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AKTU · B.Tech · 6th semester

AKTU Data Science in IoT (BCIT601) Question Paper 2025-26

UniversityDr. A.P.J. Abdul Kalam Technical University (AKTU), Lucknow
CourseB.Tech, Semester VI
SubjectData Science in IoT (BCIT601)
ExamTheory Examination 2025-26 (even semester)
Time · Marks3 hours · 70 marks
SourceAKTU question paper, from the ABESIT question paper bank
View original PDF Other years

Note: Attempt all Sections. In case of any missing data; choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 7 = 14 marks

  1. Explain the major challenges faced in IoT Analytics.
  2. What is Data Pre-engineering in IoT Analytics?
  3. How do visualization techniques help in identifying model accuracy?
  4. What are Linked Analytical Datasets?
  5. Explain the concept of Predictive Maintenance.
  6. What are IoT-based applications?
  7. What is Real-Time Analytics in IoT?

Section B

Q2. Attempt any three of the following · 7 × 3 = 21 marks

  1. What is IoT Analytics, and why is it important in modern data-driven businesses?
  2. How does Exploratory Data Analytics (EDA) help in identifying patterns, trends, and anomalies in datasets?
  3. Differentiate between Simple Regression and Multiple Regression with suitable examples.
  4. Explain different strategies used for linking data sources in analytics systems.
  5. Explain the role of IoT Analytics in Healthcare with examples such as remote patient monitoring and smart medical devices.

Section C

Q3

Attempt any one part of the following · 7 × 1 = 7 marks

  1. How does cloud computing support IoT Analytics, and what are the advantages of using cloud-based IoT platforms?
  2. What are the key issues related to data management and scalability in IoT Analytics systems?

Q4

Attempt any one part of the following · 7 × 1 = 7 marks

  1. What are the different types of data used in Data Analytics, and how are they classified in IoT systems?
  2. Compare skewness and kurtosis with suitable examples, and explain how they help in understanding data distribution.

Q5

Attempt any one part of the following · 7 × 1 = 7 marks

  1. Explain Polynomial Regression and discuss the importance of Pipelines in machine learning workflows.
  2. Describe the use of Box Plots, Pivot Tables, and Heat Maps in data visualization and exploratory analysis.

Q6

Attempt any one part of the following · 7 × 1 = 7 marks

  1. How can IoT Analytics create new revenue opportunities for organizations and industries?
  2. How does the predictive maintenance cycle help reduce operational costs and improve equipment efficiency?

Q7

Attempt any one part of the following · 7 × 1 = 7 marks

  1. Discuss the application of IoT Analytics in Smart Surveillance systems for security and public safety.
  2. Compare the use of IoT Analytics across different domains such as healthcare, agriculture, finance, and smart cities.

Other years

More AKTU Data Science for IoT papers on LearnAIFast.

Data Science in IoT 2024-25 (BCIT601) Data Analytics for IoT 2023-24 (KOT077) All AI & ML papers

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