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TRC3500 - Sensor & Artificial Perception

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TRC3500 - Sensors and artificial perception (FULL NOTES) Topics: 1. TRC3500 - Sensors and artificial perception 2. Transfer Functions, Calibration, and Sensor Characteristics 3. Sensing from Resistance and Uncertainty 4. Sensing from Induction and Noise 5. Piezo- and Pyroelectric Effects, Ratiometric Circuits 6. Analog to Digital Conversion and Sampling 7. Capacitance and Perception 8. Digital Signal Processing (DSP) 9. Optical Sensors and 2D Signals 10. Multiplexing and Data Fusion 11. Encoding and Information 12. Exam Format

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TRC3500: Sensors and Artificial Perception


Week 1: Introduction to Sensing and Measurement

Key Concepts:

1. Sensors as Transducers:

o Convert physical phenomena (temperature, pressure, motion) into
electrical signals.

o A sensing module includes all hardware and embedded systems needed
to support the sensor and capture data.

2. Perception as Inference:

o Combines raw data with prior knowledge to construct a model of the
environment.

o Must manage variation and uncertainty to estimate the most likely
interpretation of noisy inputs.

3. Sensing and Transduction:

o Transduction: Conversion of one form of energy (mechanical, thermal)
into another (electrical signals).

o Input Modality: Type of stimulus (light, force, chemical composition).

o Output Modality: Resulting electrical signals (voltage, current).

4. Categories of Sensors:

o Direct Sensors: Produce electrical signals directly from the stimulus
(e.g., photodiode, piezoelectric sensor).

o Hybrid Sensors: Involve intermediate conversion steps (e.g., chemical
sensors generating heat).

o Passive Sensors: Do not require external power (e.g., thermocouples).

o Active Sensors: Require external power (e.g., thermistors).

Measurement and Evidence:

• Measurement Techniques:

o Direct: Explicitly obtain a value (e.g., ruler, thermometer).

, o Indirect: Relate to other measurable variables (e.g., thermistor resistance
converted to temperature).

o Null: Compare unknown quantity to a known reference (e.g., Wheatstone
Bridge).

• Measurement Quality:

o Validity: Measures the correct parameter without confounding variables.

o Reliability: Consistency across repeated trials.

o Accuracy: Closeness to the true value.

o Precision: Consistency of repeated measurements.

o Resolution: Smallest detectable change.

• Errors:

o Theoretical: Model assumptions fail.

o Static: Steady-state inaccuracies (e.g., parallax errors).

o Environmental: External factors (temperature, humidity).

o Dynamic: Sensor response lag.

o Insertion Errors: Device perturbs the system.

Standards in Measurement:

• Hierarchy:

o International Reference Standards (most reliable).

o National Primary Standards.

o Transfer Standards.

o Working Standards (least reliable).

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