target User

Designing for the
everyday farmer.

"I want something that just works. I don't have time to learn another complicated app."

How Might We

How might we help organic farmers monitor and control pests with minimal effort, while keeping the process eco-friendly and data-informed?

Core Needs

  • A simple visual system to monitor outbreaks without walking every field.
  • A non-chemical control method aligning with organic certification.
  • An affordable, zero-training solution.
  • A way to track effectiveness of pest control over time.

Frustrations

  • Current solutions are too expensive or too complicated.
  • Manual scouting is exhausting and unreliable, especially during rainy days.
  • Lack of data to understand where pests are spreading or recurring.
04 — Technical Direction

From field research to a
chemical-free solution.

To meet the needs of organic farmers, we researched technologies that could replace chemical pesticides while automating the labor-intensive scouting process.

A.I. Visual Recognition

Deep learning models continuously monitor and classify pests, making detection faster and less dependent on human experience.

Bug Vacuuming

An immediate, physical method to extract surface-level pests without compromising organic certification.

Steam Sterilization

High-temperature steam effectively targets pest eggs and soil-borne pathogens, breaking the reproductive cycle.

Robot+A.I.+IoT
Connected via IoT robotics, these technologies form an autonomous loop: identify the threat, remove the visible, and sterilize the invisible.
05 — The Product

Hardware & Interface.

Translating the technical requirements into a robust physical robot and an intuitive digital dashboard for the farmers.

A.I. Visual Pest Recognition

The robot's onboard cameras scan crops in real-time. The AI model identifies pest types and severity, logging the data to the farmer's dashboard without requiring manual field walks.

[ Image: AI Visual Recognition UI/Render ]

Autonomous Pest Management

Once deployed, the robot navigates the farm autonomously. It uses a combination of bug vacuuming for adult insects and steam sterilization for soil-level eggs, ensuring a 100% chemical-free process.

[ Image: Robot Hardware Render / Steam Vacuum ]

Pest Heatmap Dashboard

Data collected by the robot is visualized on a simple mobile and web app. Farmers can instantly see which areas of the farm have high pest pressure and track the effectiveness of the robot's interventions over time.

[ Image: Mobile App / Heatmap UI ]
06 — Design Process

From sketch to reality.

[ Image: Sketch ]

01. Sketch

[ Image: Hifi Model ]

02. Hifi

[ Image: Physical Model ]

03. Model