syllabus of Industry 4.0

1. Semester – IV Paper – XI
Course Code: BSC-DS 411T Title of the Course: Industry 4.0
Credits: 02 Total Lectures: 30Hrs.
Course Outcomes (COs):
a. To have good conceptual clarity about the ‘why’, ‘what’ and ‘how’ of Industry 4.0
b. To understand and appreciate the science of blockchain technology
c. To appreciate the convergence of Data Science with Cloud Computing and related areas.
d. To have awareness emerging trends in Industry 4.0 and related challenges
e. To understand Best Practices of data science in industry 4.0 areas.
Detailed Syllabus:
Unit - I Conceptual Background of Industry 4.0 08
1.1 Forth Industrial Revolution in 21st
Century,
1.2 Data Industry and its Importance in Industry 4.0,
1.3 Data Economy, Fintech, Health-Tech, Edu-Tech, etc.
1.5 Hardware & Software Technologies for Industry 4.0: Machine
Learning, Artificial Intelligence, Internet of Things, Blockchain, Big
Data & Analytics, Cloud Computing; Cyber-Physical-Systems,
1.6 Convergence of these Technologies, Industry Ecosystems,
1.7 Industrial Internet Use Cases, Smart Industries, Smart Factories, Smart
Cities, Smart Transport, Smart CX, etc.
Unit-II Distributed Ledger Technology: The Science of the Blockchain 07
2.1 Distributed Computing Paradigm, Distributed Ledger Technology
concepts,
2.2 Fault-Tolerance, Consensus, Byzantine Agreement
2.3 Cryptography Basics, Authenticated Agreement, Quorum Systems,
Smart Contracts & Crypto-Currencies
2.4 Distributed Storage
Unit-III Cloud Computing, Edge Computing 07
3.1 Cloud Computing, Edge Computing
3.2 BDA, Data Lake, Data Pipelines
3.3 Smart Internet

2. Unit-IV Industry 4.0, AI, and Data Science: Trends and Challenges 08
4.1 Predicting Fraudulent Motor Vehicle Insurance Claims Using Data
Mining Model
4.2 Multiplexer for Low Power and Area Efficient Design in Industry 4.0
4.3 Data Science and AI for E-Governance: A Step towards Society 5.0
4.4 Application Areas of Data Science and AI for Improved Society 5.0 Era
4.5 Applying Machine-Learning and Internet of Things in Healthcare
4.6 Artificial Intelligence: The New Expert in Medical Treatment
4.7 Machine Learning Approach for Breast Cancer Early Diagnosis
4.8 Intelligent Surveillance System Using Machine Learning
4.9 Cyber Security: An Approach to Secure IoT from Cyber Attacks Using
Deep Learning
4.10 Learning the Dynamic Change of User Interests from Noise Web Data
4.11 Artificial Intelligence Techniques Based Routing Protocols in VANETs:
A Review
4.12 A Comparison of Different Consensus Protocols
4.13 The Backbone of the Blockchain Technology
4.14 Blockchain in AI: Review of Decentralized Smart System
4.15 Financial Portfolio Optimization: An AI Based Decision-Making
Approach
4.16 Intelligent Framework and Metrics for Assessment of Smart Cities
4.17 Best Practices of Data Science in Industry 4.0 areas.
Suggested Readings:
1) The Concept Industry 4.0: An Empirical Analysis of Technologies and Applications in
Production Logistics, By Christoph John Bartodziej, Springer Gabler Publication, 2017
2) Industry 4.0: The Industrial Internet of Things, By Alasdair Gilchrist, Apress Publication,
2016
3) Industry 4.0, AI, and Data Science: Research Trends and Challenges, ByVikram Bali,
Kakoli Banerjee, Narendra Kumar, Sanjay Gour, Sunil Kumar Chawla, 1st Edition (2021)
4) Distributed Ledger Technology: The Science of the Blockchain, Roger Wattenhofer,
Inverted Forest Publishing (2017)

3. Semester – IV Paper – XII
Course Code: BSC-DS 412 P Title of the Course: Lab based on Industry 4.0
Credits: 02 Total Lectures: 30Hrs.
Course Outcomes (COs):
a. To have good conceptual clarity about the ‘why’, ‘what’ and ‘how’ of Industry 4.0
b. To understand and appreciate the science of blockchain technology
c. To appreciate the convergence of Data Science with Cloud Computing and related areas.
d. To have awareness emerging trends in Industry 4.0 and related challenges
e. To understand Best Practices of data science in industry 4.0 areas.
Detailed Syllabus:
Unit - I Students are expected to complete case studies on the Unit 08