– Evolution of Internet of Things (IoT)
Objectives
• Understand the evolution of IoT
• Identify precursor technologies
• Explain transition to intelligent IoT systems
Early Internet Paradigm
• Internet originally connected computers and
people
• Human-centric communication model
• No direct interaction with physical world
Need for IoT Evolution
• Lack of real-time physical data
• Manual monitoring inefficiencies
• Demand for automation and intelligence
Embedded Systems Era
• Standalone task-specific systems
• Limited computation and memory
• No Internet connectivity
Machine-to-Machine (M2M) Communication
• Automated communication between
machines
• Minimal human intervention
• Proprietary architectures
Limitations of M2M
• Vendor lock-in
• Poor scalability
• Lack of interoperability
Wireless Sensor Networks (WSN)
• Large-scale sensor deployment
• Distributed sensing and aggregation
• Energy-constrained nodes
WSN Contributions and Limitations
• Low-power sensing foundation
• Environmental monitoring support
• Limited Internet integration
Cyber-Physical Systems (CPS)
• Integration of computation and physical
processes
• Real-time feedback and control
• Foundation for automation
Role of CPS in IoT
• Bridges cyber and physical worlds
• Supports smart environments
• Enhances system autonomy
RFID Technology
• Automatic object identification
• Non-line-of-sight communication
• Mass tagging capability
RFID Contribution to IoT
• Unique object identity
• Tracking and tracing
• Enabled object-centric Internet
Emergence of IoT Paradigm
• Integration of Internet, M2M, WSN, CPS, RFID
• Global connectivity
• Interoperable architecture
IoT Definition Perspective
• Anytime, anywhere connectivity
• Anything communication
• Seamless interaction among things
Enabling Technologies – Overview
• Sensors and actuators
• Embedded systems
• Communication technologies
• Cloud and IPv6
Sensors and Actuators
• Sense physical parameters
• Generate real-world data
• Enable control actions
Embedded Devices and Edge Computing
• Microcontrollers and SoCs
• Low power operation
• Local intelligence
Communication Technologies
• Wired and wireless networks
• Short and long range protocols
• Reliable data exchange
Role of IPv6
• Huge address space
• Unique device identification
• IoT scalability enabler
Cloud Computing in IoT
• Centralized data storage
• High-performance analytics
• IoT service platforms
IoT Evolution Phases
• Identification
• Connectivity
• Interaction
• Intelligence
Phase 1 – Identification
• RFID-based tagging
• Object identity
• Basic tracking
Phase 2 – Connectivity
• Internet-enabled devices
• Remote access
• Wireless networking
Phase 3 – Interaction
• Device-to-device communication
• Human–thing interaction
• Data exchange
Phase 4 – Intelligence
• Big data analytics
• Artificial intelligence
• Autonomous decisions
IoT Architecture View
• Device layer
• Network layer
• Application layer
Characteristics of Evolved IoT
• Scalability
• Interoperability
• Context-awareness
• Self-configuration
Challenges in IoT Evolution
• Security
• Privacy
• Energy efficiency
• Standardization
Security and Privacy Challenges
• Authentication and authorization
• Data confidentiality
• User privacy protection
Energy and Standardization Issues
• Battery constraints
• Energy harvesting
• Heterogeneous standards
Outcomes of IoT Evolution
• Smart cities
• Healthcare
• Industrial IoT
• Agriculture
IoT as Future Internet
• Internet of Everything
• AI-integrated systems
• Industry 4.0 foundation
Summary
• IoT evolved through multiple technologies
• From isolated systems to intelligent networks
• Enables real-world smart applications

ENABLING IoT FROM INTRODUCTION TO IOT BY MISRA

  • 1.
    – Evolution ofInternet of Things (IoT)
  • 2.
    Objectives • Understand theevolution of IoT • Identify precursor technologies • Explain transition to intelligent IoT systems
  • 3.
    Early Internet Paradigm •Internet originally connected computers and people • Human-centric communication model • No direct interaction with physical world
  • 4.
    Need for IoTEvolution • Lack of real-time physical data • Manual monitoring inefficiencies • Demand for automation and intelligence
  • 5.
    Embedded Systems Era •Standalone task-specific systems • Limited computation and memory • No Internet connectivity
  • 6.
    Machine-to-Machine (M2M) Communication •Automated communication between machines • Minimal human intervention • Proprietary architectures
  • 7.
    Limitations of M2M •Vendor lock-in • Poor scalability • Lack of interoperability
  • 8.
    Wireless Sensor Networks(WSN) • Large-scale sensor deployment • Distributed sensing and aggregation • Energy-constrained nodes
  • 9.
    WSN Contributions andLimitations • Low-power sensing foundation • Environmental monitoring support • Limited Internet integration
  • 10.
    Cyber-Physical Systems (CPS) •Integration of computation and physical processes • Real-time feedback and control • Foundation for automation
  • 11.
    Role of CPSin IoT • Bridges cyber and physical worlds • Supports smart environments • Enhances system autonomy
  • 12.
    RFID Technology • Automaticobject identification • Non-line-of-sight communication • Mass tagging capability
  • 13.
    RFID Contribution toIoT • Unique object identity • Tracking and tracing • Enabled object-centric Internet
  • 14.
    Emergence of IoTParadigm • Integration of Internet, M2M, WSN, CPS, RFID • Global connectivity • Interoperable architecture
  • 15.
    IoT Definition Perspective •Anytime, anywhere connectivity • Anything communication • Seamless interaction among things
  • 16.
    Enabling Technologies –Overview • Sensors and actuators • Embedded systems • Communication technologies • Cloud and IPv6
  • 17.
    Sensors and Actuators •Sense physical parameters • Generate real-world data • Enable control actions
  • 18.
    Embedded Devices andEdge Computing • Microcontrollers and SoCs • Low power operation • Local intelligence
  • 19.
    Communication Technologies • Wiredand wireless networks • Short and long range protocols • Reliable data exchange
  • 20.
    Role of IPv6 •Huge address space • Unique device identification • IoT scalability enabler
  • 21.
    Cloud Computing inIoT • Centralized data storage • High-performance analytics • IoT service platforms
  • 22.
    IoT Evolution Phases •Identification • Connectivity • Interaction • Intelligence
  • 23.
    Phase 1 –Identification • RFID-based tagging • Object identity • Basic tracking
  • 24.
    Phase 2 –Connectivity • Internet-enabled devices • Remote access • Wireless networking
  • 25.
    Phase 3 –Interaction • Device-to-device communication • Human–thing interaction • Data exchange
  • 26.
    Phase 4 –Intelligence • Big data analytics • Artificial intelligence • Autonomous decisions
  • 27.
    IoT Architecture View •Device layer • Network layer • Application layer
  • 28.
    Characteristics of EvolvedIoT • Scalability • Interoperability • Context-awareness • Self-configuration
  • 29.
    Challenges in IoTEvolution • Security • Privacy • Energy efficiency • Standardization
  • 30.
    Security and PrivacyChallenges • Authentication and authorization • Data confidentiality • User privacy protection
  • 31.
    Energy and StandardizationIssues • Battery constraints • Energy harvesting • Heterogeneous standards
  • 32.
    Outcomes of IoTEvolution • Smart cities • Healthcare • Industrial IoT • Agriculture
  • 33.
    IoT as FutureInternet • Internet of Everything • AI-integrated systems • Industry 4.0 foundation
  • 34.
    Summary • IoT evolvedthrough multiple technologies • From isolated systems to intelligent networks • Enables real-world smart applications