Computer Science
04782026–2028 syllabus

COMPUTER SCIENCE · CHAPTER 5

Automated systems

Explain monitoring, control, robotics and artificial intelligence with balanced evaluation.

Full syllabus4 connected sectionsSyllabus-aligned guide

LEARNING OBJECTIVES

What you will be able to do

  • distinguish monitoring from control systems
  • describe sensor–processor–actuator feedback
  • explain robot characteristics and uses
  • describe AI systems and evaluate their impacts

AT A GLANCE

Syllabus0478Coverage2026–2028Sections4LevelFull syllabus

INTRODUCTION · THE BIG IDEA

Explain monitoring, control, robotics and artificial intelligence with balanced evaluation.

Automated systems collect data, process it and act with limited human intervention. A monitoring system reports conditions; a control system changes the environment using feedback.

Robotics and artificial intelligence can improve consistency and operate in dangerous settings, but introduce cost, employment, bias, safety and accountability questions.

01

SECTION 01

Monitoring and control systems

Core concept

A sensor measures a physical property. If its signal is analogue, an ADC converts it for a computer. The processor compares input with stored conditions; a control system sends output through a DAC or interface to an actuator and repeats the loop.

Monitoring systems record or alert without automatically changing the process. Control systems act, such as opening a greenhouse vent or changing a motor speed.

ORIGINAL STUDY DIAGRAMClosed-loop control
1Sensor measures condition
2ADC digitises if needed
3Processor compares with target
4Actuator changes process
5Sensor measures again
02

SECTION 02

Automated-system design and evaluation

Core concept

Automation can operate continuously, respond quickly, repeat accurately and protect people from danger. It can reduce labour cost and generate detailed data.

Limitations include installation and maintenance cost, sensor failure, incorrect programming, cyber risk, job displacement and poor handling of exceptional situations. Safe systems use validation, redundant sensors, alarms, manual overrides and fail-safe states.

Context evaluation
BenefitLinked risk
24-hour operationmaintenance and energy need
consistent decisionsrepeats incorrect rules consistently
less human exposureremote cyber or equipment failure
lower labour needjob loss and reskilling cost
Original worked example

Greenhouse control decision

  1. The temperature sensor reads 31 °C and the stored upper target is 28 °C.
  2. The processor compares the values and activates a motor that opens a vent.
  3. New readings continue; the motor stops or reverses when the target range is restored.

Answer: This is a control system because feedback automatically changes the greenhouse conditions.

03

SECTION 03

Robotics

Core concept

Robots use sensors, processors and actuators and may be autonomous or remotely controlled. They work in manufacturing, logistics, medicine, agriculture, exploration and hazardous environments.

They offer precision, repeatability and safe remote work but may be expensive, limited outside programmed conditions and hazardous if sensing or control fails. Human supervision remains important in safety-critical work.

ORIGINAL STUDY DIAGRAMRobot action cycle
1Perceive environment
2Process against goal
3Select action
4Drive actuator
5Use new feedback
04

SECTION 04

Artificial intelligence

Core concept

AI systems perform tasks associated with intelligent behaviour, such as recognising patterns, making predictions, understanding language or selecting actions. Machine learning builds a model from training data instead of specifying every rule directly.

Expert systems use a knowledge base, rule base, inference engine and user interface to reach conclusions and explanations. Machine-learning quality depends on representative data, chosen features and testing. Bias in data can produce unfair outcomes.

AI can process large data quickly and assist decisions, but may be opaque, wrong outside training conditions and difficult to hold accountable. Privacy, security, intellectual property and human oversight matter.

AI approaches
ApproachHow it worksMain limitation
Expert systemapplies stored rules to factsknowledge is costly to capture
Machine learninglearns patterns from examplesdata bias and limited explainability

QUICK CHAPTER SUMMARY

The ideas to carry forward

  • Monitoring reports; control changes a process.
  • Feedback allows repeated adjustment toward a target.
  • Robots sense, process and act physically.
  • AI performance depends on data, design, testing and oversight.

QUICK REVISION CHECKLIST

Can you do each of these without your notes?

  • distinguish monitoring from control systems
  • describe sensor–processor–actuator feedback
  • explain robot characteristics and uses
  • describe AI systems and evaluate their impacts