1. Which of the following is a subsystem of Artificial Intelligence that enables computers to learn from data using statistical techniques without being explicitly programmed?
(a) Natural Language Processing
(b) Machine Learning
(c) Robotics
(d) Blockchain
2. The five V’s that characterise Big Data are Volume, Velocity, Variety, Veracity and __.
(a) Validity
(b) Value
(c) Variability
(d) Visualisation
3. Assertion (A): Virtual Reality creates a completely computer-generated three-dimensional situation that simulates the real world.
Reason (R): Augmented Reality superimposes computer-generated perceptual information over the existing physical surroundings.
(a) Both A and R are true and R is the correct explanation of A.
(b) Both A and R are true but R is not the correct explanation of A.
(c) A is true but R is false.
(d) A is false but R is true.
4. In cloud computing, the model that provides a platform or environment to develop, test and deliver software applications without worrying about the underlying infrastructure is called:
(a) IaaS
(b) PaaS
(c) SaaS
(d) Grid Computing
5. Which emerging technology works on the concept of a decentralised and shared database where each participating computer maintains a copy of the ledger?
(a) Internet of Things
(b) Cloud Computing
(c) Blockchain
(d) Grid Computing
6. Assertion (A): Sensors are prime components of robots that help them interact with the physical environment.
Reason (R): A smart sensor takes input from the physical environment and uses built-in computing resources to perform predefined functions.
(a) Both A and R are true and R is the correct explanation of A.
(b) Both A and R are true but R is not the correct explanation of A.
(c) A is true but R is false.
(d) A is false but R is true.
7. The network of devices that have embedded hardware and software to connect and exchange data with other devices on the same network is known as:
(a) Web of Things
(b) Internet of Things
(c) Grid Computing
(d) Big Data
8. Which of the following is NOT a characteristic of Big Data?
(a) Volume
(b) Velocity
(c) Variety
(d) Centralisation
9. NLP is primarily used for:
(a) Creating virtual reality environments
(b) Interaction between humans and computers using human spoken languages
(c) Managing distributed CPU resources
(d) Storing data on remote servers
10. A drone is an example of:
(a) Virtual Reality application
(b) Unmanned aircraft that can be remotely controlled or fly autonomously
(c) Cloud service model
(d) Data analytics tool
1. Define Artificial Intelligence. How does it make machines behave intelligently?
2. Differentiate between Virtual Reality and Augmented Reality.
3. What is a sensor? Give one example of its use in mobile phones.
4. List any two characteristics of Big Data and explain any one.
5. What is the difference between Internet of Things (IoT) and Web of Things (WoT)?
6. Define Grid Computing. How is it different from cloud computing in terms of focus?
1. Explain any three applications of Robotics mentioned in the chapter.
2. What is Data Analytics? How can Pandas library be useful for it?
3. The following code fragment is intended to represent a simple check for Veracity in Big Data processing. Identify the error and correct it.
python
data = [100, "error", 200]
if data[1] == "error":
print("Data is trustworthy")
else:
print("Data has veracity issue")
Explain the correction with reference to the chapter.
4. Explain the role of sensors in creating smart cities with one example each for smart building and smart bridge.
5. The code below attempts to simulate a basic Blockchain transaction verification step. Identify the error and rewrite the correct version.
python
blocks = ["block1", "block2"]
new_block = "block3"
if new_block in blocks:
print("Transaction verified")
else:
blocks.append(new_block)
print("Block added to chain")
Why is this correction important according to the chapter?
1. Explain the three standard cloud service models (IaaS, PaaS and SaaS) with one example of each. How does “pay per use” benefit users? (5 marks)
2. Write a complete Python program that takes a list representing daily data generation (simulating Big Data volume) and prints the total volume and whether it exceeds a threshold of 1000 units. Use proper indentation and comments. (5 marks)
3. Explain the working of Blockchain technology with the help of a dry-run using a trace table for the following sequence of transactions:
- Transaction 1 requested
- Verified by all nodes
- Added to chain
Show the state of the ledger after each step. (5 marks)
Case 1: A municipal corporation wants to convert a city into a smart city using IoT, sensors and cloud computing.
(a) How can sensors help in managing traffic congestion?
(b) Explain the role of IoT in waste management.
(c) Which cloud service model would be most suitable for hosting the city’s central monitoring application and why?
(d) How can data collected through IoT devices exhibit the ‘Velocity’ characteristic of Big Data?
Case 2: A school education department plans to implement blockchain for maintaining student scholarship records.
(a) Why is decentralisation useful in this scenario?
(b) How does the ‘append only’ ledger ensure transparency?
(c) Give one advantage of using blockchain over a centralised database for scholarship distribution.
(d) Name one other sector (besides education) where the same technology can be applied as per the chapter.
data = [250, 300, 450, 150]
total = sum(data)
print("Total volume:", total)
if total > 1000:
print("Exceeds threshold")
else:
print("Within threshold")
```
3. Trace table:
Step 1: Ledger = [] → Transaction requested
Step 2: Ledger = [] → Verified by nodes
Step 3: Ledger = [Tx1] → Block added
Case 1: (a) Sensors monitor vehicle flow (b) IoT bins signal fill levels (c) PaaS for hosting applications (d) High rate of continuous sensor data generation.
Case 2: (a) No single point of failure or tampering (b) All nodes maintain identical copy (c) Prevents alteration of records (d) Land registration / healthcare / voting.
All questions are answerable from the NCERT chapter text. Reviewed by GFIS faculty.