Emerging Technologies

Automated Systems

Robotics

Robotics is a branch of computer science that incorporates the:

  • design
  • construction
  • operation

... of robots.

Applications of robotics include:

  • factory equipment
  • domestic robots
  • drones

Robot

A robot:

  • has a mechanical structure or framework
  • has electrical components
  • is programmable

Uses

Robots can be used in many areas including:

  • industry
  • transport
  • agriculture
  • medicine
  • domestic
  • entertainment

There are many advantages and disadvantages to using robots in a commercial environment. This is where economic concepts intersect with computer science.

  • Robots can perform dangerous tasks and keep workers safe
  • Robots can take over repetitive tasks
  • Efficiency of production may increase
  • Could be expensive to setup robots initially
  • Deskilling of workforce may occur

Artificial Intelligence

AI is a branch of computer science dealing with the simulation of intelligent behaviours by computers.

The characteristics of AI include the:

  • collection of data
  • storage of rules for using data
  • ability to reason
  • ability to adapt

Expert System

An expert system tries to make decisions and works alongside humans. Expert systems have:

  • Knowledge Base: a repository of facts
  • Rule Base: the logic that the expert system must follow
  • Inference Engine: the brain of the expert system that makes decisions by applying rules to knowledge to provide a result
  • Interface: the method by which a user can interact with the expert system
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The knowledge base is essential because the expert system generates rules based on it.

The effectiveness of an expert system relies on the accuracy of facts in the knowledge base provided by human experts.

Machine Learning

Machine learning is when a program has the ability to automatically adapt its own processes or data.

  • Expert systems could use it to improve their results
  • Robots may use it to learn from mistakes

No matter the application, machine learning requires big data. For this, programs need to collect extensive amounts of data and analyse patterns within the data.