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Case Study: Traffic Light Control System

Traffic lights in many cities work on fixed timing rules (e.g., red for 60 seconds, green for 45 seconds). This ensures
smooth traffic movement at normal times. However, in emergencies or heavy traffic jams, the fixed timing cannot
adapt, which is a limitation of rule-based decision making.

Logic-Based Decision Making
This method uses conditional statements (if–then–else) to decide. The computer checks conditions and then takes the
appropriate action.
Some examples of logic-based decision making are as follows:
u A washing machine stops when water is drained (IF water = empty → THEN stop).

u ATM machines allow cash withdrawal only if the entered PIN is correct.
u Elevators decide whether to go up or down depending on button presses.
Some advantages of logic-based decision making are as follows:
u Can handle multiple conditions.
u More flexible than fixed rules.

u Easy to understand and implement.
u Reliable for structured problems.
Some disadvantages of logic-based decision making are as follows:
u Cannot deal with uncertain or incomplete data.

u Becomes complex with too many conditions.
u Requires careful programming.
u Limited adaptability.

Case Study: Washing Machine Automation
Modern washing machines use logic-based decision making. For example, IF the timer ends, THEN the machine stops
spinning. IF water is not drained, THEN the machine does not move to the next cycle. This ensures safety and correct washing.
However, if unexpected situations occur (like water pressure issues), the machine may fail to make the right decision.

Data-Based Decision Making
Machines use data to decide. They analyse large sets of information, identify patterns, and then select the most
suitable output.
Some examples of data-based decision making are as follows:

u Netflix or YouTube recommending videos.
u Weather forecasting using past weather data.
u Banks detecting fraud transactions by studying transaction data.
Some advantages of data-based decision making are as follows:
u Can provide personalised results.
u More accurate when large data is available.
u Useful in predicting future trends.
u Can handle complex decision-making.

Some disadvantages of data-based decision making are as follows:
u Needs a huge amount of data.

40 Touchpad Artificial Intelligence - XI