# Automated Data Acquisition in Construction with Remote Sensing Technologies
## 4 Integration of Various RS Technologies
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Type** & **Integrated RS System** & **Capabilities** & **Limitations** & **Refs.** \\ \hline \multirow{8}{*}{RFID + LS} & (1) & Faster and more robust recognition and positioning of objects in 3D modeling & (1) & Poor positioning performance when the objects are the corner of a room \\  & RFID + LS & (2) & Laser scanners are relatively expensive & (TLS could cost more than 560k) \\  & & laser scanners object recognition specially in a crowded and full of furniture environment & (3) & Need for a facility management \\ \hline \multirow{8}{*}{Integration of the vision-based technologies other RTLS} & (1) & Less number and time for scanning are required & \\  & & (2) & Less number of digital photos are required which & \\  & & (3) & Better object recognition capabilities by adding & (1) & Expensive laser scanners \\  & & depth information from laser data to the available & (2) & Problems associated with calibration \\  & & digital photo planes & & and orientation of data acquired from two sensory sources, e.g., & \\ \multirow{8}{*}{Integration of the vision-based technologies other RTLS} & Photogrammetry + laser scanning & (4) & Convenient for modeling objects with unclear & (25, 28, 33, 34, 38, 50) \\  & & & geometrical properties (e.g., excavation activities) & geo-referencing issues \\  & & (5) & More accuracy in the localization of edge points & (5) & Less effective when the site is crowded \\  & & & (6) & Providing more details about material, color, and & or covered by enclosures \\  & & & texture of the objects which improves the & \\  & & & geometry and visual quality of the 3D modeling & \\  & & & (7) & Self-calibrating capabilities for cameras & \\ \hline \multirow{8}{*}{Photogrammetry + RTS (robotic total station)} & Photogrammetry & (1) & Enhanced scaling and 3D modeling capabilities & (1) & High cost of RTS devices \\  & & (2) & Better measurement accuracy (down to few & (2) & Synchronization of digital cameras \\  & & & decimeter) rather than using individual & \\ \cline{1-1}  & & & photogrammetry techniques & (3) & Limited capability for tacking multiple \\ \cline{1-1}  & & & & moving objects \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._ \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Type** & **Integrated RS System** & **Capabilities** & **Limitations** & **Refs.** \\ \hline  & (1) & More reliability in positioning in comparison with individual use of each technology by replacing the data of one sensor with another in case of any failure in each sensor & (2) & Calibration difficulties specially for large scale sites \\ Photoy videogrammetry & (2) & More accurate and timely information are provided by proving more automation and decreasing computational effort & (3) & Less accuracy in comparison with other geo-referenced photogrammetry techniques (e.g., using a RTS or GNSS system) \\  & (3) & Portability & (1) & Discrepancy between the accuracy of the UWB mapping and that of LiDAR mapping \\  & (1) & Overcoming challenges associated with the presence of multipath, NLOS 2 protogations and the UWB mapping and that of LiDAR mapping & (6,15,28) \\ Laser scanning + UWB & (2) & Less accumulated error in comparison with an individual usage of laser scanning technology & (2) & High implementation cost \\  & (3) & Ease of need for prior knowledge or control inputs & \\ \hline \hline \end{tabular}  
\end{table} 
Table 3: _Cont._