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
Property | Type | Description | Nullable |
---|---|---|---|
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
Property | Type | Description | Nullable |
---|---|---|---|
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.
| 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.
| 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.
| 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.
| 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.
Property | Type | Description | Nullable |
---|---|---|---|
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.
| 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
Property | Type | Description | Nullable |
---|---|---|---|
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.
Property | Type | Description | Nullable |
---|---|---|---|
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.
| 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 |
| 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.
| True | |
attributes |
| True | |
predictions | Event/Moment predictions for this user
| 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
| 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.
Property | Type | Description | Nullable |
---|---|---|---|
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.
| 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.
Property | Type | Description | Nullable |
---|---|---|---|
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
Property | Type | Description | Nullable |
---|---|---|---|
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
Property | Type | Description | Nullable |
---|---|---|---|
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
Property | Type | Description | Nullable |
---|---|---|---|
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.
Property | Type | Description | Nullable |
---|---|---|---|
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
Property | Type | Description | Nullable |
---|---|---|---|
type | 'DayCountAnomaly' | True | |
start | String | True | |
end | String | True | |
analysis_type |
| 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.
Property | Type | Description | Nullable |
---|---|---|---|
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
Property | Type | Description | Nullable |
---|---|---|---|
type | 'DistanceAnomaly' | True | |
start | String | True | |
end | String | True | |
analysis_type |
| 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
Property | Type | Description | Nullable |
---|---|---|---|
type | 'DurationAnomaly' | True | |
start | String | True | |
end | String | True | |
analysis_type |
| 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
Property | Type | Description | Nullable |
---|---|---|---|
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
Property | Type | Description | Nullable |
---|---|---|---|
type | String | 'FloatAttribute' | True |
value | Float | True |
GenericMoment
Kind: Object
Implements: IMoment An occurrence of a moment that we have detected for a user.
Property | Type | Description | Nullable |
---|---|---|---|
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.
| 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.
Property | Type | Description | Nullable |
---|---|---|---|
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.
| True |
explanation_you | String | Reasoning why this segment was assigned to this from a second person point of view.
| True |
segment_definition | The SegmentDefinition this segment relates to. | True |
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