IGCSE Computer Science: Automated and Emerging Technologies — Revision Notes

Topic 6 is about computer systems that act without constant human control: automated systems built from sensors, microprocessors and actuators, robots, and artificial intelligence. In Cambridge IGCSE Computer Science (0478) it is examined on Paper 1, and almost every question is set in a scenario, so you score by applying each idea to the situation given rather than by reciting a definition.

Condensed for the final weeks. For the full explanation and longer worked examples, use the Automated and emerging technologies study guide; to practise, use the Automated and emerging technologies practice questions.

Syllabus coverage

Learning outcomes from the Cambridge IGCSE Computer Science 0478 syllabus for 2026, 2027 and 2028:

Ref	Learning outcome (summarised)
6.1.1	How sensors, microprocessors and actuators work together in automated systems
6.1.2	Advantages and disadvantages of an automated system in a given scenario (industry, transport, agriculture, weather, gaming, lighting, science)
6.2.1	What is meant by robotics
6.2.2	Characteristics of a robot
6.2.3	Roles robots can perform, with advantages and disadvantages (industry, transport, agriculture, medicine, domestic, entertainment)
6.3.1	What is meant by artificial intelligence (AI)
6.3.2	Main characteristics of AI
6.3.3	Basic operation and components of AI systems: expert systems and machine learning

Key definitions

Term	Definition to learn
Sensor	An input device that measures a physical quantity, such as temperature or light
Microprocessor	Processes the data from the sensor and decides what action is needed
Actuator	An output device that produces movement or another physical action, such as a motor, valve or pump
Automated system	A system that uses sensors, a microprocessor and actuators to perform a task without human intervention
Robotics	A branch of computer science that incorporates the design, construction and operation of robots
Artificial intelligence (AI)	A branch of computer science dealing with the simulation of intelligent behaviours by computers
Expert system	An AI system with a knowledge base, rule base, inference engine and interface that gives advice in one area
Machine learning	When a program can automatically adapt its own processes and/or data

6.1 How does an automated system work?

Learn this as a loop — the order is where marks are won.

1. The sensor continually measures a physical quantity and sends the readings to the microprocessor (via an analogue-to-digital converter if the reading is analogue).
2. The microprocessor compares each reading with a stored value or range.
3. If the reading is outside the range, the microprocessor sends a signal to the actuator.
4. The actuator carries out the action (opens a valve, switches on a motor, turns on a light).
5. The process repeats continuously, so the system keeps responding to changes.

Scenario quick-reference

Area	Example	Sensor	Actuator action
Lighting	Street lights that switch on at dusk	Light	Switches lamps on or off
Agriculture	Automatic field irrigation	Moisture	Opens a valve to the water supply
Transport	Automatic train doors at a platform	Proximity / pressure	Motor opens or closes the doors
Industry	Bottling line filling bottles	Level	Closes the filling valve
Weather	Remote weather station	Temperature, humidity, pressure	Stores and transmits readings (data logging)
Science	Laboratory experiment monitoring	pH, temperature	Adds a chemical or adjusts a heater
Gaming	Motion-controlled console	Accelerometer	Changes what is shown on screen or makes a controller vibrate

Advantages and disadvantages of automated systems

Advantages	Disadvantages
Faster response to changes than a human	Expensive to set up and maintain
Work continuously, 24 hours a day	Can fail if a sensor or actuator breaks, and may not detect its own fault
More accurate and consistent	May reduce the number of jobs
Safer: people do not need to work in dangerous places	Vulnerable to hacking if connected to a network
Can reduce waste, such as water or energy	Cannot cope with situations they were not programmed for

Always tie each point to the scenario: “the irrigation system only waters when the soil is dry, so less water is wasted” scores; “it saves resources” may not.

6.2 Robots

Characteristics of a robot (learn all three):

• a mechanical structure or framework
• electrical components, such as sensors, microprocessors and actuators
• it is programmable

Examples in the syllabus: factory equipment, domestic robots and drones.

Area	Example role	Advantage	Disadvantage
Industry	Welding car bodies	Works without breaks, consistent quality	High initial cost; fewer jobs
Transport	Driverless vehicles	Can reduce human error	Hard to program for every situation; public trust
Agriculture	Fruit-picking robots, crop-spraying drones	Works long hours, sprays exact amounts	Expensive; may damage crops if sensors fail
Medicine	Surgical robots	Very steady and precise	Expensive; surgeons need training
Domestic	Robot vacuum cleaners	Saves the owner time	Struggles with stairs and clutter
Entertainment	Animatronics in theme parks or films	Repeatable, realistic movement	Costly to build and maintain

6.3 Artificial intelligence

Main characteristics of AI (6.3.2): the collection of data and the rules for using that data; the ability to reason; and it can include the ability to learn and adapt.

Expert system components

Component	Role
Knowledge base	Stores the facts about the area of expertise
Rule base	Stores the IF–THEN rules used to apply the facts
Inference engine	Applies the rules to the facts and the user’s answers to reach a conclusion
Interface	Lets the user enter information and see the conclusion and explanation

How it runs: the interface asks questions → the user’s answers are passed to the inference engine → the inference engine searches the knowledge base using the rule base → it may ask further questions → it outputs a conclusion (often with a probability) through the interface.

Machine learning: the program automatically adapts its own processes and/or data, for example as it is given more examples, so its performance improves without it being reprogrammed.

Worked example: describing an automated system in full

An automatic barrier at a car park exit opens when a car pulls up. Describe how the system works. [4]

• A proximity (or pressure) sensor detects the car and sends data to the microprocessor. [1]
• The microprocessor compares the reading with a stored value to decide whether a car is present. [1]
• If a car is present, the microprocessor sends a signal to the actuator (motor), which raises the barrier. [1]
• The sensor keeps monitoring; when the car has passed, the microprocessor signals the motor to lower the barrier. [1]

Common mistakes / exam traps

• Calling a sensor an actuator or vice versa. A sensor is input; an actuator is output that causes movement.
• Saying “the sensor decides” — only the microprocessor makes decisions.
• Forgetting that the process is continuous.
• Writing generic advantages (“it’s better”) that do not mention the scenario.
• Saying a robot must look like a human. The syllabus characteristics are framework, electrical components and programmable.
• Mixing up the knowledge base (facts) and the rule base (rules).
• Calling any program that follows fixed rules “machine learning”. Machine learning means the program adapts itself.

Frequently asked questions

Is a robot always an automated system? A robot uses sensors, microprocessors and actuators like an automated system, but its defining features in 0478 are a mechanical framework, electrical components and being programmable. Many robots are also remotely controlled by people.

What is the difference between an expert system and machine learning? An expert system applies fixed rules in its rule base to the facts in its knowledge base. Machine learning changes its own processes or data as it gets more data, so its behaviour adapts.

Do I need to name the type of sensor? Yes, in scenario questions name a specific sensor (light, moisture, proximity) and say what it measures. The hardware topic (3.2) lists the sensors you should know.

Self-test

1. State the role of the actuator in an automated system.
2. Give the three characteristics of a robot.
3. State two disadvantages of using robots in a factory.
4. Name the four components of an expert system.
5. State what is meant by machine learning.

Answers: 1. To carry out a physical action, such as turning a motor or opening a valve, when it receives a signal from the microprocessor. 2. A mechanical structure or framework; electrical components such as sensors, microprocessors and actuators; it is programmable. 3. Any two: high cost of buying and maintaining them; fewer jobs for workers; they cannot adapt to tasks they were not programmed for. 4. Knowledge base, rule base, inference engine and interface. 5. A program that can automatically adapt its own processes and/or data.