Emerging Technologies Chapter 1, 2 and 3 module
Page 1: Introduction to Emerging Technologies
Presenter: Zebiba Ahmed
Affiliation: MIIM&HSC
Page 2: Table of Contents
Overview of topics:
Introduction to Emerging Technologies
Data Science
Artificial Intelligence (AI)
Augmented Reality (AR)
Ethics and Professionalism of Emerging Technologies
Other Emerging Technologies
Internet of Things (IoT)
Page 3: Assessment
Breakdown of assessment criteria:
Assignment / Quiz / Attendance: 20%
Test: 30%
Final Exam: 50%
Page 4: What is Emerging Technology (ET)?
Defines ET as:
Technologies currently developing or expected to have significant social or economic impacts.
Technologies in development and testing to ensure efficacy for mass production.
Page 5: Introduction to ET
Definitions vary across fields (media, business, education).
In education, ET includes tools and innovations for educational purposes.
Page 6: General Definition of ET
ET generally involves:
Technologies based on new ideas that are creating significant effects in society.
Page 7: Characteristics of Emerging Technologies
Tools, engaging software, hardware concepts, ideas:
Provide opportunities for creativity and collaboration.
May threaten existing systems or norms.
Often misunderstood or not well-known.
Page 8: Technological Evolution
Describes radical transformation via technological development:
Changes over time provide humans greater control over the environment.
Page 9: Technological Convergence
Interlinking of computing, information technologies, media content, and communication:
Results from Internet evolution and digital media products/services.
Page 10: Definition of Technology
Origin of the term from Greek "techno-logía" (art, skill, craft) and "logía" (study of):
Broadly defined as application of knowledge for societal goods.
Page 12: List of Currently Availabale Emerging Technologies
Key examples:
Artificial Intelligence
Blockchain
Augmented & Virtual Reality
Cloud Computing
Digital and robotic process automation, etc.
Page 13: Introduction to the Industrial Revolution (IR)
Definition: Transition from handmade goods to machines in factories (1700s-early 1800s).
Originated in England for efficiency and productivity.
Page 14: Changes from the Industrial Revolution
Impact of technical advances on production methods and working conditions.
Different IR phases from IR 1.0 to Industry 4.0.
Page 15: Key Innovations of the Industrial Revolution
Major inventions:
Steam Engine, mass production technologies, digital advancements.
Page 16: Important Inventions of the Industrial Revolution
Categories:
Transportation: Steam Engine, Railroad, Airplane.
Communication: Telegraph, Telephone.
Industry: Cotton Gin, Electric Lights.
Page 17: Historical Background of the IR
Began in Great Britain, spread to Europe.
Linked to increased food production from the Agricultural Revolution.
Page 18: Types of Industries
Four categories:
Primary: Raw material extraction (mining, farming).
Secondary: Manufacturing (cars, steel).
Tertiary: Services (teaching, healthcare).
Quaternary: Research and development.
Page 19-21: Overview of IR 1.0
Key features:
Transition to machine-based production using steam power.
Increased production capacity and efficiency.
Page 22-23: Overview of IR 2.0
Marked by electricity and assembly line production:
Introduction of interchangeable parts.
Henry Ford's influence on automotive production.
Page 24-25: Overview of IR 3.0
The Digital Revolution:
Involvement of computers and digital logic circuits.
Automation of production with minimal human intervention.
Page 26-28: Overview of IR 4.0
Coined by Klaus Schwab in 2016:
Features cyber-physical systems, IoT, AI, and smart factories.
Page 29-30: Role of Data in Emerging Technologies
Data as a strategic asset:
Essential for business and technological decisions.
Every action generates data.
Page 31-32: Enabling Devices and Networks
Types of devices:
Memory, microprocessors, logic, and networks for data sharing.
Page 34-36: Human to Machine Interaction
Definition of HMI and HCI:
Importance in improving user-computer interactions.
Fields contributing to HCI include psychology, computer science, and engineering.
Page 37-38: Future Trends in Emerging Technologies
Key technology trends:
5G, AI, autonomous devices, blockchain, and augmented analytics.
Page 41: Introduction to Data Science
Data science as an influential interdisciplinary field.
Encompasses methods and algorithms for knowledge extraction from data.
Page 42-46: Data Science Fundamentals
Comparison of data science vs data scientist roles:
Importance of statistical methods and machine learning in data analysis.
Page 47-48: Algorithms and Data vs Information
Definition and role of algorithms in data processing.
Clarification of data and information differences.
Page 49-50: Data Processing Cycle
Steps involved in converting raw data to meaningful information:
Includes input, processing, output, and storage phases.
Page 51-52: Data Types
Definitions and examples of data types (int, bool, char, etc.).
Explanation of data representation in computing.
Page 53-56: Types of Data from Analytics Perspective
Structured, unstructured, and semi-structured data definitions.
Page 57: Metadata
Definition: Data about data, helping describe and manage data.
Page 58-60: Data Value Chain
Describes stages of data usage from acquisition to analysis and storage.
Page 62-66: Big Data Definition and Landscape
Discussion on the scale, complexity, and processing challenges of big data.
Characteristics based on the 3 Vs: volume, velocity, and variety.
Page 67-70: Clustered Computing
Explanation of clustered computing, high availability, and scalability benefits.
Introduction to Hadoop and its ecosystem for big data processing.
Page 71-74: Hadoop Data Processing Stages
Stages of data ingestion, processing, and analysis within Hadoop framework.
Page 76-83: Artificial Intelligence Overview
Definition, types, and brief history of AI.
Advantages and disadvantages of AI technologies.
Page 84-92: AI Development History
Timeline of significant AI developments and milestones.
From mechanical myths to modern advancements.
Page 93-94: Levels and Types of AI
Breakdown of AI based on capabilities and functionalities, from weak AI to superintelligence.
Page 95-107: Applications and Tools of AI
Overview of AI applications across various industries and the significance of tools used for problem-solving.