Automotive & ADAS
Vehicle Sensor Suite
Modern vehicles contain 100+ sensors working in concert. Advanced Driver Assistance Systems (ADAS) rely on multiple sensor modalities to perceive the driving environment and make safety-critical decisions in real time.
ADAS Sensor Technologies
| Sensor | Range | Strengths | Limitations |
|---|---|---|---|
| Camera | 10–250m | Lane detection, sign recognition, color | Poor in rain/fog/night |
| Radar (77 GHz) | 0.5–250m | Velocity, all-weather, long range | Low angular resolution |
| LiDAR | 1–200m | 3D point cloud, high resolution | Expensive, rain interference |
| Ultrasonic | 0.2–5m | Low cost, parking assist | Short range, slow |
| IMU (6-DOF) | N/A | Vehicle dynamics, orientation | Drift over time |
| GPS/GNSS | Global | Position, RTK cm-accuracy | No indoor, multipath |
ADAS Features
Common ADAS Applications:
- Adaptive Cruise Control (ACC): Radar + camera → throttle/brake actuators. Maintains safe following distance
- Lane Keep Assist (LKA): Camera → EPS motor (electric power steering). Corrects steering if drifting
- Automatic Emergency Braking (AEB): Radar + camera + LiDAR → brake actuator. Sub-100ms response time
- Blind Spot Detection: Rear radar sensors → visual/haptic warning
- Parking Assist: 8–12 ultrasonic sensors → steering + throttle + brake actuators
ADAS Sensor Fusion Architecture
flowchart LR
subgraph Sensors["Sensor Array"]
CAM["📷 Camera"]
RAD["📡 Radar"]
LID["🔴 LiDAR"]
ULT["🔊 Ultrasonic"]
IMU["📐 IMU"]
GPS["🛰️ GPS"]
end
subgraph Fusion["Perception Layer"]
SF["Sensor Fusion
& Object Detection"]
end
subgraph Features["ADAS Features"]
ACC["Adaptive
Cruise Control"]
LKA["Lane Keep
Assist"]
AEB["Emergency
Braking"]
PA["Parking
Assist"]
end
subgraph Act["Actuators"]
TH["Throttle"]
ST["Steering"]
BR["Brakes"]
end
Sensors --> Fusion --> Features --> Act
style SF fill:#3B9797,stroke:#3B9797,color:#fff
style AEB fill:#fff5f5,stroke:#BF092F,color:#132440
Healthcare & Wearables
Vital Signs Monitoring
Wearable Health Sensors
| Measurement | Sensor Technology | Typical IC | Accuracy |
|---|---|---|---|
| Heart Rate | PPG (photoplethysmography) | MAX30102 | ±2 BPM |
| SpO2 | Dual-wavelength PPG (red + IR) | MAX30102 | ±2% |
| ECG | Biopotential electrodes | AD8232, MAX30003 | Clinical grade |
| Temperature | IR thermopile / NTC | MLX90614 | ±0.1°C |
| Activity / Steps | 3-axis accelerometer | LIS3DH, ADXL362 | ±5% step count |
| Blood Pressure | Oscillometric + PPG | Custom ASIC | ±5 mmHg |
Medical Devices
Medical-Grade Requirements:
- Regulatory: FDA 510(k) / CE marking / IEC 60601 (medical electrical safety)
- EMC: IEC 60601-1-2 electromagnetic compatibility testing
- Patient Safety: Leakage current < 10 µA, electrical isolation via optocouplers
- Reliability: MTBF > 50,000 hours, self-test on startup
- Data Security: AES-256 encryption, HIPAA compliance for data transmission
Industrial Automation
PLC & SCADA
Programmable Logic Controllers (PLCs) are the backbone of factory automation. They read sensor inputs (temperature, pressure, flow, position), execute ladder logic or structured text programs, and drive actuators (motors, valves, conveyors) through standardized I/O modules.
Industrial Sensor Interfaces
| Signal Type | Range | Application |
|---|---|---|
| 4–20 mA | Current loop, 2-wire | Pressure, temperature, flow transmitters |
| 0–10 V | Voltage analog | Valve position, speed reference |
| Pt100 / Pt1000 | RTD resistance | Precision temperature |
| Thermocouple | Type J, K, T, S | High-temperature furnace/oven |
| 24V Digital | NPN/PNP sinking/sourcing | Limit switches, proximity sensors |
| Encoder (differential) | RS-422 / HTL / TTL | Motor speed, position feedback |
Industrial Robotics
Industrial Robot Sensor Integration:
- Joint Encoders: Absolute encoders on each axis for position feedback (17-bit+)
- Force/Torque Sensors: 6-axis F/T at the end-effector for assembly, polishing, and collaborative robots
- Vision Systems: 2D/3D cameras for pick-and-place, quality inspection, bin picking
- Safety: Light curtains, safety mats, laser scanners (SIL 3, Category 3/4)
- Communication: EtherCAT, PROFINET, EtherNet/IP for real-time control (1 ms cycle)
Consumer Electronics
Smartphone Sensor Array
| Sensor | Purpose | Typical IC |
|---|---|---|
| Accelerometer | Screen rotation, step counting, shake detection | BMI270, LIS2DW12 |
| Gyroscope | Gaming, image stabilization, navigation | BMI270 (combo) |
| Magnetometer | Compass, metal detection | LIS3MDL, AK09918 |
| Proximity | Screen off during calls | TMD2725, VL53L1X |
| Ambient Light | Auto brightness | TSL2591, APDS-9960 |
| Barometer | Altitude, floor detection | BMP390, LPS22HH |
| Fingerprint | Biometric authentication | Capacitive / optical / ultrasonic |
| Haptic Motor | Vibration feedback | LRA + DRV2605L driver |
Aerospace & Drones
Drone Flight Controller Sensors:
- IMU (6/9-DOF): Accelerometer + gyroscope + magnetometer for attitude estimation (Madgwick/Mahony filter)
- Barometer: Altitude hold (BMP388, ±0.5m resolution with digital filtering)
- GPS/GNSS: Position hold, waypoint navigation, return-to-home (u-blox M8/M10, 10 Hz update)
- Optical Flow: Downward-facing camera + sonar for indoor position hold without GPS
- LiDAR/Sonar: Altitude ranging for precision landing and terrain following
- ESC Telemetry: Motor RPM, current, temperature via DSHOT/BLHeli telemetry
- Actuators: 4–8 brushless motors via ESCs, gimbal servos, payload release mechanisms
Conclusion & Next Steps
Every industry applies the same sensor-actuator principles but with domain-specific constraints: automotive demands functional safety (ISO 26262), healthcare requires biocompatibility and regulatory approval, industrial needs harsh-environment ratings, and aerospace requires weight optimization and redundancy.
Key Takeaways:
- ADAS fuses multiple sensor modalities (camera + radar + LiDAR) for reliable perception
- Healthcare wearables face strict regulatory requirements (FDA, IEC 60601)
- Industrial automation uses standardized signal interfaces (4–20 mA, 0–10V, PNP/NPN)
- Smartphones pack 10+ sensors into a single handheld device
- Drone flight controllers integrate IMU + barometer + GPS with sensor fusion algorithms
In Part 9, we dive into Advanced Topics — sensor fusion algorithms, Kalman filters, TinyML on microcontrollers, power optimization, and fault tolerance.