Guide Home / 7. Information and Systems / 7.2 Collecting Asset Data / 7.2.2 How to Collect Data

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.

Before collecting new data, make sure you are leveraging data that already exists or is already collected, and coordinate with other agency groups that may have a need for the same data.

Table 7.3 - Example Data Collection Approaches

Asset ClassData Collection MethodData CollectedNotes
PavementVisual InspectionPresent 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
PavementAutomated data collection vehicle with laser scanning systemroughness, cracking, nuttingIncludes 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
PavementLight Detections and Ranging (LiDAR)/ Terrestrial Laser Scanning (TLS)roughness, cracking, nuttingProvides a high resolution continuous pavement survey. Often inventory data for other assets can be extracted from the data set
PavementFalling weight deflectometerstrength/deflection
PavementLocked wheel tester/spin up testerskid resistance
PavementGround Penetrating Radar (GPR)layer thicknesses, detection of voids and crack depth
PavementCoringlayer thicknesses, detection of voids and crack depth
PavementSmart phonespotholes, roughnessIncludes systems for reporting of potholes and measuring roughness through crowdsourcing
Structures and BridgeSensorsinventory, condition ratingsStrain and displacement gauges; wired or wireless,
Structures and BridgeUnmanned Aerial Vehicles (UAVs)condition of non-bridge struc- tures (e.g. retaining walls)
Structures and BridgeLiDARVertical Clearance
Structures and BridgeVisualinventory, condition ratingsCan be supplemented using UAV and other technologies
Structures and BridgeAcoustical (e.g., impact echo)delamination, corrosion
Structures and BridgeInfrared/ Thermal Imagingdelamination, corrosion
Structures and BridgeGPRconcrete deck condition
Structures and BridgeHalf Cell Potential Testconcrete deck condition
Traffic SignsVideologinventory, condition ratingsautomated or semi-automated techniques available for classification
Traffic SignsMobile LiDARinventory, condition ratings
Traffic SignsField Inspection – mobile applicationinventory, condition ratings
Traffic SignsRetroreflectometerretroreflectivity

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.