Automated and emerging technologies
How automated systems use sensors, microprocessors and actuators, what makes a robot, and how artificial intelligence, expert systems and machine learning work.
📌 Key points
- An automated system uses sensors, a microprocessor and actuators to carry out a task without human input, e.g. in industry, transport, agriculture, weather stations, gaming, lighting and science.
- In an automated system, sensors take readings, analogue data is converted to digital, the microprocessor compares the readings with stored (preset) values, and it sends signals to actuators to make a change; this repeats continuously.
- Advantages of automated systems: faster, more consistent and accurate, can work 24/7 and in dangerous places, and lower running costs; disadvantages: expensive to set up and maintain, can be hacked or fail, may cause job losses and cannot cope with situations they were not programmed for.
- Robotics is the branch of computer science dealing with the design, construction and operation of robots. A robot has a mechanical structure (framework), electrical components (sensors, microprocessors, actuators) and is programmable.
- An end effector is the tool attached to a robot arm to do the job, e.g. a gripper, drill, welding gun or spray gun.
- Robots are used in factories, transport (driverless vehicles), agriculture, medicine, homes (e.g. robot vacuum cleaners) and entertainment; they work in dangerous places and are precise, but are expensive and can only do what they are programmed to do.
- Artificial intelligence (AI) is the branch of computer science that simulates intelligent behaviour by computers; its characteristics are the collection of data, rules for using that data, the ability to reason, and possibly the ability to learn and adapt.
- An expert system has a knowledge base (facts from experts), a rule base (IF…THEN rules), an inference engine (applies the rules to the facts and the user's answers to reach a conclusion) and a user interface; it can explain how it reached its conclusion.
- Machine learning lets a program automatically adapt its own processes and/or data when it is given new data or experiences, without being explicitly reprogrammed.
📖 Key terms
- Automated system
- A combination of software and hardware that works by itself, without human input.
- Microprocessor
- An integrated circuit that processes the sensor data and decides what output is needed.
- End effector
- The device at the end of a robot arm that carries out the task, e.g. a gripper or drill.
- Artificial intelligence
- The simulation of intelligent behaviour, such as reasoning and learning, by a computer.
- Knowledge base
- The part of an expert system that stores facts gathered from human experts.
- Inference engine
- Applies the rules in the rule base to the knowledge base and user's answers to reach a conclusion.
- Machine learning
- When a program changes its own processes or data based on new data, without being reprogrammed.
✏️ Worked example
A greenhouse must be kept between 20 °C and 25 °C. Describe how an automated system does this.
- A temperature sensor takes a reading; the analogue reading is converted to digital.
- The microprocessor compares the reading with the stored values 20 °C and 25 °C.
- If the temperature is below 20 °C, it sends a signal to an actuator to switch the heater on (and close the windows).
- If the temperature is above 25 °C, it sends a signal to switch the heater off and an actuator opens the windows.
- If it is in range, no action is taken. The process repeats continuously.
In "describe how the system works" answers, name each part (sensor, microprocessor, actuator) and say what it does with the data. Saying "the computer controls it" earns no marks.
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