Unit 5: Emerging Technologies
AUGMENTED REALITY (AR)
Augmented Reality is a technology that adds digital elements (images, text, animations) onto the real-world environment through devices like smartphones, tablets, or AR glasses.
AR overlays computer-generated information on the real world in real time.
Example: Pokémon Go, Snapchat filters.
Features
- Real-time interaction
- Combines physical and digital worlds
- Uses GPS, camera, sensor data
- High user engagement
- Interactive 3D visualization
Limitations
- Requires high-performance devices
- Can cause eye strain
- Privacy issues (camera access)
- Limited field of view
- Development cost is high
Application Areas
- Gaming (Pokémon Go)
- Retail (virtual try-on)
- Education (interactive learning models)
- Healthcare (surgery assistance)
- Navigation (Google AR Navigation)
- Interior design (IKEA AR app)
VIRTUAL REALITY (VR)
Virtual Reality creates a fully immersive, computer-generated environment, isolating the user from the real world using VR headsets.
Overview
VR simulates a 3D artificial world where users can look and move around as if physically present.
Features
- Fully immersive experience
- 360° simulation
- Uses VR headsets, gloves, sensors
- Real-time motion tracking
- Highly interactive
Limitations
- Expensive hardware
- Motion sickness for some users
- Requires powerful systems
- Limited physical movement area
Application Areas
- Gaming and entertainment
- Virtual tours (real estate, tourism)
- Medical training (virtual surgery)
- Military simulations
- Online education (virtual classrooms)
- Architecture & design visualization
GRID COMPUTING
Grid computing connects multiple distributed computers to solve a single large problem collaboratively.
Overview
It uses the combined processing power of geographically distributed systems to perform compute-intensive tasks.
Features
- Resource sharing across networks
- High performance
- Scalability
- Supports large problem-solving
- Distributed architecture
Limitations
- Complex setup
- Security issues across shared networks
- Requires high-speed connectivity
- Risk of node failure
Application Areas
- Weather forecasting
- Scientific research
- Data mining
- Astronomy simulations
- Drug discovery
- Financial modeling
GREEN COMPUTING
Green computing is the practice of designing, using, and disposing of computers and related systems efficiently to reduce environmental impact.
Overview
It aims to minimize energy consumption, reduce e-waste, and promote eco-friendly technologies.
Features
- Energy-efficient hardware
- E-waste management
- Virtualization
- Cloud computing for efficiency
- Renewable energy usage
Limitations
- High initial cost
- Lack of awareness
- Requires specialized hardware
- Recycling processes are expensive
Application Areas
- Data centers optimization
- Low-power devices (LED monitors)
- Virtual meetings (reduces travel)
- Solar-powered computing
- Recycling programs
BIG DATA ANALYTICS
Big Data Analytics refers to analyzing large, diverse, and complex datasets to discover patterns, trends, and insights.
Overview
Uses technologies like Hadoop, Spark, NoSQL to process huge volumes of structured and unstructured data.
Features
- Deals with 5 V’s: Volume, Velocity, Variety, Veracity, Value
- Real-time analytics
- Predictive insights
- Machine learning integration
- Scalability
Limitations
- Requires skilled professionals
- High storage & processing cost
- Data privacy issues
- Complex tools & platforms
Application Areas
- E-commerce (recommendation engines)
- Banking (fraud detection)
- Healthcare (patient records, diagnostics)
- Marketing analytics
- Social media analysis
- Smart cities data
QUANTUM COMPUTING
Quantum computing uses quantum bits (qubits) that can exist in multiple states simultaneously, enabling extremely fast computation.
Overview
It leverages principles like superposition and entanglement to solve complex problems faster than classical computers.
Features
- Extremely high processing power
- Parallel computation
- Solves complex mathematical problems
- Uses quantum algorithms
Limitations
- Very expensive
- Requires near-zero temperature
- Technology still in early stages
- Difficult to maintain qubit stability (decoherence)
Application Areas
- Cryptography
- Drug discovery
- Financial modeling
- Weather prediction
- Optimization problems
- Machine Learning acceleration
BRAIN–COMPUTER INTERFACE (BCI)
A Brain–Computer Interface enables direct communication between the human brain and a computer system without physical movement.
Overview
BCI reads brain signals using EEG, sensors, or implants and converts them into commands for external devices.
Features
- Direct brain-to-machine communication
- Real-time signal processing
- Uses AI and neural decoding
- Can control external devices
Limitations
- Ethical issues
- Risk of privacy invasion
- Expensive and complex
- Medical risks with implants
- Limited accuracy
Application Areas
- Assistive devices for disabled people
- Controlling robotic arms
- Neuro-gaming
- Medical rehabilitation
- Brain monitoring
- Military communication systems
SUMMARY TABLE (Quick Revision)
| Technology | Features | Limitations | Applications |
|---|---|---|---|
| AR | Digital overlays | Device & privacy issues | Gaming, education, retail |
| VR | Immersive virtual world | Motion sickness, cost | Gaming, training, tourism |
| Grid Computing | Shared resources | Security, complexity | Research, forecasting |
| Green Computing | Energy-efficient | High cost | Data centers, recycling |
| Big Data Analytics | Real-time insights | Privacy, cost | Banking, marketing |
| Quantum Computing | Ultra-fast | Expensive, unstable | Cryptography, ML |
| BCI | Brain-controlled devices | Ethical risks | Healthcare, robotics |