IC3IoT 2018 | 15-17 February 2018

Short Courses

The conference program includes Short Courses, which will be conducted by leading experts in the field. Details will get updated in the conference website and available in subsequent mailings. As of now we have the following Short Courses confirmed:

Course 1

Introduction to Internet of Things (IoT) and Smart Technologies (ST)

Course Leader

Mr. Vignesh Govindraj, Research Engineer Teller Comm Private Limited, Bangalore, India
Mr. Mithileysh Sathiyanarayanan, Research Scientist Red Sift, London

Date/Time

15 February 2018 / 12:00noon - 5pm

Fee

Rs. 1000 (local) / USD 150 (overseas)
(includes, Certificate, short course kit, buffet lunch & tea/coffee network session)

Who Should Attend

This course is designed for anyone who:

  • wants to understand big data landscape;
  • wants to analyze enormous amounts of data;
  • wants to work in Hadoop and its eco-system components, and
  • have a programming background and want to take career to next level.

  Limited seats, on first-come first-serve basis.           

Course 2

Signal Processing, Image Processing and Deep Learning Techniques for the Development of Intelligent Healthcare Systems

Course Leader

Dr. E.Priya
Asst. Professor,
Department of ECE,
Sri Sairam Engineering College,

Date/Time

16 February 2018 and 17 February 2018 / 11:00am to 4:45pm

Fee

Rs. 1000 (local) / USD 150 (overseas)
(includes, Certificate, short course kit, buffet lunch & tea/coffee network session)

Who Should Attend

This course is designed for anyone who:

  • wish to understand the concepts in signal and image analysis for real time applications
  • is looking for a research career in signal and image processing sector
  • is interested in deep learning techniques for the development of automated decision support system
  • wants to explore the optimization techniques

  Limited seats, on first-come first-serve basis.           

     

Course 1

Introduction to Internet of Things (IoT) and Smart Technologies (ST)

Course Leader

Mr. Vignesh Govindraj,
Research Engineer Teller Comm Private Limited, Bangalore, India
Mr. Mithileysh Sathiyanarayanan,
Research Scientist Red Sift, London








Abstract
Internet of Things (IoT) is a popular buzzword and currently a hot technology worldwide. The “Internet of Things” describes an important technology trend which is having lasting effects on society at large.Government, academia, and industry are involved in different aspects of research, implementation, and business with IoT. IoT cuts across different application domain verticals ranging from civilian to defence sectors. These domains include agriculture, space, healthcare, manufacturing, construction, water, and mining, which are presently transitioning their legacy infrastructure to support IoT. Today it is possible to envision pervasive connectivity, storage, and computation, which, in turn, gives rise to building different IoT solutions. IoT-based applications such as innovative shopping system, infrastructure management in both urban and rural areas, remote health monitoring and emergency notification systems, and transportation systems, are gradually relying on IoT based systems. Interesting, the explosive growth of the “Internet of Things” is changing our world and the rapid drop in price for typical IoT components is allowing people to innovate new designs and products at home. Therefore, it is very important to learn the fundamentals of this emerging technology.
This course aims to give:

  • a solid grounding in the key technologies involved and how they're integrated to form complete IoT systems
  • an understanding of how the internet of things fits within the wider context of the ICT industry
Key Points and Features
  • Learn the latest trends, applications and products on IoT domains
  • Learn about cutting edge technologies on which you can pursue higher studies or work in companies
  • Learn and understand how to make rapid prototypes
  • Networking and mentoring opportunities from internationally recognized experts
  • Social networking with peers
  • Many papers related to IoT and other inter-connected domains will be discussed
  • Opportunity to practically learn 1:1 in this course
  • Internship opportunities at IoT Start-ups in Bangalore


Course Outline

     
  1. Introduction to IoT
    • The role of IoTin different domains
    • Challenges and opportunities of using IoT
    • Introduction to IoT and Architectural elements
    • Learning the definition and usage of the term “internet of things” in different contexts
    • Understanding where the IoT concept fits within the broader ICT industry and possible future trends
    • An overview of key concepts and challenges related to smart technologies.
    • Understanding the various network protocols used in IoT
    • Understanding the key wireless technologies used in IoT systems, such as WiFi, 6LoWPAN, bluetooth and ZigBee.
    • Understanding the IoT Ecosystem and the Stack
    • An overview of IoT protocols – A comparison
    • Examining the evolution of the Internet and how the interconnection of people, processes, data, and things is transforming every industry.
  2. Design and Development
    • IoT architecture, hardware, software and protocols
    • Designing the IoT hardware and software
    • RTOS for IoT
    • IoT design considerations, constraints and interfacing between the physical world and the developed device
    • The building blocks of IoT device hardware – Thing, Data acquisition module, Data acquisition module, communications module
    • Challenges and constrains in designing the IoT hardware
    • Introduction to sensors and microcontrollers – Selecting the right controller for your design
    • Opensource RTOS for IoT – Contiki, Zephyr &FreeRTOS
    • Implementation of IoT with Raspberry Pi
    • Interoperability in IoT, Introduction to Arduino Programming
    • Basics of Networking: communication protocols
  3. IoT Applications and use cases
    • Smart Humans – Medical IoT
    • IIoT – Industrial IoT
    • Smart Homes and cities
    • IoT in Agriculture
    • Understanding the role of IoT in various applications and their impact
  4. The Future of IoT
    • Where is IoT heading?
    • Emergence of Big Data, Analytics and Data Science
    • Internet of ‘Threat’?
    • IoT security
    • Understanding the role of big data, cloud computing and data analytics in a typical IoT system
    • Understanding the need for security in IoT
    • Learn the security concerns that must be considered when implementing IoT solutions.
    • Discussion on the ramifications that IoT is having on society today
    • Learn how to make design trade-offs between hardware and software.
    • Learn how the Internet of Everything(IoE) is completely replacing the Internet of things (IoT).

    Upon completing this course, you will be able to:
    1. Define the term “Internet of Things”
    2. State the technological trends which have led to IoT
    3. Describe the impact of IoT on society
    4. Define what an embedded system is in terms of its interface
    5. Enumerate and describe the components of an embedded system
    6. Describe the interactions of embedded systems with the physical world
    7. Name the core hardware components most commonly used in IoT devices
    8. Describe the interaction between software and hardware in an IoT device
    9. Describe the role of an operating system to support software in an IoT device
    10. Describe the structure of the Internet and explain the use of networking and basic networking hardware

Who Should Attend

The course is designed for

  • BE/ME/M.Tech Engineering Students (CSE, IT, ECE, EEE, Instrumentation and Industrial Engineering)
  • Academic and Research Students/faculties (including PhD or Post-doc)
  • Internship students
  • Industrial employees

The course will help one to:

  • understand Internet of Things (IoT) and Smart Technologies (ST)
  • develop simple and/or complex prototyes, and
  • work with real-time components

 

Course 2

Signal Processing, Image Processing and Deep Learning Techniques for the Development of Intelligent Healthcare Systems

Course Leader

Dr. E.Priya
Asst. Professor,
Department of ECE,
Sri Sairam Engineering College,









































Abstract
In this digital era, signal and image processing is very promising multidisciplinary research domain. The proposed short course intends to report on the latest trend and progress in the development of signal, image processing and deep learning techniques. It aims to provide a platform for researchers working in this area to explore the techniques supported by case studies and practical examples.
The objective of this course is to make the participants understand the challenges in proposed domain, update the content of the area and explore it for academic and research purpose in right away. This short course is intended to create a platform to deliberate the state-of-the-art research perspectives and findings relevant to image and signal processing. The course will help the participants to expand their expertise in processing, analysis of images and signals in healthcare. It also aims to ascertain the latest research issues, ideas and happenings relevant to domain area.
This course will bridge the gap between signal, image processing and healthcare system and present a collection of high-quality research work that report the latest advances in the area.
Potential uses:
1. The participants will be able to know the latest application area of signal and image processing in developing tools for healthcare systems.
2. This short course will give an insight on various algorithms in signal, image processing and novel machine learning techniques such as deep learning which will motivate the faculty and research scholars for carrying out their research work in the domain.
3. The sessions are aimed at giving all the participants a better understanding of concepts.
4. A better exposure to different avenues of research opportunities in the proposed domain.
Topics:
1. Pre-processing techniques in context to signal and image processing
2. Segmentation relevant to 1D and 2D
3. Advanced feature extraction techniques
4. Novel feature reduction techniques
5. Deep learning techniques
6. Optimization techniques
7. Case studies


Course Outline
1. Pre-processing techniques in context to signal and image processing
The topic involving pre-processing procedure helps in the understanding to remove the artifacts present in the raw signal or image. It provides functions to denoise and smooth signal or image to prepare them for further analysis.
2. Segmentation relevant to 1D and 2D
Segmentation is often required as the first processing step and it is the most crucial among all computerized operations done on the recorded signal or acquired images. In spite of several decades of research, segmentation remains a challenging concern in signal, image processing and computer vision.
3. Advanced feature extraction techniques
The method of feature analysis relies on an appropriate representation of shape or appearance and developing that representation for further classification. It plays a crucial role in a variety of applications due to its invariant properties on translation, scaling and rotation. This topic mainly focuses on combining and refining the most informative feature sets or techniques.
4. Novel feature reduction techniques
Novel feature selection is aimed these days as the use of superfluous features often leads to inferior performance in signal processing and pattern recognition techniques. Feature selection is aimed in selecting significant features which would retain the original physical interpretation with reduced computational time.
5. Deep learning techniques
It includes the fundamentals in the field of Deep learning (a subfield of machine learning) and image processing supported by case studies and practical examples. This topic covers an in-depth analysis of real life applications of neural networks to signal and image analysis.
6. Optimization techniques
The optimization techniques aid in finding the optimum solution by finding the finest set of parameters without violating the constraint mentioned in the problem. Optimization techniques play a major role in many of the industry based application and is the need of the hour.
7. Case studies
Case studies of real time signal and image processing applications involving deep learning procedures are intended to be discussed during each topic.

Upon completing this course the participants will be able to:
1. Understand the various system components implicated in the processing and analysis of signals and images.
2. Novel and emerging procedures in the analysis of signals and images involving machine learning such as deep learning techniques.
3. Develop a computer assisted automated system for healthcare diagnostics.
4. Develop computing tools for decision support system.

Who Should Attend

The course is designed for

  • BE/ME/M.Tech Engineering Students (CSE, IT, ECE, EEE, Instrumentation and Industrial Engineering)
  • Academic and Research Students/faculties (including PhD or Post-doc)
  • Internship students
  • Industrial employees
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