Emerging Trends

Introduction to Emerging Trends

Artificial Intelligence (AI)

• Definition: The ability of machines or computer systems to learn and adapt based on human-like intelligence processes and experiences.

• Capabilities: Can perform tasks autonomously, e.g., trains without drivers, auto-pilot aircraft.

Machine Learning

• Definition: An application of AI that enables systems to learn and improve from experience without being explicitly programmed.

• Characteristics:

  • Development of self-learning computer programs that access data.

  • Algorithms create mathematical models based on training data to predict or make decisions.

Examples of Machine Learning

1. Facial recognition technology for photo tagging in social media.

2. Optical Character Recognition (OCR) technology that converts images of text into editable formats.

Natural Language Processing (NLP)

• Definition: A branch of AI focused on interactions between computers and humans using natural language.

• Objective: To read and understand human languages, enabling natural interaction with computers.

• Techniques: Most NLP methods rely on machine learning to interpret human language.

Uses of NLP

1. Language translation applications (e.g., Google Translate).

2. Word processors (e.g., Microsoft Word) that check grammatical accuracy.

3. Interactive Voice Response (IVR) systems in call centers.

4. Personal assistant applications (e.g., Siri, Alexa).

Immersive Experiences (AR / VR)

• Definition: The perception of being in a different space than reality, often in entertainment contexts.

• Demand: People seek the most immersive experiences in entertainment.

Augmented Reality (AR)

• Definition: Enhances live views with digital elements, often through smartphone cameras.

• Examples: Snapchat lenses, Pokemon Go.

• Application: Helps users envision furniture in their homes before purchasing.

Virtual Reality (VR)

• Definition: Fully immersive experience that disconnects from the physical world.

• Applications: Used by property agents and automobile dealers for virtual walkthroughs.

Robotics

• Definition: An interdisciplinary research area combining computer science and engineering.

• Focus: Design, construction, operation, and use of robots to assist humans.

• Objective: Develop machines for various day-to-day tasks, enhancing safety.

• Example: India's first robot "Mitra."

Characteristics of Robotics

• Ability to replicate human actions and operate in dangerous environments (e.g., bomb deactivation).

• Flexible design; robots can take many forms, some resembling humans.

Big Data

• Definition: Extremely large volumes of data that traditional systems cannot handle.

• Usage: Employed by companies for data analysis to enhance businesses.

• Characteristics: Defined by three Vs - High Volume, High Variety, High Velocity.

Characteristics of Big Data

• Volume: Refers to the massive amount of data generated.

• Velocity: Pertains to the speed data is processed.

• Variety: Different types/formats of data.

Internet of Things (IoT)

• Definition: A system of interconnected devices and objects enabled to transfer data without human intervention.

• Example: Smart home systems that allow remote monitoring and control of devices.

Sensors

• Definition: Devices that detect and respond to physical parameters and convert them into measurable signals.

• Types of Sensors:

  1. Temperature Sensor.

  2. Proximity Sensor.

  3. Accelerometer.

  4. Infrared Sensor.

  5. Pressure Sensor.

  6. Light Sensor.

  7. Ultrasonic Sensor.

  8. Chemical (Smoke, Gas, and Alcohol) Sensors.

Smart Cities

• Definition: Urban areas leveraging IoT sensors to collect and analyze data for efficient management of resources and services.

• Functions: Monitors and manages traffic, utilities, waste, and other community services.

Smart City Components

• Integration of ICT and IoT devices to optimize operations.

• Enhancements to urban services and interactions between citizens and government.

Cloud Computing and Cloud Services

• Definition: Access to remote information and applications stored in the cloud.

• Benefits: Enables remote work and access to data without location constraints.

• Functionality: Various services, including data storage and application hosting.

Types of Cloud Computing

• Comprised of three main services:

  1. Software-as-a-Service (SaaS)

  2. Infrastructure-as-a-Service (IaaS)

  3. Platform-as-a-Service (PaaS)

Software-as-a-Service (SaaS)

• Definition: Software applications licensed to customers via pay-as-you-go models (e.g., Microsoft Office 365).

Infrastructure-as-a-Service (IaaS)

• Definition: Delivers servers, storage, and other resources as an on-demand service over the Internet.

• Example Providers: IBM Cloud, Microsoft Azure.

Platform-as-a-Service (PaaS)

• Definition: A platform for creating software and applications delivered online.

• Examples: Force.com, Heroku.

Grid Computing

• Definition: Networked computers working together to solve complex problems or analyze data.

• Function: Acts as a "supervirtual computer" for collaborative tasks.

Blockchain Technology

• Definition: A decentralized, immutable record of data managed by a network of computers.

• Key Feature: Data is secured and linked using cryptographic principles.

Potential Uses for Blockchain Technology

1. Payment processing and money transfers.

2. Supply chain monitoring for efficiency and real-time tracking.

3. Enhanced copyright protection for digital content.

4. Improvements in retail loyalty rewards programs.