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UAV Control System

Agricultural UAV Interface Design
Tablet AppAgtechB2B
Team (4)
Product Designer, Technician Interface (me), Product Designers
Timeline Aug 2025|Dec 2025
Tool
FigmaFigma
    UAV Control System main hero image
    Overview

    AgriDrone is a modular farm UAV: one aircraft swaps payloads for mapping, spraying, and crop monitoring instead of buying three separate drones. I designed the Technician tablet UI for payload control and field diagnostics.

    01 · Context & Problem

    Technician UI for a multi-payload farm drone

    Teammates owned Pilot and Specialist screens; this case study focuses on the Technician role—payload operations, diagnostics, and repairs in the field.

    466 acres

    Average U.S. farm: manual monitoring doesn't scale.

    $15k+

    Typical single-task drone: three systems is unrealistic.

    • One platform Mapping, spray, and thermal in one system
    • 12-hour shifts UI must stay clear under long field load
    • Zero overload Payloads, diagnostics, repairs, all without friction
    AgriDrone Showreel: multi-role agricultural workstation UAV system in action. (This video is provided by Prof. Cameron Rennacker and Shoaib Ahmad.)
    02 · Project Goals

    Three goals for the Technician tablet

    Role-specific UI

    A focused workspace for payload ops: cameras, spray, cargo, and repairs.

    Lower cognitive load

    Fast health reads, clear alerts, and troubleshooting without split attention.

    Ecosystem fit

    Technician UI aligned with Pilot and Specialist screens from the team.

    03 · Key Solutions / Final Design

    A clear tablet workspace in the field

    Health cards, actionable alerts, and maintenance logs: everything a technician needs on one digestible screen.

    Health monitoring

    Status cards for fluid, pressure, and temperature at a glance.

    Actionable alerts

    Pop-ups show the issue and recommended next steps.

    Maintenance logs

    Automated history so technicians don't rely on memory alone.

    04 · Design Process

    Research through AI-assisted troubleshooting

    Phase 01 · Research

    Concept Development

    One tablet for every payload.

    Sprayers, seeders, radar: one screen, no app switching.

    UAV technician interface concept mockup
    Concept mockup: interchangeable payloads on one technician screen.

    Diagnostic time: identify a payload issue

    Estimated minutes for a technician to pinpoint a payload fault using current workflows vs. the unified tablet UI goal.

    Multi-app
    18m
    Paper checklist
    12m
    Unified UI goal
    5m
    4 Payload types
    12h Typical shift length
    3 Dashboard views
    Phase 02 · Information Architecture

    Wireframing

    Three dashboards: overview, mission, statistics.

    Overview for health, mission for active tasks, statistics for logs, so each view shows only what the technician needs.

    Technician Overview Dashboard with at-a-glance UAV and attachment health monitoring
    Overview Dashboard: at-a-glance UAV and attachment health.
    Technician Mission Dashboard tracking active spraying zones and usage trends
    Mission Dashboard: active task zones and usage trends.
    Technician Statistics Dashboard with post-flight data and maintenance logs
    Statistics Dashboard: post-flight data and maintenance logs.
    Phase 03 · Human Factors

    Iteration

    Proximity, mental models, and salience tame dense data.

    Grouped module cards, a 3D UAV diagram, and green/yellow/red alerts cut scan time and tie digital warnings to physical parts.

    Contextual alert workflow pop-up with blocked nozzle alert and recommended next steps
    Contextual Alert Workflow: salience and proximity applied to critical nozzle alerts.
    Phase 04 · AI Integration

    Troubleshooting

    AI chatbot: step-by-step fixes or specialist handoff.

    When a module fails, an in-app chatbot walks through fixes or escalates to a specialist, with no deep software expertise required.

    AI Troubleshooting Chatbot integrated into the Technician interface
    AI Chatbot Integration: predictive aiding and specialist escalation via a centralized messaging hub.
    05 · Visual Demonstration

    Technician interface in context

    AgriDrone ecosystem context mockup showing multi-role agricultural workstation UAV system
    AgriDrone Ecosystem Context: multi-role agricultural workstation UAV system.
    06 · Reflection & Impact

    Fix problems, not just read errors

    Field stress proved human factors and predictive aiding matter: the outcome is a readable workspace that ships with Pilot and Specialist UIs.

    Problems solved

    Complex multi-tool diagnostics became a readable tablet workspace for technicians.

    Goals achieved

    Full Technician UI/UX delivered in sync with Pilot and Specialist roles.

    Vision

    Less fatigue and faster maintenance keep AgriDrone flying, and farmers saving time.

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