There are many different approaches to collecting asset and related data. Often a mix of approaches is used, including visual inspection, semi-automated and automated approaches. The technologies for data collection are advancing rapidly, allowing for increased use of semi-automated and automated approaches for collecting more accurate data at a lower cost. Examples of recent innovations include:
- Improvements in machine vision that allow extracting some forms of asset inventory data from video or LiDAR.
- Use of unmanned aerial vehicles (UAV, also called drones) for allowing bridge inspectors to obtain video of hard-to-reach areas of a bridge.
- Improvements in non-destructive evaluation (NDE), allowing for greater use of techniques such as ground penetrating radar (GPR) for pavement and bridge decks and instrumenting bridges to monitor performance over time.
- Improvements in hand-held devices allowing for increased field use, reducing cost and time of manual data collection.
Several of these technologies provide opportunities to save money by collecting data for multiple assets within a single collection effort. Table 7.3 provides a summary of potential data collection approaches for common roadway asset classes.
Table 7.3 - Example Data Collection Approaches
|Asset Class||Data Collection Method||Data Collected||Notes|
|Pavement||Visual Inspection||Present Serviceability Index (PSI)||Often used in urban environments or for small networks where data collection using automated collection approaches is impractical – can be supplemented by UAVs|
|Pavement||Automated data collection vehicle with laser scanning system||roughness, cracking, nutting||Includes a range of 2D video and 3D laser-based systems. Many systems store video images and can capture additional measures, such as cross slope, gradient and curvature|
|Pavement||Light Detections and Ranging (LiDAR)/ Terrestrial Laser Scanning (TLS)||roughness, cracking, nutting||Provides a high resolution continuous pavement survey. Often inventory data for other assets can be extracted from the data set|
|Pavement||Falling weight deflectometer||strength/deflection|
|Pavement||Locked wheel tester/spin up tester||skid resistance|
|Pavement||Ground Penetrating Radar (GPR)||layer thicknesses, detection of voids and crack depth|
|Pavement||Coring||layer thicknesses, detection of voids and crack depth|
|Pavement||Smart phones||potholes, roughness||Includes systems for reporting of potholes and measuring roughness through crowdsourcing|
|Structures and Bridge||Sensors||inventory, condition ratings||Strain and displacement gauges; wired or wireless,|
|Structures and Bridge||Unmanned Aerial Vehicles (UAVs)||condition of non-bridge struc- tures (e.g. retaining walls)|
|Structures and Bridge||LiDAR||Vertical Clearance|
|Structures and Bridge||Visual||inventory, condition ratings||Can be supplemented using UAV and other technologies|
|Structures and Bridge||Acoustical (e.g., impact echo)||delamination, corrosion|
|Structures and Bridge||Infrared/ Thermal Imaging||delamination, corrosion|
|Structures and Bridge||GPR||concrete deck condition|
|Structures and Bridge||Half Cell Potential Test||concrete deck condition|
|Traffic Signs||Videolog||inventory, condition ratings||automated or semi-automated techniques available for classification|
|Traffic Signs||Mobile LiDAR||inventory, condition ratings|
|Traffic Signs||Field Inspection – mobile application||inventory, condition ratings|
Once data are collected, it is essential to put in place regular processes for updating the data. This can be accomplished through periodic data collection cycles, or through updating as part of asset project development and maintenance management processes.