L5_Everything-can-be-Automated

Automation

  • Definition of Automation

    • Automation is any process that is self-driven, reduces, and eventually eliminates the need for human intervention.

    • The Internet of Things (IoT) creates opportunities for tasks that previously needed human intervention to become automated.

  • Applications of Automation

    • Use of robots in hazardous environments such as mining, firefighting, and industrial accident clean-up.

    • Application in automated assembly lines and self-service checkouts in stores.

    • Implementation of automatic building environmental controls.

    • Development of autonomous vehicles, including cars and planes.

How is Automation being Used?

  • Key Areas of Automation

    • Smart Home Automation

    • Smart Buildings

    • Industrial IoT and Smart Factories

    • Smart Cities

    • Smart Grid

    • Smart Cars

    • Stores and Services

    • Medical Diagnosis and Surgery

    • Aircraft Auto-Pilot

When Things Start to Think

  • Smart Devices

    • Many devices incorporate smart technology, altering behavior based on specific circumstances.

      • Examples: A smart appliance reducing power consumption during peak demand or a self-driving car.

    • A device is considered "smart" if it makes decisions or takes actions based on external information.

What Is Artificial Intelligence and Machine Learning?

  • Artificial Intelligence (AI)

    • AI refers to the intelligence demonstrated by machines capable of perceiving their environment and making decisions.

    • Systems imitate cognitive functions associated with the human mind, such as learning and problem-solving.

  • Machine Learning (ML)

    • A subset of AI utilizing statistical techniques to enable computers to learn from their environment.

    • Machines can improve their performance on tasks without being explicitly programmed for those tasks.

ML and the IoT

  • Common Uses of Machine Learning

    • Speech Recognition: Employed in digital assistants.

    • Product Recommendation: Systems analyze customer profiles to suggest relevant products or services.

    • Shape Recognition: Programs can convert crude hand-drawn diagrams into formal diagrams and text.

    • Credit Card Fraud Detection: Profiling based on purchasing patterns to detect anomalies.

    • Facial Recognition: Used in security and access control applications.

What is Intent-Based Networking (IBN)?

  • Concept of Intent-Based Networking

    • The IT industry is developing an approach to link infrastructure management to business intent.

    • Networks need to integrate IoT devices, cloud services, and remote offices securely and seamlessly.

    • Networks must protect digital initiatives against evolving threats and quickly adapt to policy changes.

How are ML, AI, and IBN Linked?

  • Capabilities of Intent-Based Networking

    • Integrates automation, AI, and ML to manage network functions aligned with specific goals or intents.

    • The network can translate business intent into policies and utilize automation for configuration deployments.

  • Key Elements of Intent-Based Networking

    • Assurance: End-to-end verification of network behavior.

    • Translation: Applying business intent to configure the network.

    • Activation: Execution of specified intents and policy creation.

Use Cases for Intent-Based Networking

  • Business Optimization

    • Intent-based networking allows organizations to concentrate on their objectives, supported by automated systems that fulfill those needs.

    • Example: Cisco Digital Network Architecture (Cisco DNA).

      • An open, extensible, software-driven system that simplifies and accelerates enterprise network operations while reducing costs and risks.