Master Thesis Assignment: Creating a Smart Construction Site through Wearables with a Focus on Activity Recognition
Introduction
The construction industry is ripe for a technological revolution, and you could be at the forefront! This Master’s thesis project offers an exciting opportunity to delve into the world of wearable technology and its application in creating a smart construction site.
Objective
The primary objective of this project is to design and develop a system that uses wearable technology for activity recognition on a construction site. This system will enhance safety, improve efficiency, and facilitate real-time decision-making.
Project Description
You will be tasked with:
- Literature Review: Conduct a review of existing research on wearable technology in the construction industry, with a particular focus on activity recognition.
- System Design: Design a system that uses wearable technology, particularly the motion sensors, to recognize and record various activities on a construction site. This could include activities like lifting, carrying, climbing, digging, operating machinery, etc.
- Data Collection & Analysis: Collect and analyze data from the wearables to gain insights into the activities on the construction site. This will involve applying machine learning and data analysis techniques.
- System Testing & Evaluation: Test the designed system in a construction environment and evaluate its performance.
Benefits
This project will provide you with the opportunity to:
- Work on a cutting-edge topic at the intersection of construction, wearable technology, and data science.
- Gain hands-on experience with wearable technology, machine learning, and data analysis.
- Make a tangible impact on the construction industry by improving safety and efficiency.
- Contribute to the academic body of knowledge in this emerging field.
Research Project - ECOLOGIC
This project is an integral component of the broader ECOLOGIC (Emission Control and Logistics Optimization for Green Infrastructure Construction) research initiative, which seeks to significantly enhance the sustainability of the Dutch construction logistics sector. The overarching goal is to achieve this by developing dependable data-driven insights and employing advanced analysis techniques such as IoT and AI, all facilitated through a real-time Carbon Digital Twin (DT). ECOLOGIC involves collaboration with various industrial partners, presenting the opportunity for valuable cooperation.
Pre-Requisites
Prospective students should have a background in Computer Science, Embedded Systems, Data Science, or a related field. Knowledge of machine learning, data analysis, and experience with wearable technology will be beneficial.
Are you ready to take up this challenge and contribute to shaping the future of the construction industry? Join us in this exciting endeavor!
Contact
- Özlem Durmaz, associate professor, Pervasive Systems (ozlem.durmaz@utwente.nl)
- Rob Bemthuis, postdoctoral researcher, Pervasive Systems (r.h.bemthuis@utwente.nl)