Untitled Quiz

Automation is an umbrella term for technologies that can perform tasks with minimal human intervention
CAM (Computer-Aided Manufacturing) integrates computer systems into manufacturing processes, from design to production
- CAD (Computer-Aided Design): Used for design and simulation
- CAE (Computer-Aided Engineering): Used for analysis and simulation
- CAPP (Computer-Aided Process Planning): Used for planning the manufacturing process
CIM (Computer-Integrated Manufacturing) aims to integrate various aspects of a factory, covering areas like:
- Cellular Manufacturing: Organizing production into specialized cells
- Flexible Manufacturing System: Adaptable systems for different product variations
- Holonic Manufacturing: Decentralized, self-organizing systems
- Just-in-Time: Producing goods only when needed
- Lean Manufacturing: Minimizing waste and optimizing processes
- Communication network: Connecting workstations and systems
- Artificial Intelligence: AI-powered systems for decision-making and process optimization

Smart home automation uses technology to automate devices like lights, thermostats, and security cameras
Motion Sensors:
- Detect movement, switching on/off lights based on presence, saving energy
- Trigger security alerts
Temperature Sensors:
- Monitor room temperature, adjusting heating/cooling for optimal comfort
- Reduce energy consumption by only activating HVAC systems when necessary
Humidity Sensors:
- Track humidity levels, preventing mold growth
- Activate dehumidifiers or exhaust fans for better air quality
Light Sensors:
- Detect ambient light levels, adjusting artificial lighting to save energy
- Optimize lighting conditions based on daylight

Sensors play a crucial role in automotive automation, improving safety, efficiency, and convenience
Reverse (Parking) Sensor:
- Detects obstacles behind the vehicle, alerting drivers with sounds or signals for safe backing up
Light Sensor:
- Detects light levels, automatically turning headlights on/off as needed for safety
Engine Temperature Sensor:
- Monitors engine temperature, controlling fuel use and cooling
- Alerts the driver if the engine overheats to prevent damage
Fuel Sensor:
- Measures fuel level in the tank, displaying it on the dashboard for timely refueling
Airbag Sensor:
- Detects sudden deceleration or impact, deploying airbags to protect passengers

AI: A broad field focusing on creating machines or software capable of tasks typically requiring human intelligence
- Includes technologies like machine learning, neural networks, and natural language processing
- AI systems learn from data, adapt to new information, and are more flexible in dynamic environments
- Example: Autonomous vehicles
Expert System: A type of AI mimicking human expert decision-making in specific domains
- Uses a predefined set of rules and facts (knowledge base) to solve problems
- Rely on rules created by experts and lack learning capabilities
- Example: Medical diagnosis systems

Autonomous Vehicles (AVs) are vehicles that can operate without direct human intervention
Use sensors, AI, and machine learning to sense their surroundings, interpret data, and make driving decisions
Key Components of AVs:
- Sensors (Cameras, LiDAR, Radar, Ultrasonic): Detect objects, road signs, lane markings, etc.
- Perception Algorithms: Analyze sensor data to recognize objects and situations
- Mapping and Localization: Determine the vehicle's position using HD maps and GPS/SLAM
- Path Planning and Decision Making: AI models plan routes, determine speed, and make driving decisions
- Control Systems: Execute planned actions (steering, braking, accelerating)

Expert systems assist healthcare professionals in diagnosis, treatment, and patient care
Knowledge Base: Stores medical knowledge, including symptoms, treatments, drug interactions, and patient data
Inference Engine: Applies rules to the knowledge base to make decisions, suggesting diagnoses and treatments
User Interface: Allows interaction with the system, entering data, reviewing suggestions, and obtaining recommendations

Expert systems aid mechanics in vehicle diagnosis, recommending repairs, and optimizing maintenance
Knowledge Base: Stores information on vehicle systems, fault codes, symptoms, and repair guides
Inference Engine: Analyzes symptoms or error codes, suggesting likely causes and tests
User Interface: Allows mechanics to enter data, view diagnostic suggestions, and follow repair instructions

Expert systems predict and prevent equipment failures to reduce downtime and extend lifespan
Knowledge Base: Stores maintenance knowledge, historical data, and manufacturer recommendations
- Includes rules about part failure and solutions for common issues
Inference Engine: Analyzes data to identify potential failures and recommend appropriate actions
User Interface: Allows interaction with the system, reviewing recommendations and taking preventative measures