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Data Reference H-P

Objects

HandheldCallingAnnotation

Kind: Object
Property
Type
Description
type
'HandheldCallingAnnotation'
start
String
end
String
duration
Int
Duration is in milliseconds.

HandlingWithoutCallingAnnotation

Kind: Object
Property
Type
Description
type
'HandlingWithoutCallingAnnotation'
start
String
end
String
duration
Int
Duration is in milliseconds.

HandsfreeCallingAnnotation

Kind: Object
Property
Type
Description
type
'HandsfreeCallingAnnotation'
start
String
end
String
duration
Int
Duration is in milliseconds.

IAggregatedAnomaly

Kind: INTERFACE
Implemented by: AggregatedDistanceAnomaly, AggregatedDurationAnomaly, DayCountAnomaly, OccurrenceCountAnomaly An anomaly that we have detected for a user over a period of time.
Property
Type
Description
period
Aggregation period over which the data is calculated.
day_part
DayPart
Optional additional aggregation over which the data is calculated.

IAnomaly

Kind: INTERFACE
Property
Type
Description
type
'IAnomaly'
start
String
end
String
analysis_type
anomaly
Anomaly
sigma
Float
The observed standard deviation from expected behavior for this anomaly. If the standard deviation is high, the anomaly confidence will be low.
probability
Float
The larger the probability, the more anomaly. Value is between 0.0 and 1.0.

IBranchEvent

Kind: INTERFACE
Implemented by: StationaryPrediction, TransportPrediction A single predicted event.
Property
Type
Description
start
String
Predicted start time of the event.
end
String
Predicted end time of the event.
probability
Float
The probability of this prediction occurring.
type
'IBranchEvent'

IDayCountAnomaly

Kind: INTERFACE
Implemented by: DayCountAnomaly
Property
Type
Description
observed_days
Float
Observed amount of days.
expected_days
Float
Expected amount of days.

IDistanceAnomaly

Kind: INTERFACE
Property
Type
Description
observed_distance
Float
Observed distance in meter.
expected_distance
Float
Expected distance in meter.

IDurationAnomaly

Kind: INTERFACE
Property
Type
Description
observed_duration
Float
Observed duration in seconds.
expected_duration
Float
Expected duration in seconds.

IEvent

Kind: INTERFACE
Implemented by: Trip, Stationary, Transport An occurrence of an event that we have detected for a user. This interface is implemented by the Stationary and Transport models.
Property
Type
Description
type
EventType
'IEvent'
previous_event_id
String
next_event_id
String
start
String
The time this moment started, ISO8601. Value can change and become more accurate over time. Example: 2015-05-28T14:37:14.839+00:00
end
String
The time this moment ended, ISO8601. Value can be null. Value can change and become more accurate over time. Example: 2015-05-28T14:37:14.839+00:00
start_ts
BigInt
end_ts
BigInt
analysis_type
How well this event is analyzed by the platform, this value will update over time. Possible values: preliminary, indepth, processed.
weather
Weather data associated with this event.

IEventFeedback

Kind: INTERFACE
Implemented by: StationaryFeedback, TransportFeedback An occurrence of event feedback submitted by a user.
Property
Type
Description
event_feedback

IEventPrediction

Kind: INTERFACE
Implemented by: StationaryIntervalPrediction, TransportIntervalPrediction An occurrence of an event prediction that we have detected for a user.
Property
Type
Description
event_type
EventType

IFeedback

Kind: INTERFACE
Implemented by: StationaryFeedback, TransportFeedback, CrashFeedback, MomentFeedback An occurrence of feedback submitted by a user.
Property
Type
Description
type
'IFeedback'
end
String
End time the feedback relates to, sourced by the event, moment or user-provided.
created
String
Time when this feedback entry was created.
projection_time
String
Time to provide when the feedback data was read from the API. ISO8601. Optional.

IIntervalPrediction

Kind: INTERFACE
Implemented by: StationaryIntervalPrediction, TransportIntervalPrediction A prediction that has a start interval.
Property
Type
Description
start_interval

IMoment

Kind: INTERFACE
Implemented by: GenericMoment, CityMoment, CountryMoment An occurrence of a MomentDefinition that we have detected for a user.
Property
Type
Description
type
'IMoment'
start
String
The time this moment started, ISO8601. Value can change and become more accurate over time. Example: 2015-05-28T14:37:14.839+00:00
end
String
The time this moment ended, ISO8601. Value can be null. Value can change and become more accurate over time. Example: 2015-05-28T14:37:14.839+00:00
start_ts
BigInt
end_ts
BigInt
analysis_type
How well this moment is analyzed by the platform, this value will update over time. Possible values: preliminary, indepth, processed.
moment_definition_id
String
The ID of the MomentDefinition this moment relates to.
moment_definition
The MomentDefinition this moment relates to.

IMomentAnomaly

Kind: INTERFACE
Property
Type
Description
moment_definition_id
String

IMomentFeedback

Kind: INTERFACE
Implemented by: MomentFeedback An occurrence of moment feedback submitted by a user.
Property
Type
Description
moment_feedback

IOccurrenceCountAnomaly

Kind: INTERFACE
Implemented by: OccurrenceCountAnomaly
Property
Type
Description
observed_occurrences
Float
Observed amount of occurrences.
expected_occurrences
Float
Expected amount of occurrences.

IPrediction

Kind: INTERFACE
Implemented by: StationaryIntervalPrediction, TransportIntervalPrediction An occurance of a prediction that we have detected for a user.
Property
Type
Description
type
'IPrediction'
probability
Float

ISegment

Kind: INTERFACE
Implemented by: GenericSegment An occurrence of a SegmentDefinition that we have detected for this user.
Property
Type
Description
type
'ISegment'
segment_definition_id
String
The ID of the SegmentDefinition this segment relates to.
segment_definition
The SegmentDefinition this segment relates to.

IStationaryAnomaly

Kind: INTERFACE
Property
Type
Description
place_category
String
location_significance

ITimeAggregateAttribute

Kind: INTERFACE
Implemented by: CommuteTimeAggregate, StationaryTimeAggregate, TransportTimeAggregate, WorkingTimeAggregate An attribute that aggregates by TimePeriod.
Property
Type
Description
period

ITransportAnomaly

Kind: INTERFACE
Property
Type
Description
transport_mode
transport_mode_category

ITransportBehaviorAnnotation

Kind: INTERFACE
Property
Type
Description
type
'ITransportBehaviorAnnotation'
start
String
end
String

IUser

Kind: INTERFACE
Implemented by: User, ControlUser
Property
Type
Description
type
UserType
'IUser'
id
String
The unique identifier for this user.
can_login
Boolean
created_at
String
The time when this user was created, ISO8601. Example: 2015-05-28T14:37:14.839+00:00
sdk
application_id
String
The ID of the Application this user relates to.
application
The Application this user relates to.
custom_event_history
Custom Event History
event_history
IEvent
An unordered list of events we have detected for this user.
car_behavior
The user car behavior aggregated over the last 9 weeks.
aggregated_driving_scores
transport_heatmaps
The aggregated transport heatmaps calculated over time.
metadata
JSON
All custom set metadata properties on this user. This is a JSON object with key->value pairs.
device
The last known active tracking device metadata
active_moments
IMoment
An unordered list of moments that are ongoing from the point of view of the platform.
moment_history
IMoment
An unordered list of moments we have detected for this user.
semantic_time
The user's semantic time averaged over time.
anomaly_history
IAnomaly
segments
ISegment
An unordered list of segments that are detected for this user.
location_clusters
Locations this user has been stationary at and the features we have learned about those locations (significance, point of interest, ...)
location
Waypoint
The last known location we have for this user.
health
The historical health attributes.
attributes
predictions
Event/Moment predictions for this user
prediction_tree
Multiple possible predictions of events that are about to take place next. They are ordered by the highest probability of each sequence of events taking place.
feedback_history
IFeedback
Feedback on this user

IUserAttribute

Kind: INTERFACE
Property
Type
Description
type
'IUserAttribute'

InputAddress

Kind: INPUT_OBJECT

InputCrash

Kind: INPUT_OBJECT

InputCrashFeedback

Kind: INPUT_OBJECT

InputEventFeedback

Kind: INPUT_OBJECT

InputLocationPlaceCandidate

Kind: INPUT_OBJECT

InputMoment

Kind: INPUT_OBJECT

InputMomentFeedback

Kind: INPUT_OBJECT

InputOndeviceMLModel

Kind: INPUT_OBJECT
Name of the models that were used to detect the crash. Mainly used as internal reference.

InputStationary

Kind: INPUT_OBJECT

InputStationaryLocation

Kind: INPUT_OBJECT

InputTrajectoryWaypoint

Kind: INPUT_OBJECT
A single waypoint in the augmented trajectory.

InputTransport

Kind: INPUT_OBJECT

InputTransportBehaviorFeatures

Kind: SCALAR

InputTransportBehaviorScores

Kind: SCALAR

InputTransportTrajectory

Kind: INPUT_OBJECT

InputWaypoint

Kind: INPUT_OBJECT

JSON

Kind: SCALAR
The JSON scalar type represents JSON values as specified by ECMA-404.

LocationCluster

Kind: Object
Property
Type
Description
type
String
'LocationCluster'
last_visit
String
latitude
Float
longitude
Float
address
Address
radius
Int
is_poi
Boolean
significance

LocationPlaceCandidate

Kind: Object
A place selected from one of our data sources.
Property
Type
Description
type
String
'LocationPlaceCandidate'
name
String
Name of the place. Can be null if no specific place can be assigned.
category_hierarchy
String
A list of venue categories in hierarchical order. The first item represents the broadest category, with each subsequent item representing a more specific one. For ex. ["shop","food","grocery","supermarket"]
probability
Float
latitude
Float
longitude
Float
provider
String

LocationSignificance

Kind: ENUM
    home: A location identified as one of the user's home locations.
    work: A location identified as one of the user's work locations.
    regular: Locations you regularly visit. Typical examples are places you regularly go shopping, your gym, a friend's place, ...
    nonregular: Default type for locations you don't often visit.
    poi: Points of interest that have not been classified as home/work previously.
    new: Only available a short time when you visit the location the first time.

MomentDefinition

Kind: Object
A single moment definition.
Property
Type
Description
type
String
'MomentDefinition'
id
String
Identifier of this MomentDefinition. Possible values: working_at_work,working_remote,home,morning,lunch,afternoon,evening,night,commute_from_work,commute_from_home,business_trip,holiday,nearby_home,nearby_work,city_name,country,children_drop_off,sport_routine,shopping_routine,evening_entertainment,night_out,afternoon_drinks,evening_drinks,breakfast_out,lunch_out,dinner_out,about_to_working,about_to_commute_from_home,about_to_commute_from_work,about_to_children_drop_off,about_to_sport,about_to_shopping,nearby_poi
category
String
Category ID of this MomentDefinition, if any. Possible values: activity,semantic_time,travel,geography,location,about_to_routine
display_name
String
A displayable name for this MomentDefinition.
description
String
A short description about this MomentDefinition.

MomentFeedback

Kind: Object
Implements: IFeedback, IMomentFeedback
Property
Type
Description
type
'MomentFeedback'
end
String
End time the feedback relates to, sourced by the event, moment or user-provided.
created
String
Time when this feedback entry was created.
projection_time
String
Time to provide when the feedback data was read from the API. ISO8601. Optional.
moment_feedback
moment
IMoment
The Moment this feedback refers to.

MomentFeedbackFeedback

Kind: Object
Property
Type
Description
moment_definition_id_assessment
If the user thinks our detected moment is correct.
moment_definition_id_feedback
String
Correction by the user in case our detection was incorrect.

MomentType

Kind: ENUM
    GenericMoment
    CityMoment
    CountryMoment

OccurrenceCountAnomaly

Kind: Object
Property
Type
Description
type
'OccurrenceCountAnomaly'
start
String
end
String
analysis_type
anomaly
Anomaly
sigma
Float
The observed standard deviation from expected behavior for this anomaly. If the standard deviation is high, the anomaly confidence will be low.
probability
Float
The larger the probability, the more anomaly. Value is between 0.0 and 1.0.
period