Automated & Emerging Technologies
Automated systems, robotics, artificial intelligence, expert systems and machine learning.
1 Automated Systems
An automated system uses sensors, microprocessors, and actuators working together to monitor and control a process without continuous human intervention.
The Three Components
2 Automation Scenarios
Sensors used: Moisture, temperature, light
Process: Moisture sensor detects dry soil → microprocessor activates water valve actuator → crops are watered. Temperature sensor prevents watering in frost conditions.
- Saves water — only irrigates when needed
- Works 24/7 without human presence
- More precise than manual watering
- Reduces labour costs
- High initial setup cost
- System failure can harm crops
- Requires technical maintenance
- Sensor malfunction gives wrong readings
Sensors used: Infrared (vehicle detection), pressure (road weight)
Process: Infrared sensors count vehicles waiting at each light → microprocessor analyses traffic flow → traffic light actuators are adjusted to reduce queuing and prioritise busy lanes.
- Reduces congestion dynamically
- Responds to real traffic — not fixed timers
- Can prioritise emergency vehicles
- Reduces journey times and emissions
- Expensive to install and maintain
- System failure causes major disruption
- Hackers could manipulate traffic signals
Sensors used: Pressure, proximity, temperature, flow
Process: Sensors monitor production line → microprocessor controls robotic arms, conveyor speeds, and quality checks → actuators adjust machinery.
- Consistent quality — no human error
- Operates continuously without breaks
- Faster production rates
- Safer for dangerous environments
- Job losses — human workers displaced
- High upfront investment
- Cannot adapt to unexpected situations
3 Robotics
Robotics is a branch of computer science involving the design, construction, and operation of robots. A robot is a programmable machine with a physical structure that can carry out tasks automatically.
Characteristics of a Robot
- A mechanical structure or framework — physical body to perform tasks
- Electrical components — sensors (inputs), microprocessor (processing), actuators (outputs)
- Programmable — behaviour defined by software that can be changed
Where Robots Are Used
| Area | Example | Benefit |
|---|---|---|
| Industry | Robotic welding arms on car production lines | Precision, speed, consistent quality |
| Medicine | Surgical robots (e.g. Da Vinci) | More precise than human hands, minimally invasive |
| Agriculture | Harvesting robots, drone crop sprayers | 24/7 operation, reduce chemical use |
| Domestic | Robotic vacuum cleaners (Roomba) | Convenient, saves time |
| Transport | Autonomous vehicles, warehouse robots | Safer, more efficient logistics |
4 Artificial Intelligence
Artificial Intelligence (AI) is a branch of computer science dealing with the simulation of intelligent behaviour by computers — making machines perform tasks that would normally require human intelligence.
Characteristics of AI
- Data collection — AI systems collect large amounts of relevant data
- Rules for using data — defined rules or learned patterns determine how to process the data
- Ability to reason — can draw conclusions and make decisions from available information
- Ability to learn and adapt — can improve performance over time based on new data (machine learning)
5 Expert Systems
An expert system is an AI program that mimics the decision-making ability of a human expert in a specific domain, using a knowledge base and rules.
| Component | Description | Example |
|---|---|---|
| Knowledge base | A large database of facts and information about the domain | Medical symptoms, treatments, diagnoses |
| Rule base | A set of IF-THEN rules that define how to use the knowledge | IF fever AND rash THEN consider measles |
| Inference engine | Applies the rules to the knowledge base to reach conclusions | Processes symptoms entered by the user to suggest diagnoses |
| User interface | The interaction layer — collects inputs and displays conclusions | Questions asked to the doctor / patient |
In the exam, always name ALL FOUR components of an expert system: knowledge base, rule base, inference engine, user interface. Missing one loses marks.
6 Machine Learning
Machine learning is a type of AI where a program automatically adapts its own processes and/or data based on experience — it learns from data without being explicitly programmed for every situation.
- Programmer writes explicit rules
- Computer follows those rules exactly
- Cannot handle situations not covered by rules
- Expert system is an example
- System is trained on large datasets
- Finds patterns without explicit rules
- Improves accuracy with more data
- Examples: spam filters, image recognition, recommendation engines