Benefits and Barriers of Monitoring Construction Activities Using Hi-Resolution Automated Cameras

Fusing passive RFID and BIM for increased accuracy in indoor localization

“…Moreover, GPS cannot be used in an indoor environment (Ogaja 2011), and neither technology is able to record the timestamps which is vital for localization. Cameras and vision technology have been used in construction for project monitoring and safety (Bohn and Teizer 2010, Memarzadeh et al 2012, Yang et al 2014, Yang et al 2011, Yang et al 2010, Teizer and Vela 2009), but have not been integrated with BIM based FM. Vision based technologies are not suitable for tracking objects because they do not (yet) rely on unique identification for each utility, and therefore cannot distinguish between similar objects (Kropp et al 2014).…”

Status quo and open challenges in vision-based sensing and tracking of temporary resources on infrastructure construction sites

“…Camera-or video-based monitoring technology in combination with processing algorithms typically provide a non-intrusive, easy, inexpensive, and rapid mechanism for generating a body of operational information and knowledge which, when made publicly available to project stakeholders, enable secure inquiry into construction operations that is currently not possible [12]. Longer term, vision-based research can serve as a valuable aid to project management by enabling tighter control and greater efficiency.…”

“…Although vision based sensing of site operations is applied on several thousand jobsites every day and the technology generally comes at low cost and yields high benefits [12,14], the complexity of handling large data sets has prevented significant progress. Field applications so far have mostly focused on recording site status and data archiving [14].…”

“…Temporary material supply tracking using time-lapse imagery (material: steel shoring piles; imagery taken from[12]). …”

Measuring Bridge Construction Efficiency Using the Wireless Real-Time Video Monitoring System

“…Results of previous research indicate that existing computer vision technologies have the required capabilities of successfully recognizing objects such as flowers, soccer balls, tools, and materials (Brilakis et al 2005;Shapiro and Stockman 2001); human parts such as the limbs, torso, and head (Mori and Malik 2002;Ramanan and Forsyth 2003); and human motions such as walking, running, kicking, and jumping (Bohn and Teizer 2009;Ioffe and Forsyth 2001;Lan and Huttenlocher 2005;Lim et al 2006). Building on these successes, computer scientists have also developed technologies to automatically detect human actions such as dancing and playing tennis and football (Efros et al 2003;Han et al 2006;Yilmaz and Shah 2005).…”