IoT Specialization Syllabus

Major/Minor Specialization Scheme-AY-2022-2023(R-2020) Internet of Things Course Description Teaching Scheme (Program Specific) Semester Course Code Course Title Modes of Teaching / Learning / Weightage Hours Per Week (Approx) Theory Tutorial Practical Total Contact Credits Hours 3 3 SP-ETC-IOT-301 Introduction To Internet 3-5 - - 40 Of Things 4 SP-ETC- IOT-401 Embedded System 3-5 - - 40 3 Design With ARM 5 SP-ETC- IOT-501 Programming, Data Structures And 3-5 - - 40 3 Algorithms Using - - 40 3 Python - - 40 3 - - 40 3 6 SP-ETC- IOT-601 Cloud Computing 3-5 7 SP-ETC- IOT-701 Introduction to Machine 3-5 Learning 8 Introduction to Industry 3-5 SP-ETC- IOT-801 4.0 and Industrial Internet of Things Total (per semester) 40 0 0 240 18 1) ESE- End Semester Examination 2) Assignments can be either NPTEL Assignments/Assignments assigned to Students by Faculty Mentor 3) Students need to go through the syllabus in sequential fashion. 4) Students can do two parallel courses in a semester if he has backlog.

Syllabus for Internet of Things Specialization – R-2020 A.Y. (2022-23) S.E. Semester –III B.E. (Electronics & Communication Engineering) S.E. SEM: III Course Name: Introduction To Internet Of Things Course Code: SP-ETC-IOT-301 Teaching Scheme (Program Specific) Examination Scheme (Formative/ Summative) Modes of Teaching / Learning / Weightage Modes of Continuous Assessment / Evaluation Hours Per Week Theory Practical/Oral Term Total Theory Tutorial Practical Contact Credits Hours (100) (25) Work 3 - - 33 (25) Assignment ESE PR/OR TW 25 75 - - 100 ESE: End Semester Examination - Paper Duration - 3 Hours Prerequisite: Basic Programming Language Course Objective: To understand the basic concepts of IoT and various sensors and actuators used for sensing and actuation. The course will also enable learners to understand the working of communication protocols used in sensor networks and machine to machine communication. Learners also get introduced to Python programming and Raspberry Pi along with various applications of IoT. Detailed Syllabus: Total Hours: - 36 (12 Weeks) Module Topics NPTEL/MOOC Link No. 1 Introduction https://onlinecourses.npte Introduction to IoT, Sensing, Actuation, Basics of Networking, l.ac.in/noc23_cs83/previe Communication Protocols, Sensor Networks, Machine-to-Machine Communications, Interoperability in IoT w 2 Arduino Programming Introduction to Arduino Programming, Integration of Sensors and Actuators with Arduino 3 Python and Raspberry Pi Introduction to Python programming, Introduction to Raspberry Pi, Implementation of IoT with Raspberry P 4 SDN Introduction to SDN, SDN for IoT, Data Handling and Analytics 5 Cloud Computing Introduction to Cloud Computing, Sensor-Cloud, Fog Computing, 6 Applications and Case Study of IoT Smart Cities and Smart Homes, Connected Vehicles, Smart Grid, Industrial IoT, Case Study: Agriculture, Healthcare, Activity Monitoring Books and References:

S. Misra, A. Mukherjee, and A. Roy, 2020. Introduction to IoT. Cambridge University Press. 1 https://www.amazon.in/Introduction-IoT-Sudip- Misra/dp/1108959741/ref=sr_1_1?dchild=1&keywords=sudip+misra&qid=1627359928&sr=8-1 S. Misra, C. Roy, and A. Mukherjee, 2020. Introduction to Industrial Internet of Things and Industry 4.0. CRC 2 Press. https://www.amazon.in/dp/1032146753/ref=sr_1_3?dchild=1&keywords=sudip+misra&qid=1627359971&sr=8-3 3 Learning Internet of Things by Peter Waher, ISBN-13 : 978-1783553532 One Module =Approx. 2 weeks

Syllabus for Internet of Things Specialization – R-2020 A.Y. (2022-23) S.E. Semester –IV B.E. (Electronics & Communication Engineering) S.E. SEM: IV Course Name: Embedded System Design With ARM Course Code:SP-ETC-IoT-401 Teaching Scheme (Program Specific) Examination Scheme (Formative/ Summative) Modes of Teaching / Learning / Weightage Modes of Continuous Assessment / Evaluation Hours Per Week Theory Practical/Oral Term Total (100) (25) Work (25) Theory Tutorial Practical Contact Credits Assignment ESE PR/OR TW Hours 3 - - 3 3 25 75 - - 100 ESE: End Semester Examination - Paper Duration - 3 Hours Prerequisite: Basic concepts in digital circuits and microprocessor Course Objective: The course intends to deliver the systematic study to understand the basic concepts of embedded system design using ARM microcontrollers & its interfacing with sensors and actuators and finally to understand the developmental aspects of Internet of Things (IoT) based designs. Detailed Syllabus: Total Hours: - 42 hours (14 Weeks) Module Topics NPTEL/MOOC Link No. 1 Introduction to embedded systems https://onlinecourses.nptel.ac.in /noc22_cs93/preview 2 Introduction to embedded systems and microcontrollers, Characteristics 3 of an Embedded System, Basic Structure of an Embedded System, advantages and disadvantages, microcontrollers 4 Programming with ARM microcontroller 5 Instruction set architecture of ARM microcontroller, and assembly 6 language programming Interfacing of ARM microcontroller D/A and A/D converter, sensors, actuators and their interfacing, Microcontroller development boards and embedded programming platforms Applications of ARM microcontroller Applications using Temperature sensing unit, Light sensing unit, Sound sensing unit,Feedback control system, relay control unit, driving electrical appliances like motors, bulb, pump, Designing Embedded System using ARM microcontroller Applications Object tracking using GPS and GSM Project to design Embedded system Project to design an Embedded system using ARM microcontroller

Books and References: F. Vahid and T. Givargis, “Embedded System Design: A Unified Hardware/Software 1 Introduction”, Wiley India Pvt. Ltd., 2002. A.N. Sloss, D. Symes and C. Wright, “ARM System Developer’s Guide: Design and Optimizing 2 System Software”, Morgan Kaufman Publishers, 2004. W. Wolf, “Computers as Components: Principles of Embedded Computing System Design”, 3 Morgan Kaufman Publishers, 2008. One Module =Approx. 2 weeks

Syllabus for Internet of Things Specialization – R-2020 A.Y. (2022-23) S.E. Semester –V B.E. (Electronics & Communication Engineering) S.E. SEM: V Course Name: Programming, Data Structures Course Code: SP-ETC-IoT-501 And Algorithms Using Python Examination Scheme (Formative/ Summative) Teaching Scheme (Program Specific) Modes of Teaching / Learning / Weightage Modes of Continuous Assessment / Evaluation Hours Per Week Theory Practical/Oral (25) Term Total (100) Work (25) Theory Tutorial Practical Contact Credits Assignment ESE PR/OR TW Hours 3- - 33 25 75 - - 100 ESE: End Semester Examination - Paper Duration - 3 Hours Prerequisite: Basic concepts of Mathematics Course Objective: The aim of this course is to develop the basic understanding of programming using concepts of python and problem solving in python and to understand concepts of searching and sorting algorithms, dynamic programming & data structures Detailed Syllabus: Total Hours: - 42 hours (14 Weeks) Module Topics NPTEL/MOOC Link No. 1 Introduction to Python 2 Informal introduction to programming, algorithms, and data structures, 3 Downloading and installing Python, Python: variables, operations, control 4 flow - assignments, conditionals, loops, functions 5 Python Language Syntax Python types, expressions, strings, lists, tuples Python memory model: names, mutable and immutable values, List operations: slices etc. Binary search Inductive function definitions: numerical and structural induction, Elementary inductive sorting: selection and insertion sort, In-place sorting Basic algorithmic analysis https://onlinecourses.nptel. Input size, asymptotic complexity, O() notation, Arrays vs lists, Merge sort ac.in/noc23_cs95/preview Quicksort, Stable sorting, More on Python functions: optional arguments, default values Passing functions as arguments, Higher order functions on lists: map, lter, list comprehension, Python Exception Handling & Backtracking Exception handling, Basic input/output, Handling files, String processing, Backtracking: N Queens, recording all solutions, Scope in Python: local, global, nonlocal names, Nested functions, Data structures: stack, queue Heaps Python Data types and Dynamic programming Abstract datatypes, Classes and objects in Python \"Linked\" lists: find, insert, delete, Binary search trees: find, insert, delete, Height-balanced binary search trees, Efficient evaluation of recursive definitions: memorization Dynamic programming: examples, Other programming languages: C and

manual memory management Other programming paradigms: functional programming 6 Python Capstone Project Implementation of python skills through project Books and References: 1. Beginning Python: Using, Python 2.6 and Python 3.1, James Payne, Wrox Publication Second 2010 2. Core Python Programming Dr. R. Nageswara Rao Wiley Publication Third 2017 3. Beginning Python From Novice to Professional Magnus Lie Hetland, Apress Publication Second 2015 4. Core Python Applications Programming Wesley J Chun Pearson Publication Third 2017 One Module =Approx. 2 weeks .

Syllabus for Internet of Things Specialization – R-2020 A.Y. (2022-23) S.E. Semester –VI B.E. (Electronics & Communication Engineering) S.E. SEM: VI Course Name: Cloud Computing Course Code: SP-ETC- IOT-601 Teaching Scheme (Program Specific) Examination Scheme (Formative/ Summative) Modes of Teaching / Learning / Weightage Modes of Continuous Assessment / Evaluation Hours Per Week Theory Practical/Oral Term Total Theory Tutorial Practical Contact Credits Hours (100) (25) Work 3 - - 33 (25) Assignment ESE PR/OR TW 25 75 - - 100 ESE: End Semester Examination - Paper Duration - 3 Hours Prerequisite: Basics of Computer Architecture and Organization, Networking Course Objective: To understand cloud computing as a model for enabling ubiquitous, on-demand access to a shared pool of configurable computing resources, which can be rapidly provisioned and released with minimal management effort. This course will introduce various aspects of cloud computing, including fundamentals, management issues, security challenges and future research trends. Detailed Syllabus: Total Hours: - 36 (12 Weeks) Module Topics NPTEL/MOOC Link No. 1 Architecture Cloud Computing – Overview, Introduction, Architecture, Deployment Models, Virtualization, XML Basics 2 Services Web Services, Service Oriented Architecture, Service Level Agreement (SLA), Economics, Managing Data, Introduction to Map Reduce, Open Stack, Open Source Cloud, Openstack Demo https://onlinecourses.npte l.ac.in/noc22_cs87/previe 3 Case Study w Case study with a commercial cloud: Microsoft Azure, Demo, Case Study: Google Cloud Platform (GCP), Demo on Google Cloud Platform ( GCP ), SLA – Tutorial, Economics Tutorial, MapReduce, Resource Management 4 Security Cloud Security, Cloud Security, Cloud Security, Broker for Cloud Marketplace 5 Various Platforms Mobile Cloud Computing, Fog Computing, Use Case: Geospatial Cloud 6 Implementation & Scope

Introduction To DOCKER Container, Green Cloud, Sensor Cloud Computing, IoT Cloud, Course Summary and Research Areas Books and References: 1 Cloud Computing: Principles and Paradigms, Editors: Rajkumar Buyya, James Broberg, Andrzej M. Goscinski, Wiley,2011 2 Enterprise Cloud Computing - Technology, Architecture, Applications, Gautam Shroff, Cambridge University Press, 2010 3 Cloud Computing Bible, Barrie Sosinsky, Wiley-India, 2010 Cloud Security: A Comprehensive Guide to Secure Cloud Computing, Ronald L. Krutz, Russell Dean Vines, 4 Wiley- India,2010 One Module =Approx. 2 weeks

Syllabus for Internet of Things Specialization – R-2020 A.Y. (2022-23) S.E. Semester –VII B.E. (Electronics & Communication Engineering) S.E. SEM: VII Course Name: Introduction to Machine Learning Course Code: SP-ETC- IOT-701 Teaching Scheme (Program Specific) Examination Scheme (Formative/ Summative) Modes of Teaching / Learning / Weightage Modes of Continuous Assessment / Evaluation Hours Per Week Theory Practical/Oral Term Total Theory Tutorial Practical Contact Credits Hours (100) (25) Work 3 - - 33 (25) Assignment ESE PR/OR TW 25 75 - - 100 ESE: End Semester Examination - Paper Duration - 3 Hours Prerequisite: Basics programming skills, Knowledge of probability theory and linear algebra Course Objective: To understand the basic concepts of machine learning from a mathematically well motivated perspective. This course covers different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms. Detailed Syllabus: Total Hours: - 36 (12 Weeks) Module Topics NPTEL/MOOC Link No. 1 Introduction Probability Theory, Linear Algebra, Convex Optimization, Probability Theory, Linear Algebra, Convex Optimization 2 Regression Linear Regression, Multivariate Regression, Subset Selection, Shrinkage Methods, Principal Component Regression, Partial Least squares, Linear Classification, Logistic Regression, Linear Discriminant Analysis 3 Neural Networks Perceptron, Support Vector Machines, Neural Networks - Introduction, https://onlinecourses.npte Early Models, Perceptron Learning, Backpropagation, Initialization, l.ac.in/noc23_cs98/previe Training & Validation, Parameter Estimation - MLE, MAP, Bayesian Estimation w 4 Algorithms I Decision Trees, Regression Trees, Stopping Criterion & Pruning loss functions, Categorical Attributes, Multiway Splits, Missing Values, Decision Trees - Instability Evaluation Measures, Bootstrapping & Cross Validation, Class Evaluation Measures, ROC curve, MDL, Ensemble Methods - Bagging, Committee Machines and Stacking, Boosting 5 Algorithms II Gradient Boosting, Random Forests, Multi-class Classification, Naive Bayes, Bayesian Networks, Undirected Graphical Models, HMM, Variable Elimination, Belief Propagation

6 Algorithms III Partitional Clustering, Hierarchical Clustering, Birch Algorithm, CURE Algorithm, Density-based Clustering, Gaussian Mixture Models, Expectation Maximization, Learning Theory, Introduction to Reinforcement Learning, Optional videos Books and References: 1 The Elements of Statistical Learning, by Trevor Hastie, Robert Tibshirani, Jerome H. Friedman 2 Pattern Recognition and Machine Learning, by Christopher Bishop One Module =Approx. 2 weeks

Syllabus for Internet of Things Specialization – R-2020 A.Y. (2022-23) S.E. Semester –VIII B.E. (Electronics & Communication Engineering) S.E. SEM: VIII Course Code:SP-ETC-IOT-801 Course Name: Introduction To Industry 4.0 And Industrial Internet Of Things Teaching Scheme (Program Specific) Examination Scheme (Formative/ Summative) Modes of Teaching / Learning / Weightage Modes of Continuous Assessment / Evaluation Hours Per Week Theory Practical/Oral Term Total Theory Tutorial Practical Contact Credits Hours (100) (25) Work 3 - - 33 (25) Assignment ESE PR/OR TW 25 75 - - 100 ESE: End Semester Examination - Paper Duration - 3 Hours Prerequisite: Embedded system and Internet of Things (IoT) Course Objective: To understand the Industry 4.0 concerns, the transformation of industrial processes through the integration of modern technologies such as sensors, communication, and computational processing. And to understand that Industrial Internet of Things (IIoT) is an application of IoT in industries to modify the various existing industrial systems. Detailed Syllabus: Total Hours: - 36 (12 Weeks) Module Topics NPTEL/MOOC Link No. 1 Introduction to IoT Connectivity and Networking https://onlinecourses.npte Introduction to IoT Communication, IoT networking, Industrial Sensing l.ac.in/noc22_cs95/previe 2 and Actuation, Industry 4.0: Globalization and Emerging Issues, The Fourth Revolution, LEAN Production Systems, Smart and Connected w 3 Business Perspective, Smart Factories 4 Industry 4.0 Industry 4.0: The Fourth Revolution, Sustainability Assessment of 5 Manufacturing Industry, Lean Production System, Smart and Connected Business Perspective, Smart Factories, Collaboration Platform and Product Lifecycle Management Security in IIoT CyberPhysical Systems and Next-Generation sensors, Augmented reality and Virtual reality, Artificial Intelligence, Big-Data and Advanced Analysis, Cybersecurity Industrial Processes Basics of Industrial IoT, Industrial Processes, Business Models and Reference Architecture for IIoT, Key enablers of Industrial IoT: Sensing and Connectivity, Processing and Process Control IIoT Analytics and Data Management

Introduction, Machine Learning and Data science, cloud Computing and Fog Computing in IIoT, data management with Hadoop, Software defined Networking 6 IIoT Applications Factories and Assembly line, Food Industry, Oil, Chemical and Pharmaceutical Industry, Milk Processing and Packaging industry, Inventory Management and Quality Control, Plant Security and Safety, Facility Management, UAVs in Industries, Manufacturing Industries, Case Studies Books and References: S. Misra, A. Mukherjee, and A. Roy, 2020. Introduction to IoT. Cambridge University Press. Availability: https://www.amazon.in/Introduction-IoT-Sudip- Misra/dp/1108959741/ref=sr_1_1?dchild=1&keywords=sudip+misra&qid=1627359928&sr=8-1 1 2) S. Misra, C. Roy, and A. Mukherjee, 2020. Introduction to Industrial Internet of Things and Industry 4.0. CRC Press. Availability: https://www.amazon.in/dp/1032146753/ref=sr_1_3?dchild=1&keywords=sudip+misra&qid =1627359971&sr=8-3 2 One Module =Approx. 2 weeks