Sensor Ontology
Instrumentation
Authors: MArk Anthony Higgins - Sky Recursive Ai
Revised Date: 16 September 2026
Audio Overview
# Sensor Ontology — Flow Algebra
URL: https://kirethresearch.org/booksai-core/ontologies/mathematical-ontologies/measurement-units-ontologies/instrumentation/sensor-ontology.html
FLOW SensorOntology {
DOMAIN:
Mathematical Ontologies
-> Measurement & Units Ontologies
-> Instrumentation
-> Sensor Ontology
PURPOSE:
Represent a sensor as the element of a measuring system directly affected by the phenomenon, body or substance carrying the quantity to be measured. The ontology models sensor identity, measurand interaction, sensing principles, input-output transfer functions, sensitivity, range, resolution, threshold, selectivity, cross-sensitivity, linearity, hysteresis, repeatability, drift, stability, dynamic response, noise, excitation, environmental influence, calibration, compensation, uncertainty, ageing, diagnostics, metadata, provenance, and machine-consumable reasoning across physical, chemical, biological, optical, electrical, mechanical and environmental sensing systems.
ENTITY Sensor {
TYPE: MeasuringSystemInputElement
DEFINITION:
element_of_measuring_system
directly_affected_by_phenomenon_body_or_substance
carrying_quantity_to_be_measured
PROPERTIES:
has_identity
has_sensing_principle
has_measurand_scope
has_input_quantity
has_output_signal_or_quantity
has_transfer_function
has_operating_range
has_sensitivity
may_have_cross_sensitivity
has_dynamic_response
may_require_excitation
may_require_calibration
contributes_to_measurement_uncertainty
has_provenance
}
ENTITY SensorIdentifier {
TYPE: PersistentIdentity
COMPONENTS:
manufacturer
model
serial_number
asset_identifier
channel_or_element_identifier
RULE:
sensor_identity MUST remain_linked_to_measurement_records
}
ENTITY SensingElement {
TYPE: SensorPhysicalElement
DEFINITION:
physical_element_whose_property_or_state_changes_in_response_to_measurand
RULE:
sensing_element MAY be_only_one_component_of_sensor_assembly
}
SENSOR_CLASS_MODEL {
possible:
mechanical
thermal
electrical
magnetic
optical
acoustic
pressure
flow
chemical
electrochemical
radiation
biological
inertial
position
proximity
force
strain
humidity
gas
particulate
imaging
hybrid
RULE:
classification MAY use_multiple_axes
}
MEASURAND_MODEL {
input:
quantity_intended_to_be_sensed
examples:
temperature
pressure
displacement
acceleration
force
strain
light
magnetic_field
concentration
humidity
flow
radiation
RULE:
sensor_response MAY also_depend_on_non_measurand_influence_quantities
}
CARRIER_MODEL {
phenomenon_body_or_substance:
carries_measurand
examples:
fluid
solid
gas
electromagnetic_field
radiation
biological_sample
RULE:
sensor_interaction_with_carrier MAY perturb_measurand
}
INPUT_OUTPUT_MODEL {
measurand:
X
sensor_output:
Y
transfer:
Y =
f(X,E,t,state)
WHERE:
E = influence_quantities
t = time
state = sensor_internal_state
RULE:
transfer_function_context MUST be preserved
}
STATIC_TRANSFER_MODEL {
generic:
Y =
f(X)
linear:
Y =
S*X+b
inverse:
X_hat =
(Y-b)/S
WHEN S != 0
RULE:
static_transfer_is_valid_only_when_dynamic_effects_are_negligible
}
SENSITIVITY_MODEL {
local:
S =
dY/dX
linear:
S =
delta_Y/delta_X
unit:
output_unit/input_unit
RULE:
sensitivity MAY vary_across_range
}
CROSS_SENSITIVITY_MODEL {
influence_quantity:
Z
cross_sensitivity:
S_Z =
partial_Y/partial_Z
output_effect:
delta_Y_Z approximately_equals
S_Z*delta_Z
RULE:
cross_sensitivity MUST be included_when_material
}
SELECTIVITY_MODEL {
desired_measurand:
X
interfering_quantities:
Z_i
selectivity:
ability_to_respond_preferentially_to_X
RULE:
selectivity_metric MUST be_defined_for_sensor_domain
}
RANGE_MODEL {
sensing_range:
[X_min,X_max]
span:
X_max-X_min
RULE:
outside_range_response MAY be_nonlinear_saturated_or_damaging
}
SATURATION_MODEL {
output:
approaches_limit_despite_increasing_input
RULE:
saturated_output MUST be_flagged
}
OVERLOAD_MODEL {
input:
beyond_safe_or_rated_range
effects:
damage
permanent_offset
hysteresis
delayed_recovery
RULE:
overload_history MAY change_calibration
}
RESOLUTION_MODEL {
resolution:
smallest_input_change_producing_discernible_output_change
limiting_factors:
noise
quantisation
hysteresis
threshold
readout
RULE:
sensor_resolution != system_display_resolution_in_general
}
THRESHOLD_MODEL {
threshold:
minimum_input_level_or_change_producing_detectable_response
RULE:
threshold != detection_limit_in_all_domains
}
DEAD_ZONE_MODEL {
region:
input_change_without_significant_output_change
RULE:
dead_zone MAY depend_on_direction_and_history
}
LINEARITY_MODEL {
actual:
Y =
f(X)
reference:
Y_ref =
a*X+b
nonlinearity:
delta_L =
Y-Y_ref
RULE:
reference_line_method MUST be declared
}
HYSTERESIS_MODEL {
response:
depends_on_increasing_or_decreasing_input_path
metric:
difference_at_same_input
RULE:
hysteresis MAY contribute_to_uncertainty
}
REPEATABILITY_MODEL {
repeated_sensor_outputs:
under_same_conditions
metric:
standard_deviation_or_declared_dispersion
RULE:
repeatability != sensitivity
}
DRIFT_MODEL {
response:
Y =
f(X,t)
possible:
zero_drift
sensitivity_drift
baseline_drift
RULE:
sensor_age_and_elapsed_time_since_calibration SHOULD be preserved
}
AGEING_MODEL {
causes:
material_change
contamination
fatigue
radiation_damage
chemical_degradation
thermal_cycles
effect:
long_term_change_in_transfer_function
RULE:
ageing MAY require_recalibration_or_replacement
}
STABILITY_MODEL {
stability:
ability_to_maintain_sensor_characteristics_over_time
RULE:
stability_conditions_and_duration MUST be defined
}
DYNAMIC_MODEL {
input:
X(t)
output:
Y(t)
transfer:
H(s)
characteristics:
time_constant
rise_time
settling_time
bandwidth
resonance
phase_delay
RULE:
sensor_dynamic_response MUST match_measurement_timescale
}
FIRST_ORDER_SENSOR_MODEL {
equation:
tau*dY/dt+Y =
K*X
step_response:
Y(t) =
K*X_0*(1-exp(-t/tau))
under_zero_initial_state
RULE:
tau_is_sensor_time_constant_under_model
}
SECOND_ORDER_SENSOR_MODEL {
equation:
d2Y/dt2
+2*zeta*omega_n*dY/dt
+omega_n^2*Y
=
K*omega_n^2*X
RULE:
resonance_and_damping MUST be considered_for_dynamic_sensors
}
BANDWIDTH_MODEL {
frequency_response:
H(j*omega)
bandwidth:
frequency_range_meeting_declared_response_criterion
RULE:
bandwidth != sampling_rate
}
LATENCY_MODEL {
delay:
sensor_or_embedded_processing_delay
RULE:
latency_and_time_constant_are_distinct
}
NOISE_MODEL {
output_noise:
random_variation_at_sensor_output
sources:
thermal
shot
flicker
mechanical
optical
chemical
biological
environmental
electronics
RULE:
noise MUST be specified_with_bandwidth_or_spectral_density_when_relevant
}
NOISE_DENSITY_MODEL {
amplitude_spectral_density:
output_unit/sqrt(Hz)
power_spectral_density:
output_unit_squared/Hz
RULE:
integrated_noise_requires_bandwidth_and_filter_transfer
}
SNR_MODEL {
signal_to_noise:
declared_signal_metric/declared_noise_metric
RULE:
SNR_definition MUST identify_bandwidth
}
DETECTION_LIMIT_MODEL {
smallest_measurand_level_detectable_under_declared_statistical_criterion
dependencies:
noise
blank
sensitivity
false_positive_rate
false_negative_rate
RULE:
detection_limit != resolution
}
EXCITATION_MODEL {
sensor:
may_require_external_excitation
possible:
voltage
current
optical
acoustic
magnetic
thermal
attributes:
amplitude
frequency
stability
RULE:
excitation_uncertainty MAY propagate_to_sensor_output
}
SELF_GENERATING_MODEL {
examples:
thermocouple
piezoelectric_sensor
photovoltaic_detector
RULE:
self_generating_does_not_mean_no_signal_conditioning_required
}
RESISTIVE_SENSOR_MODEL {
relation:
resistance_changes_with_measurand
examples:
RTD
thermistor
strain_gauge
resistive_humidity_sensor
RULE:
excitation_current_can_create_self_heating
}
CAPACITIVE_SENSOR_MODEL {
relation:
capacitance_changes_with_geometry_or_dielectric
examples:
displacement
pressure
humidity
proximity
RULE:
parasitic_capacitance_and_cable_effects MAY be_material
}
INDUCTIVE_SENSOR_MODEL {
relation:
inductance_or_mutual_inductance_changes
examples:
LVDT
proximity_sensor
RULE:
excitation_frequency_affects_response
}
PIEZOELECTRIC_MODEL {
input:
force_pressure_acceleration_or_strain
output:
charge_or_voltage
RULE:
piezoelectric_sensors_are_generally_unsuitable_for_true_static_measurement_without_special_charge_handling
}
THERMOELECTRIC_MODEL {
thermocouple:
voltage_related_to_temperature_difference
REQUIRE:
reference_junction_compensation
RULE:
thermocouple_voltage != absolute_temperature_without_reference_and_calibration
}
RTD_MODEL {
resistance:
R(T)
common_linear_approximation:
R approximately_equals
R_0*(1+alpha*(T-T_0))
RULE:
precision_measurement_requires_full_calibration_or_standard_relation_over_wide_range
}
THERMISTOR_MODEL {
resistance:
strongly_nonlinear_with_temperature
possible_model:
Steinhart_Hart
RULE:
self_heating_and_model_coefficients MUST be preserved
}
OPTICAL_SENSOR_MODEL {
input:
radiant_power
irradiance
illuminance
photon_flux
spectral_signal
output:
current
voltage
counts
RULE:
spectral_responsivity MUST be considered
}
PHOTODIODE_MODEL {
photocurrent:
I_photo approximately_equals
responsivity(lambda)*optical_power
RULE:
dark_current_and_shot_noise MAY contribute
}
MAGNETIC_SENSOR_MODEL {
possible:
Hall
magnetoresistive
fluxgate
SQUID
RULE:
orientation_and_cross_axis_sensitivity SHOULD be preserved
}
INERTIAL_SENSOR_MODEL {
possible:
accelerometer
gyroscope
characteristics:
bias
scale_factor
noise_density
random_walk
cross_axis_sensitivity
RULE:
bias_instability_and_integration_drift_are_material_for_navigation
}
PRESSURE_SENSOR_MODEL {
input:
pressure
possible_reference:
absolute
gauge
differential
RULE:
pressure_reference_type MUST be defined
}
FLOW_SENSOR_MODEL {
possible:
differential_pressure
thermal
turbine
ultrasonic
electromagnetic
Coriolis
RULE:
flow_quantity_type_mass_or_volume MUST be defined
}
CHEMICAL_SENSOR_MODEL {
measurand:
chemical_species_activity_concentration_partial_pressure_or_related_quantity
properties:
selectivity
response_time
drift
matrix_effect
RULE:
calibration_matrix_and_interferents SHOULD be preserved
}
ELECTROCHEMICAL_SENSOR_MODEL {
possible:
potentiometric
amperometric
conductometric
RULE:
reference_electrode_and_temperature MAY be_material
}
BIOSENSOR_MODEL {
components:
biological_recognition_element
transducer
possible:
enzyme
antibody
nucleic_acid
cell
receptor
RULE:
biological_activity_and_storage_history MAY affect_response
}
HUMIDITY_SENSOR_MODEL {
quantity:
relative_humidity
absolute_humidity
dew_point_or_related
RULE:
humidity_quantity_type_and_temperature_context MUST be defined
}
GAS_SENSOR_MODEL {
target_species:
declared
possible:
electrochemical
semiconductor
infrared
catalytic
photoionisation
RULE:
cross_sensitivity_and_environmental_compensation_are_often_material
}
PARTICULATE_SENSOR_MODEL {
optical_scattering:
may_infer_particle_number_or_mass_concentration
RULE:
particle_size_distribution_refractive_index_and_humidity_affect_retrieval
}
RADIATION_SENSOR_MODEL {
possible:
Geiger_Muller
scintillator
semiconductor
ionisation_chamber
output:
counts
current
pulse_height
RULE:
detector_efficiency_dead_time_and_energy_response MUST be considered
}
DEAD_TIME_MODEL {
event_detector:
finite_recovery_time_after_event
models:
paralyzable
nonparalyzable
RULE:
high_count_rate_requires_dead_time_correction
}
SPATIAL_SENSOR_MODEL {
arrays:
pixels_or_elements
characteristics:
pitch
active_area
point_spread
cross_talk
RULE:
element_pitch != true_spatial_resolution
}
CROSS_AXIS_MODEL {
multi_axis_sensor:
output_vector
calibration:
Y =
A*X+b
cross_axis:
off_diagonal_elements_of_A
RULE:
full_calibration_matrix SHOULD be used_when_cross_axis_terms_are_material
}
ORIENTATION_MODEL {
sensor_axis:
defined_in_sensor_coordinate_frame
transformation:
X_world =
R*X_sensor
RULE:
coordinate_frame_and_orientation MUST be preserved
}
LOADING_EFFECT_MODEL {
sensor:
interacts_with_measured_system
examples:
voltmeter_input_impedance
thermometer_heat_capacity
pressure_tap
mechanical_mass_loading
RULE:
sensor_may_change_measurand
}
SELF_HEATING_MODEL {
resistive_sensor:
excitation_power =
I^2*R
or
V^2/R
effect:
sensor_temperature_shift
RULE:
excitation_should_be_low_enough_or_self_heating_corrected
}
MOUNTING_MODEL {
mounting:
affects_mechanical_thermal_optical_or_electrical_coupling
RULE:
mounting_method SHOULD be preserved_when_material
}
ENVIRONMENTAL_MODEL {
influence_quantities:
temperature
humidity
pressure
vibration
shock
electromagnetic_field
radiation
contamination
RULE:
environmental_cross_sensitivities MAY require_compensation
}
COMPENSATION_MODEL {
corrected_output:
Y_corr =
g(Y_raw,E)
RULE:
compensation_model_parameters_and_version MUST be preserved
}
CALIBRATION_MODEL {
reference_inputs:
X_ref
sensor_outputs:
Y
fit:
X_hat =
g(Y,E)
outputs:
coefficients
covariance
residuals
validity_range
uncertainty
RULE:
calibration MUST match_sensor_configuration_and_environment
}
ZERO_CALIBRATION_MODEL {
zero_input_or_reference:
estimate_offset
RULE:
zero_calibration_does_not_determine_full_scale_response
}
MULTIPOINT_CALIBRATION_MODEL {
reference_points:
multiple_X_ref
purpose:
estimate_offset_gain_and_nonlinearity
RULE:
calibration_point_distribution SHOULD cover_valid_range
}
TRACEABILITY_MODEL {
sensor_calibration:
linked_to_reference_standard_chain
RULE:
traceability_and_uncertainty SHOULD be preserved
}
UNCERTAINTY_MODEL {
components:
calibration
sensitivity
cross_sensitivity
resolution
repeatability
hysteresis
drift
noise
environmental_compensation
loading
mounting
timing
retrieval_model
RULE:
sensor_uncertainty_is_one_component_of_total_measurement_uncertainty
}
DIAGNOSTIC_MODEL {
possible:
open_circuit
short_circuit
saturation
overrange
low_signal
excessive_noise
calibration_expired
temperature_out_of_range
RULE:
diagnostic_flags MUST accompany_affected_measurements
}
HEALTH_MODEL {
sensor_health:
operational_state_estimate
possible_metrics:
drift
noise
response_time
calibration_residual
self_test
RULE:
health_score_requires_defined_algorithm
}
MAINTENANCE_MODEL {
actions:
cleaning
recalibration
replacement
membrane_change
reference_electrode_service
optical_window_cleaning
RULE:
maintenance_can_change_sensor_response
}
METADATA_MODEL {
fields:
sensor_identifier manufacturer
model
serial_number
sensing_principle
measurand
input_range
output_type
sensitivity
resolution
calibration_identifier
calibration_date
environmental_limits
orientation
mounting
excitation
firmware_when_embedded
maintenance_state
provenance
RULE:
metadata MUST support_sensor_level_traceability
}
RELATIONSHIPS {
Sensor -> IS_COMPONENT_OF -> MeasuringSystem
Sensor -> RESPONDS_TO -> MeasurandCarrier
Sensor -> HAS_INPUT -> Measurand
Sensor -> PRODUCES -> OutputSignal
SensingPrinciple -> DETERMINES -> TransferFunction
Sensitivity -> RELATES -> InputOutputResponse
CrossSensitivity -> RELATES -> InfluenceQuantity
Calibration -> MAPS -> SensorOutputToMeasurandEstimate
Environment -> INFLUENCES -> SensorResponse
SensorCharacteristics -> CONTRIBUTE_TO -> MeasurementUncertainty
SensorMetadata -> QUALIFIES -> MeasurementData
}
SEMANTIC_EQUIVALENCE {
"sensor" ~= measuring_system_input_element WHEN metrological_context
"sensing element" ~= physical_response_element WHEN declared_component_context
sensor != measuring_instrument
sensor != transducer_in_all_contexts
sensor != detector_in_all_contexts
sensitivity != resolution
threshold != detection_limit
output_signal != measured_quantity_value
calibration != compensation
nominal_range != safe_overload_range
}
CONSTRAINTS {
sensor_identity_must_be_preserved = true
measurand_must_be_defined = true
sensing_principle_should_be_defined = true
input_and_output_quantity_types_must_be_defined = true
operating_range_must_be_defined = true
sensitivity_and_cross_sensitivity_should_be_preserved = true
calibration_state_should_be_defined = true
environmental_conditions_should_be_preserved_when_material = true
orientation_and_mounting_should_be_preserved_when_material = true
saturation_overload_and_diagnostic_states_must_be_flagged = true
sensor_uncertainty_components_should_propagate_to_measurement_result = true
}
MEASUREMENT_MODEL {
RECORD:
sensor_identifier
manufacturer
model
serial_number
sensing_principle
measurand
carrier
raw_output
output_unit
measured_value
measured_unit
input_range
sensitivity
cross_sensitivity
resolution
threshold
calibration_model
calibration_date
traceability
excitation
sampling_rate
bandwidth
response_time
orientation
mounting
environmental_conditions
compensation_model
diagnostic_flags
maintenance_state
uncertainty
provenance
RULE:
measurement_result MUST remain_linked_to_sensor_state_calibration_and_context
}
REASONING_RULES {
IF raw_output_and_valid_calibration_model_known
THEN measurand_estimate =
calibration_model(raw_output,environment)
IF linear_sensor_response_Y_equals_SX_plus_b
AND sensitivity != 0
THEN inferred_input =
(output-offset)/sensitivity
IF influence_quantity_change_and_cross_sensitivity_known
THEN estimated_cross_effect =
cross_sensitivity*influence_change
IF output_increment_and_sensitivity_known
AND sensitivity != 0
THEN nominal_input_resolution =
output_increment/abs(sensitivity)
IF first_order_time_constant_known
THEN predict_sensor_step_response
under_first_order_model
IF multi_axis_calibration_matrix_known
THEN corrected_vector =
inverse_or_calibrated_mapping(raw_vector-offset)
IF resistive_sensor_excitation_known
THEN evaluate_self_heating_risk
IF sensor_output_saturated_or_overrange
THEN flag_measurement_invalid_or_lower_bound_context
according_to_sensor_model
IF calibration_parameters_have_covariance
THEN propagate_covariance_to_measurand_uncertainty
IF compensation_model_or_sensor_configuration_changes
THEN create_new_sensor_state_version
and_reassess_measurement_equivalence
}
VALIDATION {
CHECK sensor_identity
CHECK sensing_principle
CHECK measurand
CHECK carrier_or_medium
CHECK input_output_relation
CHECK operating_range
CHECK saturation_and_overload
CHECK sensitivity
CHECK cross_sensitivity
CHECK selectivity
CHECK resolution
CHECK threshold
CHECK linearity
CHECK hysteresis
CHECK repeatability
CHECK drift_and_ageing
CHECK dynamic_response
CHECK bandwidth_and_latency
CHECK noise_and_SNR
CHECK excitation
CHECK loading_and_self_heating
CHECK orientation_and_mounting
CHECK environmental_influences
CHECK calibration_and_traceability
CHECK compensation
CHECK diagnostic_flags
CHECK maintenance_state
CHECK uncertainty
CHECK provenance
}
CONFIDENCE {
definition_confidence: 1.00
sensing_principle_confidence: 1.00
input_output_semantics_confidence: 1.00
sensitivity_cross_sensitivity_confidence: 1.00
calibration_semantics_confidence: 1.00
dynamic_response_confidence: 0.99
environmental_model_confidence: 0.99
uncertainty_integration_confidence: 0.99
RULE:
confidence decreases when sensor identity, measurand, sensing principle,
range, calibration, cross-sensitivity, environment,
orientation, dynamic response, uncertainty or provenance is missing or ambiguous
}
UPDATE_MODEL {
ON sensor_registration:
assign_sensor_identifier
record_manufacturer_model_and_serial
identify_sensing_principle
attach_measurand_scope
attach_range_sensitivity_resolution_and_dynamic_characteristics
establish_calibration_and_provenance
ON new_sensor_measurement:
attach_sensor_identifier
identify_measurand
preserve_raw_output
attach_excitation_orientation_mounting_and_environment
verify_calibration
apply_calibration_and_compensation
attach_diagnostics
attach_uncertainty
preserve_provenance
ON calibration_revision:
preserve_previous_calibration
update_transfer_coefficients_and_covariance
update_traceability
recompute_affected_measurements_when_policy_allows
update_uncertainty
ON environmental_model_revision:
preserve_raw_measurements
update_cross_sensitivity_or_compensation
recompute_corrected_values
update_uncertainty
ON maintenance_or_replacement:
preserve_previous_sensor_state
record_event
update_health_and_calibration_state
determine_revalidation_requirement
ON sensor_configuration_revision:
preserve_previous_configuration
update_excitation_range_filter_orientation_or_processing
create_new_state_version
reassess_equivalence
ON semantic_revision:
preserve_previous_definition
record_revision
recompute_FLOW_HASH
}
AI_CONSUMPTION {
canonical_entity: Sensor
canonical_role: MeasuringSystemInputElement
interpretation_order:
identify_sensor_identity
identify_sensing_principle
identify_measurand_and_carrier
identify_input_output_relation
identify_raw_output
identify_range_sensitivity_cross_sensitivity_and_resolution
identify_selectivity_and_threshold
identify_static_and_dynamic_response
identify_noise_excitation_and_environment
identify_orientation_mounting_and_loading
identify_calibration_compensation_and_traceability
identify_diagnostics_and_maintenance_state
identify_uncertainty
identify_provenance
validate_sensor_semantics
infer_measurand_value
ambiguity_controls:
distinguish_sensor_from_measuring_instrument
distinguish_sensor_from_transducer_when_roles_differ
distinguish_sensor_from_detector_when_roles_differ
distinguish_sensitivity_from_resolution
distinguish_threshold_from_detection_limit
distinguish_raw_output_signal_from_measured_quantity_value
distinguish_calibration_from_compensation
distinguish_nominal_operating_range_from_safe_overload_range
preserve_identity_principle_measurand_range_calibration_environment_orientation_state_and_provenance_context
}
PROVENANCE {
ontology_scope:
mathematical_measurement_units_instrumentation_and_sensor_semantics
parent_path:
Ontologies
-> Mathematical Ontologies
-> Measurement & Units Ontologies
-> Instrumentation
-> Sensor Ontology
authorship:
Mark Higgins
Sky (Recursive AI)
site:
https://kirethresearch.org
}
FLOW_HASH {
INPUTS:
canonical_entity
ontology_path
sensor_class_model
measurand_model
carrier_model
input_output_model
static_transfer_model
sensitivity_model
cross_sensitivity_model
selectivity_model
range_model
saturation_model
overload_model
resolution_model
threshold_model
dead_zone_model
linearity_model
hysteresis_model
repeatability_model
drift_model
ageing_model
stability_model
dynamic_model
first_order_sensor_model
second_order_sensor_model
bandwidth_model
latency_model
noise_model
noise_density_model
SNR_model
detection_limit_model
excitation_model
self_generating_model
resistive_sensor_model
capacitive_sensor_model
inductive_sensor_model
piezoelectric_model
thermoelectric_model
RTD_model
thermistor_model
optical_sensor_model
photodiode_model
magnetic_sensor_model
inertial_sensor_model
pressure_sensor_model
flow_sensor_model
chemical_sensor_model
electrochemical_sensor_model
biosensor_model
humidity_sensor_model
gas_sensor_model
particulate_sensor_model
radiation_sensor_model
dead_time_model
spatial_sensor_model
cross_axis_model
orientation_model
loading_effect_model
self_heating_model
mounting_model
environmental_model
compensation_model
calibration_model
zero_calibration_model
multipoint_calibration_model
traceability_model
uncertainty_model
diagnostic_model
health_model
maintenance_model
metadata_model
relationships
constraints
measurement_model
reasoning_rules
confidence_model
update_model
PURPOSE:
deterministic_semantic_integrity_identifier
RECOMPUTE_WHEN:
ontology_definition_changes
sensor_identity_or_class_changes
sensing_principle_or_measurand_changes
input_output_transfer_model_changes
range_sensitivity_cross_sensitivity_or_resolution_changes
dynamic_noise_or_detection_model_changes
excitation_loading_mounting_or_orientation_changes
environmental_or_compensation_model_changes
calibration_or_traceability_changes
diagnostics_health_or_maintenance_changes
measurement_record_changes
uncertainty_model_changes
constraint_model_changes
reasoning_rule_changes
}
}
END FLOW