Data Reference C-G
This document refers to deprecated parts of the platform and has been left intact to help customers with legacy integrations. In order to access the latest platform features and documentation, please go to https://docs.sentiance.com.
Objects
CarBehaviorFeatures
Kind: Object
type
String
'CarBehaviorFeatures'
True
phone_handling
Int
Total time in milliseconds we detected phone handling by the user during this transport. Value will be -1 when the transport data was not sufficient.
True
distance_during_annotations
Int
Distance in meter during which the system had good quality sensor data available to observe transport behavior. Value will be -1 when the transport data was not sufficient.
True
CarBehaviorScores
Kind: Object
type
String
'CarBehaviorScores'
True
overall
Float
An aggregation of all scores where we had sufficient data. A low score in one of the scores will result in a lower overall score.
Deprecation notice
overall is deprecated.
Deprecated as it is computed based on the v1 scores.
True
overall_v2
Float
An aggregation of all scores where we had sufficient data. A low score in one of the scores will result in a lower overall score.
True
smooth
Float
The smooth driving score measures how calm you drive. High accelerations and heavy braking result in a lower score, the use of coasting results in a higher score. The higher your score, the calmer you drive! When we do not have sufficient data the value will be -1.
Deprecation notice
smooth is deprecated.
Deprecated in favor of smooth_v2
.
True
legal
Float
The legal driving score measures how well you adhere to speed limits. The higher your score, the more you respect the speed limits! When we do not have sufficient data the value will be -1.
Deprecation notice
legal is deprecated.
Deprecated in favor of legal_v2
.
True
anticipative
Float
The anticipative driving score measures how well you anticipate traffic. A fast sequence of braking and accelerations in general traffic situations results in a lower score, the use of coasting results in a higher score. The higher your score, the more anticipative you drive! When we do not have sufficient data the value will be -1.
Deprecation notice
anticipative is deprecated.
Deprecated in favor of anticipative_v2
.
True
focus
Float
The proportion of time (percentage) the user is focused while driving, being focused means: not using the phone, which is detected through phone handling.
True
mounted
Float
The proportion of time (percentage) the phone is mounted while driving.
True
hard_accel
Float
Measures how often you accelerate hard. Every hard acceleration will be penalised by subtracting a percentage of your score. When we do not have sufficient data this value will be -1.
True
hard_brake
Float
Measures how often you need to brake hard. Every hard brake will be penalised by subtracting a percentage of your score. When we do not have sufficient data this value will be -1.
True
hard_events
Float
This is a combination of hard_accel and hard_brake score. The hard brakes and accelerations are also normalized by the total number of events. When we do not have sufficient data this value will be -1.
True
legal_v2
Float
The legal driving score measures how well you adhere to speed limits. The higher your score, the more you respect the speed limits! When we do not have sufficient data the value will be -1.
True
hard_turn
Float
Measures how often you turn hard. Every hard turn will be penalised by subtracting a percentage of your score. When we do not have sufficient data this value will be -1.
True
smooth_v2
Float
The smooth driving score measures how smooth you drive. High accelerations, heavy braking and heavy turning result in a lower score. Scores are normalized with respect to a wide population. The higher your score, the smoother you drive! When we do not have sufficient sensor data characterizing your drive, the value will be -1. Beside an updated normalization, the difference with smooth score v1 is that turns are also taken in account.
True
anticipative_v2
Float
The anticipative driving score measures how well you anticipate turns. Hard accelerations before or hard braking during a turn result in a lower score. The higher your score, the more anticipative you drive! When we do not have sufficient sensor data characterizing your drive, the value will be -1. Beside an updated normalization, this new version has a more accurate detection of brakes in turns.
True
handheld_calling
Float
A score based on how much time you spent using your phone and calling (1 means good behavior).
True
handheld_calling_duration
Int
Total time in seconds the user was calling while holding the phone during the transport.
True
handsfree_calling
Float
A score based on how much time you spent calling without holding your phone (1 means good behavior).
True
handsfree_calling_duration
Int
Total time in seconds the user was calling handsfree during the transport.
True
handling_without_calling
Float
A score based on how much time you spent holding your phone without calling (assume typing, texting etc.)
True
handling_without_calling_duration
Int
Total time in seconds the user held the phone without calling (assume typing, texting etc.) during the transport.
True
attention
Float
A combined score of handheld_calling, handsfree_calling and handling_without_calling.
True
CityMoment
Kind: Object
Implements: IMoment An occurrence of a City moment that we have detected for a user.
type
'CityMoment'
True
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
True
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
True
start_ts
True
end_ts
True
analysis_type
How well this moment is analyzed by the platform, this value will update over time.
Possible values:
preliminary, indepth, processed.
Deprecation notice
analysis_type is deprecated.
After significantly improving our platform's real-timeliness, we now don't need the analysis of a trip to go through multiple phases. This means you no longer need to filter our Firehose or API output by AnalysisType. Previously, trips had three analysis types based on processing latency. They were, namely, 'processed,' 'indepth,' and 'preliminary.' Based on your use cases, you may have filtered out certain types. As we will deprecate this field on Dec 10, 2021, you will need to change your backend if you use the AnalysisType field.
True
moment_definition_id
String
The ID of the MomentDefinition this moment relates to.
True
moment_definition
The MomentDefinition this moment relates to.
True
city_name
String
The name of the city this moment applies to.
True
CommuteTimeAggregate
Kind: Object
Implements: ITimeAggregateAttribute, IUserAttribute
type
'CommuteTimeAggregate'
True
period
True
transport_duration
Float
True
mode_category
True
ControlUser
Kind: Object
Implements: IUser A user that can authenticate using either password or token strategies, has an email address, might have access to dashboards, might have multiple roles, might manage multiple accounts and applications.
type
'ControlUser'
True
String
The email address that is optionally linked to provide access to the https://developers.sentiance.com and others.
True
account_roles
The accounts this user has elevated permissions to.
True
id
String
The unique identifier for this user.
True
can_login
Boolean
True
created_at
String
The time when this user was created, ISO8601. Example: 2015-05-28T14:37:14.839+00:00
True
sdk
True
application_id
String
The ID of the Application this user relates to.
True
application
The Application this user relates to.
True
custom_event_history
Custom Event History
True
event_history
An unordered list of events we have detected for this user.
True
car_behavior
The user car behavior aggregated over the last 9 weeks.
True
aggregated_driving_scores
True
transport_heatmaps
The aggregated transport heatmaps calculated over time.
Deprecation notice
transport_heatmaps is deprecated.
No longer used.
True
metadata
All custom set metadata properties on this user. This is a JSON object with key->value pairs.
True
device
The last known active tracking device metadata
True
active_moments
An unordered list of moments that are ongoing from the point of view of the platform.
True
moment_history
An unordered list of moments we have detected for this user.
True
semantic_time
The user's semantic time averaged over time.
True
anomaly_history
Deprecation notice
anomaly_history is deprecated.
No longer relevant.
True
segments
An unordered list of segments that are detected for this user.
True
location_clusters
Locations this user has been stationary at and the features we have learned about those locations (significance, point of interest, ...)
True
location
The last known location we have for this user.
True
health
The historical health attributes.
Deprecation notice
health is deprecated.
No longer supported
True
attributes
Deprecation notice
attributes is deprecated.
No longer supported.
True
predictions
Event/Moment predictions for this user
Deprecation notice
predictions is deprecated.
Please use prediction_tree
.
True
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.
True
feedback
Feedback on this user
Deprecation notice
feedback is deprecated.
Replaced by feedback_history
True
feedback_history
Feedback on this user
True
step_count
Step count details of the given user on the given date range. This feature is currently in Beta, for additional information contact support@sentiance.com.
True
CountryMoment
Kind: Object
Implements: IMoment An occurrence of a Country moment that we have detected for a user.
type
'CountryMoment'
True
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
True
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
True
start_ts
True
end_ts
True
analysis_type
How well this moment is analyzed by the platform, this value will update over time.
Possible values:
preliminary, indepth, processed.
Deprecation notice
analysis_type is deprecated.
After significantly improving our platform's real-timeliness, we now don't need the analysis of a trip to go through multiple phases. This means you no longer need to filter our Firehose or API output by AnalysisType. Previously, trips had three analysis types based on processing latency. They were, namely, 'processed,' 'indepth,' and 'preliminary.' Based on your use cases, you may have filtered out certain types. As we will deprecate this field on Dec 10, 2021, you will need to change your backend if you use the AnalysisType field.
True
moment_definition_id
String
The ID of the MomentDefinition this moment relates to.
True
moment_definition
The MomentDefinition this moment relates to.
True
country_name
String
The name of the country this moment applies to.
True
Crash
Kind: Object
An occurrence of a Crash that we have detected for a user.
max_magnitude
Int
Peak magnitude in m/s^2 multiplied by 100 (e.g. a value of 150 is actually 1.5 m/s^2).
True
timestamp
String
The time the crash happened, in ISO8601 format. Value can change and become more accurate over time. Example: 2015-05-28T14:37:14.839+00:00
False
confidence
Int
(0-100) confidence level that the crash is a true positive.
True
speed_at_impact
Int
Estimated speed in which the vehicle was travelling before the impact in m/s multiplied by a 100 (e.g., a value of 750 is actually 7.50 m/s.
True
delta_v
Int
Estimated change in velocity at impact in m/s multiplied by a 100. This is estimated from the acceleration signal.
True
waypoint
To be filled
True
on_device_ml_model
Name of the models that were used to detect the crash. Mainly used as internal reference.
True
CrashAnnotation
Kind: Object
Implements: ITransportBehaviorAnnotation
type
'CrashAnnotation'
True
start
String
Time when the crash started, formatted as an ISO 8601 datetime.
False
end
String
Time when the crash ended, formatted as an ISO 8601 datetime.
True
event_id
String
ID of the transport event during which the crash occurred.
True
latitude
Float
Latitude of the location where the crash occurred.
True
longitude
Float
Longitude of the location where the crash occurred.
True
max_magnitude
Float
Magnitude of maximum acceleration detected at the moment of the crash in Gs.
True
confidence
Int
Confidence level that the crash is a true positive.
True
speed_at_impact
Float
Speed of the vehicle at the moment of impact in km/h.
True
delta_v
Float
Change in velocity of the vehicle at the moment of impact in km/h.
True
crash_event_origin
Origin of the crash event.
True
CrashEventOriginEnum
Kind: ENUM
NA: The origin is unknown.
AUTOMATICALLY_DETECT: The crash event was automatically detected by the Sentiance SDK.
APP_TEST_EVENT: The crash event was manually generated by the SDK for testing purposes.
MANUALLY_REQUESTED: The crash event was manually requested and generated by the client.
CrashFeedback
Kind: Object
Implements: IFeedback
type
'CrashFeedback'
True
start
String
Start time the feedback relates to, sourced by the event, moment or user-provided.
False
end
String
End time the feedback relates to, sourced by the event, moment or user-provided.
True
created
String
Time when this feedback entry was created.
True
projection_time
String
Time to provide when the feedback data was read from the API. ISO8601. Optional.
True
crash_feedback
True
crash
The Crash this feedback refers to.
True
CrashFeedbackConfirmation
Kind: ENUM
NoCrash: No crash
LowImpactNoAssistance: Low impact crash and no assistance required.
LowImpactVehicleTowed: Low impact crash but the vehicle had to be towed.
HighImpactEmergencyAssistance: High impact crash that required ambulance/police assistance.
CrashFeedbackFeedback
Kind: Object
feedback_type_of_crash
This field represents feedback about the type of the crash.
True
feedback_airbag_deployed
Boolean
This field represents feedback to confirm if the airbag was deployed during the crash.
True
feedback_car_driveable
Boolean
This field represents feedback to confirm if the vehicle was driveable after the crash.
True
feedback_confirmation
This field represents feedback to confirm if a crash happened.
True
CrashFeedbackType
Kind: ENUM
CollisionWithAnimal: Collision with animal
CollisionWithPedestrian: Collision with pedestrian
CollisionWithNonMotorizedVehicle: Collision with non-motorized vehicle
CollisionWithObject: Collision with an object
CollisionWithVehicle: Collision with a vehicle
WindshieldGlassDamaged: Windshield/glass damaged
Others: Others
CustomEvent
Kind: Object
Custom Events.
id
String
The ID of the event in the Sentiance system. This is unique across all custom events
True
created_at
String
The time this event was created ISO8601.
True
created_at_ts
True
type
String
'CustomEvent'
True
start
String
The time this event started, ISO8601.
True
end
String
The time this event ended, ISO8601. Value can be null when it is a one time event.
True
start_ts
True
end_ts
True
source
Where the event originates.
True
event_id
String
True
latitude
Float
Latitude value of the event.
True
longitude
Float
Longitude value of the event.
True
values
JSON string of key,value pairs submitted during event creation.
True
CustomEventSources
Kind: ENUM
SDK: Event was generated in the SDK.
ENCLOSING_APP: The enclosing application was generating the event through the SDK.
CUSTOMER: The event was sent by the Customer. Where the custom event originates at.
DayCountAnomaly
Kind: Object
Implements: IAnomaly, IDayCountAnomaly, IAggregatedAnomaly, IStationaryAnomaly, ITransportAnomaly, IMomentAnomaly
type
'DayCountAnomaly'
True
start
String
True
end
String
True
analysis_type
Deprecation notice
analysis_type is deprecated.
After significantly improving our platform's real-timeliness, we now don't need the analysis of a trip to go through multiple phases. This means you no longer need to filter our Firehose or API output by AnalysisType. Previously, trips had three analysis types based on processing latency. They were, namely, 'processed,' 'indepth,' and 'preliminary.' Based on your use cases, you may have filtered out certain types. As we will deprecate this field on Dec 10, 2021, you will need to change your backend if you use the AnalysisType field.
True
anomaly
True
sigma
Float
The observed standard deviation from expected behavior for this anomaly. If the standard deviation is high, the anomaly confidence will be low.
True
probability
Float
The larger the probability, the more anomaly. Value is between 0.0 and 1.0.
True
period
Aggregation period over which the data is calculated.
True
day_part
Optional additional aggregation over which the data is calculated.
True
observed_days
Float
Observed amount of days.
True
expected_days
Float
Expected amount of days.
True
place_category
String
True
location_significance
True
transport_mode
True
transport_mode_category
True
moment_definition_id
String
True
DayPart
Kind: ENUM
morning: Local time between 06:00-10:00.
noon: Local time between 10:00-14:00.
afternoon: Local time between 14:00-17:00.
evening: Local time between 17:00-24:00.
night: Local time between 00:00-06:00.
business: Business hours, local time between 08:00-18:00.
non_business: Non-business hours, local time excluding 08:00 - 18:00. Grouping of local time.
DeviceInfo
Kind: Object
Tracking device metadata.
type
String
'DeviceInfo'
True
os
The operating system this device is running.
True
os_version
String
The version of the operating system this device is running.
True
DistanceAnomaly
Kind: Object
Implements: IAnomaly, IDistanceAnomaly, IStationaryAnomaly, ITransportAnomaly, IMomentAnomaly
type
'DistanceAnomaly'
True
start
String
True
end
String
True
analysis_type
Deprecation notice
analysis_type is deprecated.
After significantly improving our platform's real-timeliness, we now don't need the analysis of a trip to go through multiple phases. This means you no longer need to filter our Firehose or API output by AnalysisType. Previously, trips had three analysis types based on processing latency. They were, namely, 'processed,' 'indepth,' and 'preliminary.' Based on your use cases, you may have filtered out certain types. As we will deprecate this field on Dec 10, 2021, you will need to change your backend if you use the AnalysisType field.
True
anomaly
True
sigma
Float
The observed standard deviation from expected behavior for this anomaly. If the standard deviation is high, the anomaly confidence will be low.
True
probability
Float
The larger the probability, the more anomaly. Value is between 0.0 and 1.0.
True
observed_distance
Float
Observed distance in meter.
True
expected_distance
Float
Expected distance in meter.
True
place_category
String
True
location_significance
True
transport_mode
True
transport_mode_category
True
moment_definition_id
String
True
DurationAnomaly
Kind: Object
Implements: IAnomaly, IDurationAnomaly, IStationaryAnomaly, ITransportAnomaly, IMomentAnomaly
type
'DurationAnomaly'
True
start
String
True
end
String
True
analysis_type
Deprecation notice
analysis_type is deprecated.
After significantly improving our platform's real-timeliness, we now don't need the analysis of a trip to go through multiple phases. This means you no longer need to filter our Firehose or API output by AnalysisType. Previously, trips had three analysis types based on processing latency. They were, namely, 'processed,' 'indepth,' and 'preliminary.' Based on your use cases, you may have filtered out certain types. As we will deprecate this field on Dec 10, 2021, you will need to change your backend if you use the AnalysisType field.
True
anomaly
True
sigma
Float
The observed standard deviation from expected behavior for this anomaly. If the standard deviation is high, the anomaly confidence will be low.
True
probability
Float
The larger the probability, the more anomaly. Value is between 0.0 and 1.0.
True
observed_duration
Float
Observed duration in seconds.
True
expected_duration
Float
Expected duration in seconds.
True
place_category
String
True
location_significance
True
transport_mode
True
transport_mode_category
True
moment_definition_id
String
True
EventFeedback
Kind: Object
type_assessment
If the user thinks the detected type is correct.
True
place_assessment
If the user thinks the detected place is correct.
True
place_feedback
The place candidate that was selected by the user as a better match, if any.
True
significance_assessment
If the user thinks the detected location significance is correct.
True
significance_feedback
The location significance that was selected by the user as a better match, if any.
True
mode_assessment
What the user thinks about the transport mode.
True
mode_feedback
The transport mode that was selected by the user as a better match, if any.
True
occupant_role_feedback
The occupant role that was selected by the user as a better match, if any.
True
EventType
Kind: ENUM
Transport
Stationary
FeedbackAssessment
Kind: ENUM
correct: When the user confirms the detection is correct.
incorrect: When the user finds the detection not correct.
FeedbackType
Kind: ENUM
StationaryFeedback: Feedback on a detected Stationary event.
TransportFeedback: Feedback on a detected Transport event.
MomentFeedback: Feedback on a detected moment.
CrashFeedback: Feedback on a detected crash.
FloatAttribute
Kind: Object
A float attribute
type
String
'FloatAttribute'
True
value
Float
True
GenericMoment
Kind: Object
Implements: IMoment An occurrence of a moment that we have detected for a user.
type
'GenericMoment'
True
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
True
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
True
start_ts
True
end_ts
True
analysis_type
How well this moment is analyzed by the platform, this value will update over time.
Possible values:
preliminary, indepth, processed.
Deprecation notice
analysis_type is deprecated.
After significantly improving our platform's real-timeliness, we now don't need the analysis of a trip to go through multiple phases. This means you no longer need to filter our Firehose or API output by AnalysisType. Previously, trips had three analysis types based on processing latency. They were, namely, 'processed,' 'indepth,' and 'preliminary.' Based on your use cases, you may have filtered out certain types. As we will deprecate this field on Dec 10, 2021, you will need to change your backend if you use the AnalysisType field.
True
moment_definition_id
String
The ID of the MomentDefinition this moment relates to.
True
moment_definition
The MomentDefinition this moment relates to.
True
GenericSegment
Kind: Object
Implements: ISegment An occurrence of a SegmentDefinition that we have detected for this user.
type
'GenericSegment'
True
segment_definition_id
String
The ID of the SegmentDefinition this segment relates to.
True
explanation
String
Reasoning why this segment was assigned to this user from a third person point of view.
Deprecation notice
explanation is deprecated.
No longer valid, clients will need to handle with their own explanation.
True
explanation_you
String
Reasoning why this segment was assigned to this from a second person point of view.
Deprecation notice
explanation_you is deprecated.
No longer valid, clients will need to handle with their own explanation_you.
True
segment_definition
The SegmentDefinition this segment relates to.
True
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