EE701: The Internet of Things: From Technology to Applications


Within the last two decades, major breakthroughs in the field of electronics, embedded systems and wireless communications have paved the way for the development of the Internet of Things (IoT). The IoT defines a truly cyber-physical system in which all sorts of physical devices, ranging from sensors and actuators to home appliances and even vehicles, are interconnected and able to autonomously interact with each other. This new form of seamless connectivity is the enabler of many diverse applications in the fields of smart healthcare, home monitoring and automation, environmental monitoring and pollution control, smart grid and infrastructure management, real time monitoring of industrial processes, and intelligent transportation of people and goods, among many others. The development of the IoT has been the focus of many research initiatives worldwide for almost two decades, and multi-billion investments were and are still being made by both governmental agencies and the private sector.

In this course, the state of the art in communication, networking and data collection technologies for the IoT will be introduced through a series of theoretical lectures and laboratory projects. In the lectures, a flipped classroom strategy will be followed to cover the main steps in the data path, including data acquisition, local data processing, data communication, data stream, data storage & cloud and data analytics. In the laboratory sessions, students will work in teams to realize a specific application of the IoT. The starting point will be state-of-the-art system-on-chip (SoCs) able to support the main technologies for the IoT (including Low-Power Wide Area Network). At the end of the semester, students will demonstrate their project to a broader audience, potentially involving key stakeholders in the IoT realm.

Objectives and Expected Outcomes

This course will provide the students with the advanced competitive skills required to contribute to the development of the IoT.

By the end of the course, students will be able to:

  • Identify and describe the main device architecture and components in IoT systems
  • Identify and describe the main data collection, transmission, storage and analysis tools for the IoT
  • Design, build and integrate an IoT board, which incorporates micro-controllers, radio transceivers, antennas and power units
  • Participate effectively in a team project and assess the strengths and weaknesses of the individual team members (including himself or herself) and the team as a unit
  • Find relevant sources of information about a specified topic in the library and on the world wide web
  • Write an effective project report to present technical knowledge to a variety of audiences
  • Conduct a live demonstration of their team projects in front of an audience

Class Contents

  1. Introduction: IoT definition, Use-cases and Business Opportunities
  2. Data acquisition: Sensors and fundamentals of circuits
  3. Local data processing: IoT boards & SoC
  4. Data communication: Wireless technologies for the IoT (WPAN, WLAN, LPWAN)
  5. Data stream: Application protocols enabling data stream from the gateway to the cloud
  6. Data storage & cloud: Distributed databases, Web semantics, IoT cloud architectures
  7. Data analytics: Data mining for the IoT and knowledge extraction
  8. System integration: Frameworks and technologies enabling the integration of IoT devices with mobile apps or other smart devices


Background knowledge in wireless communication, networking and embedded systems is required. Students should have taken Principles of Networking and, ideally, Principles of Cellular Networks, Digital Communication Systems Design and Implementation and/or Embedded Systems.

Course Organization

  • Class and Homework Assignments: 4 assignments to be solved individually
  • Laboratory Guided Assignments: 3 assignments to be solved in teams of 2 students
  • Laboratory Project: To be completed in teams of 4 students
  • Final Exam: Open-book

Grade Distribution

Class/Homework Assignments: 25%
Guided Laboratory Assignments: 15%
Laboratory Project: 30%
Final Exam: 25%
Class Participation and Professionalism: 5%

Course Materials

All the class materials will be able on UBLearns.


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since August 2, 2013.