This course exposes students to the fundamentals of IoT as a paradigm in addition to the foundational problems inherent in this realm. The course will introduce the basic terminology and ecosystem, plus development environments. Topics include IoT hardware and software platforms, data collections and analytics for IoT, security and ethical issues inherent in IoT, and networks programming for IoT.  The course explores The course explores problem solving for IoT analytics based on machine learning and deep learning using TensorFlow.  The course will run as a seminar-style readings, discussions, labs, and presentations by the students.   Students will have a semester-long project using a Raspberry PI 3.

Students shall be able to:

1. Understand key IoT concepts;
2. Explore IoT technologies, architectures, standards, and regulation;
3. Understand how to develop and implement own IoT technologies, solutions, and applications;
4. Analyze data collected from IoT sensors and devices using modern analytics approaches;
5. Demonstrate understanding of security and ethical issues inherent in IoT.

August 28, 2017: Fall classes begin

September 26, 2017: Midterm Examination

October 3, 2017:  Last day for early withdrawal (WI)

October 24, 2017: Deadline for Incomplete grades

November 7, 2017: Last day for withdrawal from courses (WP/WF)

December 7, 2017: Fall classes end

Professor Haidar M. Harmanani

haidar@lau.edu.lb • http://vlsi.byblos.lau.edu.lb • http://harmanani.github.io

Office Hours:

Block A • Room 810

Tuesday, Thursday • 3:00pm – 4:30pm • 8:00pm – 9:30pm or by appointment

Lecture notes are made available here in PDF formats. Additional readings will be posted under the resources section in this page.

Lecture 01: : Introduction, Challenges and Opportunities

Lecture 02: IoT Hardware Platforms

Lecture 03: Using the Pi for the First Time

Lecture 04: Wireless Networks

Lecture 05: Wireless Sensor Networks

Lecture 06: IoT Application Layer, Integration Patterns, REST, and CoAp  MQTT CoAP

Lecture 07: Software Platforms and Services

Lecture 08: IoT Web Programming

Lecture 09: Databases for IoT

Lecture 10: Introduction to Machine Learning RapiMiner

Lecture 11: IoT Data Analytics

Lecture 12: Deep Learning for IoT Using TensorFlow

Lecture 13: Cloud Computing and the IoT

Lecture 14: Wearables and Motion Sensing

Lecture 15: Fog Computing: Smart Homes and Cities

Lecture 16: Connected Vehicles

Lecture 17: Computer Vision for IoT

Lab 1: TBA

Lab 2: TBA

Lab 3: TBA

Lab 4: TBA

Lab 5: TBA

Project: TBA

All students are expected to take exams during the scheduled time slots. With the permission of the instructor, you may be allowed to take an exam at an alternate time. However, you must request this rescheduling at least 2 weeks prior to the exam date. Exceptions will naturally be made for sudden problems such as serious illnesses/injury. Since the exam schedule is being published at the beginning of the semester, scheduling conflicts (e.g., job interviews, GREs, etc.) are not legitimate reasons to miss an exam.

Midterm Exam

The midterm exam is scheduled for February 16, 2016: Midterm Examination. The midterm exam will be a closed book exam. In principle, all topics discussed in class (whether on the lecture notes or not) and in the assigned readings are a legitimate source for exam questions.

Previous Midterm Exam (Spring 2009)

Previous Midterm Exam Key (Spring 2009)

Final Exam

The final will be comprehensive, with roughly 1/3 of the material devoted to material covered prior to the midterm.  The exam will be on May 15, 2015 from 8:00 am - 11:00 am.

The exam will cover the following sections in the textbook:

• Chapter 1: 1.1-1.8
• Chapter 2: 2.1-2.10, 2.12-2.13
• Chapter 3: 3.1-3.5
• Chapter 4: 4.1-4.6
• Chapter 5: 5.1-5.3

Midterm Grades

Assignments Grades

Project Grades

• Install Raspian on your SD card
• Setting up Bluetooth on the Raspberry Pi 3
• NOOBS
• Mathematica and the Pi
• Initial State: Data Analytics for the Internet of Things
• RapidMiner
• Tableau Visualization Tool
• C5.0
• Weka
• C3IoT
• Local Stores
• OpenVN: Build an SSL-VPN server for your Pi
• Node-Red: Flow-based programming for the Internet of Things
• Get Started with Contiki
• OpenCV

• Raspberry Pi Foundation
• Building the Internet of Things with Raspberry Pi
• Ideas and Recipes For Home Automation With The Internet of Things
• How to Send Tweets From Your Raspberry Pi
• Home automation using R Pi + Alexa + IoT
• Raspberry Sprinkle
• Temperature & Humidity Network Monitor

Essential Readings

• Efficient Reading of Papers in Science and Technology
• How to Read a Scientific Paper

Machine Learning

• Deep Learning Book
• Machine Learning Tutorial
• Introduction to TensorFlow

Internet Of Things

• Internet of things: Vision, applications and research challenges
• Towards Physical Mashups in the Web of Things
• CoAP: An Application Protocol for Billions of Tiny Internet Nodes
• The Internet of Things: A survey
• Internet of things security
• Manufacturing Analytics and Industrial Internet of Things

• Semantic Reasoning for Context-Aware Internet of Things Applications
• A Survey on Internet of Things From Industrial Market Perspective
• Internet of Things and Big Data Analytics for Smart and Connected Communities
• The Internet of Things for Health Care: A Comprehensive Survey
• On Networking of Internet of Things: Explorations and Challenges
• Green Internet of Things for Smart World