UAT 467 · 3(1-4-4) · Year/term 4/1

UAS for Inspection

ระบบอากาศยานไร้คนขับเพื่อการตรวจสอบ

Progress

Notional hours: 135 h (online/self-study 60 · in class/lab 75)

Course description

planning and execution of inspection missions for industrial assets and processes, sensor selection, visual and positional data acquisition, anomaly detection, severity classification, temporal comparison of data, and inspection reporting

Thai description

หลักการวางแผนและปฏิบัติภารกิจตรวจสอบทรัพย์สินและกระบวนการอุตสาหกรรม การเลือกเซนเซอร์ การเก็บข้อมูลเชิงภาพและเชิงตำแหน่ง การตรวจหาความผิดปกติ การจัดระดับความรุนแรง การเปรียบเทียบข้อมูลตามช่วงเวลา และการจัดทำรายงานการตรวจสอบ

Description source: Curriculum draft (revised 28 Sep 2026)Previous site code: DRT 462

Course learning outcomes (CLO)

CLO	Outcome	PLO
CLO1	Select drone inspection methods for industrial work	PLO5
CLO2	Collect traceable, quality inspection data	PLO2PLO5
CLO3	Analyse and communicate inspection results	PLO4PLO6

Learning modules

1Industrial inspection
Weeks 1–3 · 27 h1 KU

Online (before class) · 12 h

Study the assigned knowledge units in advance, review media and take the module quiz

Structural inspection methods with dronesIn development

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

2Payloads and settings
Weeks 4–6 · 27 h2 KU

Online (before class) · 12 h

Study the assigned knowledge units in advance, review media and take the module quiz

Payloads and survey data qualityTH
EO/IR cameras and gimbalsIn development

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

3Records and evidence
Weeks 7–9 · 27 h3 KU

Online (before class) · 12 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

4Image analysis
Weeks 10–12 · 27 h2 KU

Online (before class) · 12 h

Study the assigned knowledge units in advance, review media and take the module quiz

Intelligent video analyticsIn development
Checking image quality and reading AI metricsTH

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

5Reports and limitations
Weeks 13–15 · 27 h3 KU

Online (before class) · 12 h

Study the assigned knowledge units in advance, review media and take the module quiz

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

Assessment (draft)

Labs and worksheets	35%
Module quizzes	10%
Midterm examination	20%
Mini-project or practical exam	35%

Knowledge domain

D04 Sensors and embedded systems D09 Law, safety and risk D11 Artificial intelligence and computer vision D13 Surveying, mapping and geoinformatics D14 Inspection, industry and surveillance D16 Public safety and disasters D18 Management, innovation and professional practice

Key references

Barnhart, R. K., Marshall, D. M., & Shappee, E. (Eds.). (2021). Introduction to unmanned aircraft systems (3rd ed.). CRC Press. link
Wolf, P. R., DeWitt, B. A., & Wilkinson, B. E. (2014). Elements of photogrammetry with applications in GIS (4th ed.). McGraw-Hill Education. link