Calendar

Urban Infrastructure Engineering

Urban Infrastructure Engineering

Research under Infrastructure Engineering and Construction Management focuses on the planning, design, analysis, and construction management of infrastructure systems crucial to the economic viability of UAE. 

Research projects covers construction planning and intelligent management of buildings, transportation networks, and public works, such as roads, bridges, and airport. Urban planning ensures that infrastructure projects consider aspects of resilience and sustainability. Leveraging the wealth of local civil engineering and construction activities, and the transportation sector ensures relevance and immediate use of research results.

Faculty

Analysis of Best Practices for Energy Efficient Buildings through Building Energy Modeling in Design

Construction Safety – Training for Engineers and Supervisors on Crane Safety

Traffic Monitoring and Travel Time Prediction using Mobile Sensing Data

Real Time Traffic Monitoring and Network-wide Travel Time Prediction with Multi-Sensor Data Fusion in Mobile Environment


Analysis of Best Practices for Energy Efficient Buildings through Building Energy Modeling in Design

Abu Dhabi has set a clear vision for 2030, dictating sustainability as the foundation for all new commercial and residential developments in the Emirate. In setting the Sustainable Green Building Design Criteria, green building practices, such as life cycle materials usage; energy and thermal efficiency; and indoor environmental quality are advocated by the Urban Structure Framework Plan (Plan Abu Dhabi 2030). To this effort, building energy performance modeling is used to evaluate design options and to develop the business case for incorporating energy efficiency. However, owners and decision-makers perceive building energy modeling to be an add-on cost that does not bring real beneficial information into the design process, building operation processes or energy efficient building systems. As a result, there are significant amount of misused opportunities of energy efficiency-related decisions that could be incorporated into the building design through quality energy modeling. The aim of this study will be to develop a comprehensive set of energy modeling procedures that cover key modeling applications.

The best practice analysis of this proposed study will help optimize the building design and will allow the design team to prioritize investment in the strategies that will have the greatest effect on the building’s energy use. Specifically, this project aims to identify the market opportunities for using the building energy modeling to inform a range of efficiency-related decisions, identify the top stakeholders and decision makers and their perception of energy efficient building design, and assess the markets in terms of potential energy cost savings, opportunities for competitive advantage and profitability, workforce skills and capabilities required to implement, and barrier to adoption.

Personnel

PI: Dr. Chung-Suk Cho

Co-PI: Dr. Young-Ji Byon

Funding

KUIRF L1, 2015 (AED 132,000)


Construction Safety – Training for Engineers and Supervisors on Crane Safety

Although all stakeholders including the construction management team are responsible for ensuring safe crane operations at site, their lack of complete knowledge on the latest OSHA standards, regulations and best practices for planning and conducting crane operations has often resulted in fatal crane accidents. As such, this research includes developing a tool that can be used by all stakeholders responsible for the management and planning of crane operations to assess their crane safety readiness prior to and during crane operation activities. Specifically, this research aims to investigate the hypothesis that the new OSHA crane regulations have significantly lowered the number of crane related accidents and to develop a safety readiness checklist  that serves as a guide for the project team to carryout safe crane operation and to prevent accidents and avoid costly code violations.

Urban Infrastructure

Personnel

PI: Dr. Chung-Suk Cho


Traffic Monitoring and Travel Time Prediction using Mobile Sensing Data 

As traffic demand continues to increase along with recent economic growth in UAE, especially in Abu Dhabi, traffic congestion and its accompanying negative effects (e.g., fuel consumption, air pollution, noises, etc.) have been one of the most challenging problems in urban areas (DOT, 2008; Abu Dhabi Urban Planning Council, 2011). Traffic monitoring is a key to mitigate congestion because the congestion mechanism should be unveiled to counteract the problem. Recent advance in traffic monitoring technologies can be used toward this end. 

This research proposes development of traffic monitoring system and travel time prediction algorithms using mobile sensing data. The research outcomes are expected to provide solid groundwork to build an effective transportation management system for transportation network, and efficient and effective nationwide ITS deployment can be established.

Personnel

PI: Dr. Young-Ji Byon

Funding

KAIST-KU Level 2, 2014 (AED 333,000)


Real Time Traffic Monitoring and Network-wide Travel Time Prediction with Multi-Sensor Data Fusion in Mobile Environment

As traffic demand continues to increase along with recent economic growth in UAE, especially in Abu Dhabi, traffic congestion and its accompanying negative effects (e.g., fuel consumption, air pollution, noises, etc.) have been one of the most challenging problems in urban areas (DOT, 2008; Abu Dhabi Urban Planning Council, 2011). Traffic monitoring is a key to mitigate congestion because the congestion mechanism should be unveiled to counteract the problem. Recent advance in traffic monitoring technologies can be used toward this end.

This research proposes development of traffic monitoring system based on traffic data fusion and travel time prediction algorithms by using heterogeneous traffic data sources. The research outcomes are expected to provide solid groundwork to build an effective transportation management system for transportation network, and efficient and effective nationwide ITS deployment can be established.

Personnel

PI: Dr. Young-Ji Byon

Funding

KAIST-KU Seed Money 2013 (AED 245,000)