[MISSION LOG]

CASE STUDIES

Real missions. Real data. Real results. Each project below represents a complete engagement — from research question through deployment and published findings.

[AGR-001] AGRICULTURAL RESEARCH

Multispectral Crop Analysis

Client: University agricultural research department

10×Faster data collection
<1cmGround resolution
$40KSaved vs. manual methods
3hrsPer full survey cycle

▸ THE CHALLENGE

The research team was conducting manual field surveys across 2,000+ acres — a process that consumed 3-4 weeks per survey cycle with limited spatial resolution. Graduate students spent more time walking rows than analyzing data, and coverage gaps meant unreliable datasets for their USDA-funded nitrogen uptake study.

▸ OUR SOLUTION

We deployed a DJI Matrice 300 RTK equipped with a MicaSense RedEdge-P multispectral sensor, flying automated grid patterns at 120m AGL. Custom flight plans ensured 80% overlap for photogrammetric accuracy. A Python-based data pipeline handled orthomosaic stitching, NDVI/NDRE calculation, and integration with the lab's existing GIS workflow — all automated from SD card to publication-ready maps.

▸ TECH STACK

DJI Matrice 300 RTKMicaSense RedEdge-PCustom Python PipelineNDVI / NDRE AnalysisAutomated Flight PlanningGIS Integration

“The drone survey data gave us spatial resolution we never thought possible at this scale. It fundamentally changed our experimental design.”

— Principal Investigator, Plant Science Dept.

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[INF-002] INFRASTRUCTURE INSPECTION

Bridge Structural Health Monitoring

Client: Civil engineering department

90%Cost reduction vs. scaffolding
0.2mmCrack detection threshold
12Spans inspected in 2 days
3DPoint cloud structural model

▸ THE CHALLENGE

Traditional scaffolding-based bridge inspections cost $150K+ per structure, required lane closures for weeks, and still left blind spots in hard-to-reach areas. The engineering team needed sub-millimeter crack detection across 12 aging concrete spans — safely and repeatedly.

▸ OUR SOLUTION

We built a dual-sensor inspection platform combining a high-resolution RGB camera with a radiometric thermal sensor, mounted on a custom airframe with FPGA-accelerated onboard image processing. LiDAR scans generated 3D point cloud models, while our AI crack detection pipeline (trained on 50K+ labeled bridge defect images) flagged anomalies in real-time. Photogrammetric models enabled precise change detection between quarterly inspections.

▸ TECH STACK

Custom FPGA Image ProcessingLiDAR Point CloudThermal + RGB FusionAI Crack DetectionPhotogrammetryChange Detection Pipeline

“We went from a $150K scaffolding quote to a complete digital twin of the bridge in 48 hours. The thermal data alone justified the entire project.”

— Dept. Chair, Civil Engineering

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[ENV-003] ENVIRONMENTAL MONITORING

Coastal Erosion Tracking

Client: Environmental science lab

WeeklyMonitoring capability
0.5cmVertical accuracy
NaturePublished in Nature journal
4kmCoastline coverage per flight

▸ THE CHALLENGE

Quarterly manual GPS surveys of a 4km coastline were too infrequent to capture rapid erosion events driven by storm surges. By the time the team had survey data, the coastline had already shifted. They needed high-frequency, high-accuracy monitoring without the budget for permanent ground stations.

▸ OUR SOLUTION

We established monthly automated drone flights using RTK-GPS positioning for centimeter-level accuracy. A custom Python change detection pipeline compared successive orthomosaics, automatically calculating volumetric erosion rates and generating differential elevation models. The workflow was designed for graduate students to execute independently after initial training.

▸ TECH STACK

RTK-GPS PositioningPhotogrammetric DEMsPython Change DetectionVolumetric AnalysisAutomated Flight ProfilesStudent Training Program

“The weekly resolution transformed our understanding of erosion dynamics. We captured events we would have completely missed with quarterly surveys.”

— Lead Researcher, Environmental Science

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