DRT 476 · 3(2-3-5) · Year/term 4/2

IoT and Smart Warehouse Systems

IoT และระบบคลังสินค้าอัจฉริยะ

Progress

Notional hours: 150 h (online/self-study 75 · in class/lab 75)

Course description

Internet of Things architecture in smart warehouses; sensors and wireless networks; MQTT and low-power networks; cloud data storage and dashboards; integrating UAS data with warehouse management systems; data security.

Thai description

สถาปัตยกรรมอินเทอร์เน็ตของสรรพสิ่งในคลังสินค้าอัจฉริยะ เซนเซอร์และเครือข่ายไร้สาย โปรโตคอล MQTT และเครือข่ายพลังงานต่ำ การจัดเก็บและแสดงผลข้อมูลบนคลาวด์ การบูรณาการข้อมูลจากอากาศยานไร้คนขับกับระบบบริหารคลังสินค้า และความมั่นคงปลอดภัยของข้อมูล

Description source: New draft for the curriculum committee

Course learning outcomes (CLO)

CLO	Outcome	PLO
CLO1	Explain IoT architecture in smart warehouses	PLO4
CLO2	Develop sensor messaging over MQTT	PLO4
CLO3	Integrate drone data with WMS and dashboards	PLO5

Learning modules

1IoT in warehouses
Weeks 1–3 · 30 h1 KU

Online (before class) · 15 h

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

IoT and smart warehouse systemsIn 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

2MQTT and brokers
Weeks 4–6 · 30 h1 KU

Online (before class) · 15 h

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

Deep dive: MQTT and Eclipse Mosquitto for drone and IoT systemsTH

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

3LoRa and sensor networks
Weeks 7–9 · 30 h1 KU

Online (before class) · 15 h

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

Deep dive: Internet of Military Things, LoRa/mesh networks and field applicationsTH

In class / field · 15 h

Lab or field practice from worksheets with a safety checklist

Learning evidence: Checked worksheets and quiz results

Open module

4Cloud and dashboards
Weeks 10–12 · 30 h2 KU

Online (before class) · 15 h

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

Cloud and IoT data servicesIn development
Data handling and visualisation with PythonIn 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

5Drone integration
Weeks 13–15 · 30 h1 KU

Online (before class) · 15 h

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

Drones for warehousesIn 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

Assessment (draft)

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

Knowledge domain

D01 Mathematics, physics and statistics D02 Programming and digital technology D07 Communications, networks and IoT D15 Delivery, indoor operations and warehousing D16 Public safety and disasters

Key references

Kurose, J. F., & Ross, K. W. (2021). Computer networking: A top-down approach (8th ed.). Pearson.
Wawrla, L., Maghazei, O., & Netland, T. (2019). Applications of drones in warehouse operations (White paper). ETH Zurich.