Dr. Reza Akhavian is an Assistant Professor of Construction Management at the School of Engineering, California State University East Bay (CSUEB). He received his Ph.D. in Civil Engineering (with Construction Engineering and Management concentration) from the University of Central Florida (UCF). He also holds an M.S. (UCF, 2012) and a B.S. (University of Tehran, 2010) in Civil Engineering. He has more than 20 articles published in peer-reviewed journals and conference proceedings and serves as a member of the editorial board of the American Society of Civil Engineers (ASCE) Journal of Construction Engineering and Management (JCEM).
Technology and Construction Accidents
Applications of data analytics, artificial intelligence, and automation in construction are ever-growing to save time, money, and lives in this labor-intensive multi-billion industry. Imagine a construction worker with a smartphone affixed on his arm using an armband. Or a piece of heavy equipment with a smartphone attached to its cabin windshield. While the worker or the equipment are engaged in construction activities, the movement of the smartphones generates distinguishing patterns in the data collected from their inertial measurement unit (IMU) sensors. In my research group, we collect these sensors data and using machine learning, detect the activities undertaken at any given time period. In other words, we train computers to recognize each activity using motion and vibration of the body of workers or equipment. Having such information, data-driven knowledge can be generated and data-informed decisions can be made. For example, workers’ unsafe body motions and movements can be detected, which in turn helps preventing work-related musculoskeletal disorders. This is especially important in construction because tasks are often physically-demanding and labor-intensive. We use similar algorithms to detect equipment working state to identify the times when the equipment is idle but the engine is on. Adjusting the engine state accordingly results in greenhouse gas emission reduction and cost saving. Another way of autonomously collecting data from active projects or built environment is using unmanned aerial vehicles (UAVs) or drones. For example, UAVs now fly over jobsites to collect information regarding the progress of the project completion in a faster, cheaper, and more reliable way than manual methods. Other applications that we are currently exploring include surveying existing buildings to detect heat energy leak and inspection of structural elements and connection. Data analytics, artificial intelligence, automation, and robotics, are the building blocks of the construction industry’s future.