Smartvid.io Metrics Definition

Metrics Overview

Smartvid.io’s built-in analytics capabilities aim to provide customers with insight into their data and enable them to unlock the potential of analytics throughout their organization.

Smartvid.io’s analytics enable companies to harness the power of their data to measure and manage multiple aspects of risk in construction through the following:

  • In-product insights dashboards
  • Comprehensive BI dashboard services
  • APIs

The metrics we are providing encapsulate our service offerings across Safety Monitoring and Safety Observations.

For both our offerings, the focus of the metrics we have developed is two-fold:

  • Capture user behavior and activity with our platform throughout their engagement lifecycle
  • Provide risk-related measurements that allow customers to quantify their jobsite risk.

Note: Throughout this document, we are referring to our customers’ image data as Assets.


Safety Monitoring Metrics

Activity Metrics

The main goal of the activity metrics is to track our customer’s activity in our platform and provide insight into how their activity is affecting their project and organizational performance throughout the lifecycle. All activity metrics are calculated at a project, project group and organization level. The following metrics have been created:

General Activity Metrics

Number of Asset Uploads: ASSET_UPLOAD_COUNT
This metric calculates the total number of assets uploaded for a specific time period across the different types of assets a customer has including image, video, audio etc.

Average Number of Uploads per Day: AVG_UPLOAD_PER_DAY
This metric calculates the average number of asset uploads per day.

Number of Active Users: ACTIVE_USER_COUNT
This metric calculates the number of active users in the system. An active user is considered someone who has logged into our platform in the last 30 days.

Number of Unique Asset Uploaders: UPLOADER_USER_COUNT
This metric calculates the number of unique users who upload assets to the product.

Number of Tags Created by Tag Type: TAG_INSTANCE_CREATION_COUNT
This metric calculates the number of tags created by type of tag (manual, ASR, IMREC, Integration).

  • Manual Tag: Manual tags are tags added by the user. You can add an existing tag as a manual tag, or you can create a new tag as you add it manually.
  • ASR: Audio/Speech Recognition tags are tags added to videos to images.
  • IMREC: Image recognition tags are tags defined by Vinnie.
  • Integration: This is the integration the tag came from.

Number of Assets Created by Integration Type: INTEGRATION_CREATED_COUNT
This metric calculates the number of integrations created in our platform by integration type (BOX, ACONEX, PROCORE, BIM 360, BIM 360 FIELD, EGNYTE, OXBLUE).

Number of Construction Assets: CONSTRUCTION_ASSET_COUNT
This metric calculates the number of construction assets in the system. These assets are annotated by the “Construction” tag.

Ratio of Construction Assets to Total Assets: CONSTRUCTION_TO_TOTAL_ASSET_RATIO
This metric calculates the number of annotated construction assets over the total number of assets for a project.

Activity by User Metrics

Number of Assets Created by a User: USER_ASSET_CREATED_COUNT
This metric calculates the number of assets created by individual users on the platform.

Number of Tag instances Created by a User: USER_TAG_INSTANCE_CREATION_COUNT
This metric calculates the number of tag instances created by a user by tag type (manual, ASR, IMREC, Integration).

Number of User Comments: USER_COMMENT_COUNT
This metric calculates the number of comments users leave on assets.

Safety Metrics

The main goal of the safety metrics is to track our customers’ asset typology and provide insight on potential risk on their projects. All safety metrics are calculated at the project level. The following metrics have been created:

Work at Height Metrics

Number of Ladders: This metric calculates the number of assets that contain ladders. The metric is specified for different types of ladders including:

  • ALL_LADDERS_COUNT - aggregated ladder count
  • FOLDING_LADDER_COUNT - folding ladder count
  • EXTENSION_LADDER_COUNT - extension ladder count
  • SITE_LADDER_COUNT - site ladder count
  • A_FRAME_LADDER_COUNT - A-frame ladder count
  • FRAME_LADDER_COUNT - frame ladder count
  • PODIUM_LADDER_COUNT - podium ladder count

Number of Lifts: This metric calculates the number of assets that contain lifts. The metric is specified for different types of lifts including:

  • ALL_LIFTS_COUNT - aggregated lift count
  • BOOM_LIFT_COUNT - boom lift count
  • SCISSOR_LIFT_COUNT - scissor lift count

Number of Scaffolding: SCAFFOLDING_COUNT
This metric calculates the number of assets that contain scaffolding.

Work at Height: WAH_PER_HUNDRED_CONSTRUCTION
This metric calculates any work at height performed per 100 construction assets by taking into account presence of ladders, lifts and scaffolding.

Ladder to Lift Ratio: LADDER_TO_LIFT_RATIO
This metric calculates the ladder-to-lift ratio for construction assets by taking into account the presence of all ladders and lifts.

Slip & Trip Metrics

Housekeeping and Standing Water per 100 Construction Assets: HOUSEKEEPING_AND_STANDING_WATER_PER_HUNDRED_CONSTRUCTION
This metric calculates the number of instances of housekeeping and standing water for every 100 construction assets.

Housekeeping per 100 Construction Assets:  HOUSEKEEPING_PER_HUNDRED_CONSTRUCTION
This metric calculates the number of housekeeping instances only for every 100 construction assets.

Standing Water per 100 Construction AssetsSTANDING_WATER_PER_HUNDRED_CONSTRUCTION
This metric calculates the number of standing water instances only for every 100 construction assets.

PPE Compliance Metrics

Number of People: PERSON_COUNT
This metric calculates the presence of people in assets.

Glasses Incident CountGLASSES_INCIDENT_COUNT
This metric calculates the number of incidents in which glasses non-compliance was found.

Gloves Incident CountGLOVE_INCIDENT_COUNT
This metric calculates the number of incidents in which gloves non-compliance was found.

Hard Hat Incident Count:  HARD_HAT_INCIDENT_COUNT
This metric calculates the number of incidents in which hard hat non compliance was found.

Hi-vis Incident Count: HI_VIS_INCIDENT_COUNT
This metric calculates the number of incidents in which hi-viz non compliance was found.

PPE Incident CountPPE_INCIDENT_COUNT
This metric calculates the number of PPE incidents where PPE compliance didn’t occur across glasses, gloves, hard hat and hi-vis.

Glasses Compliance:  GLASSES_COMPLIANCE
This metric calculates the glass compliance percentage per number of people present in the assets.

Hard Hat ComplianceHARD_HAT_COMPLIANCE
This metric calculates the hard hat compliance percentage per number of people present in the assets.

Gloves Compliance: GLOVE_COMPLIANCE
This metric calculates the gloves compliance percentage per number of people present in the assets.

Hi-vis ComplianceHI_VIS_COMPLIANCE
This metric calculates the hi-vis compliance percentage per number of people present in the assets.

Average PPEAVERAGE_PPE
This metric calculates the overall average of PPE compliance across glasses, hard hat, gloves and hi-vis.

Safety Observations Metrics

The main goal of the observation metrics is to provide insight into our customers’ observation activity throughout the engagement lifecycle and inform on behavior that can lead to potential jobsite risk. These metrics are calculated at project, project group, organization and trade partner level.

The customers are also able to access the raw observation data that they can use to develop additional metrics according to their needs. More information on this is provided in the API guide.

Activity Metrics

General Activity Metrics

Number of Total Observations: OBSERVATION_COUNT_TOTAL
This metric calculates the total count of observations

Number of Observations by Type: OBSERVATION_COUNT_BY_TYPE
This metric calculates the number of observations by Positive and Risk types.

Ratio of Positive to Risk ObservationsOBSERVATION_POSITIVE_TO_RISK_RATIO
This metric calculates the count of positive observations by the count of risk observations.

Number of Positive and Risk Observations by Hazard CategoryOBSERVATION_COUNT_BY_HAZARD_CATEGORY_AND_TYPE
This metric calculates the count of Positive/Risk observations by the specific hazard category. By default, the Hazard categories include:

  • Access Control
  • Chemical Safety
  • Compressed Gases
  • Confined Spaces
  • Continual Improvement
  • Contractor Management
  • Crane Safety
  • Demolition Safety
  • Electrical Safety
  • Ergonomics / Body Mechanics
  • Exposed Surfaces / Protrusions
  • Fire Safety
  • Hand and Power Tools
  • Health & Hygiene
  • Hot Work
  • Housekeeping
  • Lifting & Supporting Loads
  • Lock Out Tag Out
  • Machine Guarding
  • Material Storage
  • PPE
  • Railroad Safety
  • Road and Traffic Management
  • Trenching, Excavation & Ground Stability
  • Vehicle and Mobile Equipment Safety
  • Walking and Working Surfaces
  • Working at Height
  • Working Near or Over Water
  • Environmental
  • Heat Illness Prevention Program
  • Storm Water Pollution Prevention Program

Number of Positive and Risk Observations by Method of Identification: OBSERVATION_COUNT_BY_IDENTIFICATION_METHOD_AND_TYPE
This metric calculates the count of positive/risk observations by the specific method of identification. By default, the methods of identification include:

  • 3rd Party Audit Finding
  • 3rd Party Inspection
  • AI Detected
  • Customer Notification
  • Complaint
  • Loss Control Assessment
  • Management System Review
  • Near Miss
  • O/A/E Walkthrough
  • PTP Review
  • Planned Maintenance
  • Post Incident Action
  • Procedure / Standard Requirement
  • Regulatory Inspection (Federal, State & Local)
  • Root Cause Analysis
  • Routine Inspection
  • Safer Together Tour
  • Self Audit Checklist
  • Suggestion
  • Unplanned Walkthrough

Activity by User Metrics

Number of Observations per Observation Creator:  OBSERVATION_COUNT_BY_CREATOR
This metric calculates the count of observations per unique observation creator user id.

Number of Observations per Observation Creator for Observation Types: OBSERVATION_COUNT_BY_CREATOR_AND_TYPE
This metric calculates the count of observations based on the positive and risk observations per observation creator user id.

Number of Unique Observation CreatorsOBSERVATION_COUNT_OF_UNIQUE_CREATORS
This metric calculates the count of unique observation creator user ids.

Number of Unique Observation AssigneesOBSERVATION_COUNT_OF_UNIQUE_ASSIGNEES
This metric calculates the count of unique user ids that are assigned to observations

Safety Metrics

Average Risk Score: OBSERVATION_RISK_AVERAGE_RISK_SCORE
This metric calculates the average risk score for risk observations only.

Maximum Risk Score: OBSERVATION_RISK_MAXIMUM_RISK_SCORE
This metric calculates the maximum risk score for risk observations only.

Number of Risk Observations by Risk BandOBSERVATION_RISK_COUNT_BY_RISK_BAND
This metric calculates the count of risk observations only by specific risk band. The risk bands include:

  • Low
  • Medium
  • High
  • Extreme


Number of Risk Observations by Risk ScoreOBSERVATION_RISK_COUNT_BY_RISK_SCORE
This metric calculates the count of risk observations only by risk scores. The risk scores are  integers between 1 and 25.

Great Catches: This metric calculates the number of observations that were noted as “Great Catch”. A great catch observation is an observation deemed particularly important and unique to highlight. The following metrics are calculated:

Total number of great catches: OBSERVATION_GREAT_CATCH_COUNT_TOTAL
This metric calculates the total count of observations noted as “great catch”.

Number of great catches by type of observation (positive and risk): OBSERVATION_GREAT_CATCH_COUNT_BY_TYPE
This metric calculates the count of positive and risk observations noted as great catches.

Great Catch Average Risk Score: OBSERVATION_RISK_GREAT_CATCH_AVERAGE_RISK_SCORE
This metric calculates the average risk score of great catches for risk observations only.

Workflow Metrics

Number of Open Observations by Status and Observation Type: OBSERVATION_COUNT_OPEN_BY_STATUS_AND_TYPE
This metric calculates the count of open observations (positive, risk) by specific status. By default, the status values include:

  • New
  • In Progress
  • With Trade Partner
  • Delayed
  • Closed
  • Ready for Review
  • Closed, Reviewed


Number of Open ObservationsOBSERVATION_COUNT_OPEN_BY_TYPE
This metric calculates the count of observations by type (positive, risk) that are open.

Number of Closed Observations: OBSERVATION_COUNT_CLOSED_BY_TYPE
This metric calculates the count of observations by type (positive, risk) that are closed.

Number of Past Due Risk ObservationsOBSERVATION_RISK_COUNT_PAST_DUE
This metric calculates the count of risk observations that are past due the date they should be closed.

Average Days of Open Risk Observations: OBSERVATION_RISK_AVERAGE_DAYS_OPEN
This metric calculates the average days risk observations remain open.

Average days of Open Observations by Risk Band: OBSERVATION_RISK_AVERAGE_DAYS_OPEN_BY_RISK_BAND
This metric calculates the average days risk observations remain open based on their risk band.

Average days to Close a Risk Observation: OBSERVATION_RISK_AVERAGE_DAYS_IT_TOOK_TO_CLOSE
This metric calculates the average days to close a risk observation that was open in a non-closed state.

Average lateness in days for past due observations: OBSERVATION_RISK_AVERAGE_DAYS_LATENESS_FOR_PAST_DUE
This metric calculates the average number of days in closing observations that are past due the date they should be closed.

Metric Calculation Levels

Our metrics are calculated at multiple levels and time periods to provide our customers’ flexibility in how they are capturing their insights.

The metric level indicates the business level granularity that a metric is measured as. We currently support calculations for project, project group (if configured), organization and user levels.

The time period buckets in place represent the date ranges for which a specific metric is calculated. We currently support calculations for the last 1, 7, 30, 60, 90 days and All time (historic calculation).

The metrics are calculated and refreshed nightly and are generally available for consumption by 7 AM ET.

Below is detailed information on calculation levels supported for the various types of metrics:

Safety Monitoring Metrics

Activity Metrics:

  • Time Period: Last 1 day, 7 days, 30 days, 60 days, 90 days and All Time
  • Level: Project, Project Group, Organization

Safety Metrics

  • Time Period: Last 1 day, 7 days, 30 days, 60 days, 90 days and All Time
  • Level: Project

Observations Metrics

Time Period: Last 1 day, 7 days, 30 days, 60 days, 90 days and All Time

LevelProject, Project Group, Organization, Trade Partner


Metric Consumption

Our customers can access the metrics through our in-product User Interface, API calls, as well as our BI dashboard services.

User Interface

Our customers can access and view our metrics in our product

API

Our metrics can be accessed through API calls. It is very useful if you want to “feed” your internal systems and databases. Please refer to this link to read our Metrics API guide.

BI Dashboards

Our BI dashboard services provide visibility to all the metrics we have outlined above and can be utilized across the organization. Contact support@smartvid.io to request your set of dashboards.


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