ECE 896 (01) - Special Topics in Electrical or Computer Engineering

Spc Top/Syst Design&Data Anlys

Durham   Engineering&Physical Sciences :: Electrical&Comp Engineering
Can be taken by students who are remote.
Credits: 4.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Class Size:   10  
CRN: 11663
New or specialized courses and/or independent study. Some sections may use credit/fail grading.
Section Comments: Full Title: Internet of Smart Things ? System Design and Data Analysis
Equivalent(s): EE 896
Instructors: Diliang Chen

Times & Locations

Start Date End Date Days Time Location
8/30/2021 12/13/2021 MWF 11:10am - 12:00pm PETT 114
8/30/2021 12/13/2021 R 6:10pm - 7:00pm KING S324
Additional Course Details: 

Course Description:

Internet of Things (IoT) has migrated from hype to the mainstream. Organizations and industries require data to be gathered from objects and value and insight to be extracted from the data. This course aims to provide a hands-on experience to the IoT system design and Artificial Intelligence (AI) based sensor data analysis. This course will provide an introduction to the cutting-edge technologies in the aspects of IoT systems and AI algorithms, including IoT architecture, sensors, low-power wireless technologies, AI for IoT, and IoT security.

Topics Covered:

  • Introduction to the applications of IoT
  • IoT architecture and core IoT modules
  • Sensors, endpoints, and power systems
  • Low-power wireless technologies
  • AI for IoT
  • IoT security

What You Will Learn:

  • What the IoT is, how it works, and what it can be used for.
  • How to design an IoT device for sensor data acquisition.
  • How to collect sensor data from IoT devices in the Cloud.
  • How to make the IoT systems smarter with AI algorithms.


Book Details
by LEA

1. IoT and Edge Computing for Architects – Implementing edge and IoT systems from sensors to clouds with communication systems, analytics, and security, Second Edition, by Perry Lea. 2. Hands-On Artificial Intelligence for IoT – Expert machine learning and deep learning techniques for developing smarter IoT systems, by Amita Kapoor.

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