Industry Perception of the Knowledge and Skills Required to Implement Sensor Data Analytics in Construction

  • Mohammad Khalid
  • , Abiola Akanmu
  • , Homero Murzi
  • , Sang Won Lee
  • , Ibukun Awolusi
  • , Daniel Manesh
  • , Chinedu Okonkwo

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Construction, one of the largest industries in the world, consistently underperforms and faces barriers in leveraging the full potential of applying analytics to sensor data due to a lack of a skilled workforce. The prospects for data-driven solutions to address emerging construction challenges and enhance performance across project life cycles are therefore constrained. Through mixed-method research utilizing a survey and focus group, this study investigates the knowledge and skills required for graduating construction engineering and management students to implement sensor data analytics in the construction sector. The findings revealed that sensor data analytics knowledge and skills are required to systemically process and analyze data from sensing technologies and present them in formats for effective decision-making. The presented key knowledge areas, specific skills, and their significance can aid the construction industry and academics to streamline professional development efforts to match the actual demands, allowing for more efficacy in workforce training. The future construction workforce is expected to gain a competitive edge with sensor data analytics knowledge and skills as the ubiquitous integration of sensing technologies continues to drive the tremendous growth of sensor data.

Original languageEnglish (US)
Article number04023010
JournalJournal of Civil Engineering Education
Volume150
Issue number1
DOIs
StatePublished - Jan 1 2024
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Industrial relations
  • Strategy and Management

Keywords

  • Construction education
  • Knowledge and skills
  • Sensing technologies
  • Sensor data analytics

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