23 Sensor Selection: Requirements and Candidate Screening
23.1 Start With the Decision
A sensor shortlist starts with limits for range, error, heat, and power. Write those limits before choosing a part.
23.2 Route Overview
This is part 2 of 2. Review Sensor Selection: Evidence Before Preference for the preceding evidence.
23.3 Learning Objectives
- Test requirements before parts with a concrete scenario and pass criteria.
- Validate references with a concrete scenario and pass criteria.
23.4 Chapter Roadmap
- Requirements Before Parts
- Mandatory Gates First
- Build the Candidate Evidence Matrix
- Incremental Examples
- Weighted Scoring Is a Trade-off Tool
- Keep Gates and Preferences Separate
- Power Review Without False Precision
- Try It Now
- Pick the Non-Negotiable Gate
- Interface and Firmware Checks
- Application Snapshots
- Selection Summary Template
- Practice Checks
- Match Sensor Evidence to Need
- Order Sensor Selection Flow
- Label the Sensor Selection Route
- Knowledge Check: Gates Before Scores
- Knowledge Check: Battery-Life Evidence
- Common Pitfalls
- 1. Selecting From a Feature List
- 2. Scoring Before Rejecting
- 3. Typical Values Are Not Claims
- 4. Ignoring Firmware and Bus Behavior
- 5. Treating Bench Evidence as Optional
- Summary
- References
- See Also
- What’s Next
- Key Takeaway
23.5 Requirements Before Parts
Start with a requirements brief. The brief can be short, but it must be specific enough to reject a candidate.
The next Requirements Before Parts decision depends on the diagram Figure 23.1. Reading PIR sensor against Short range clarifies the practical meaning of A sensor shortlist should start from the measured quantity and interface constraints before comparing individual part numbers.
Start at the measurement question at the top of Figure 23.1, then follow the relevant branch to candidate sensors. The interface check separates analog and digital options before the decision summary combines range, accuracy, and connection needs. Validate the resulting choice against power, cost, and environmental conditions.
23.6 Mandatory Gates First
Use hard gates before scoring. A gate has a pass, fail, or investigate result. Do not assign a numeric score until every gate is resolved.
23.7 Build the Candidate Evidence Matrix
After the gates, compare candidates using rows that matter to the project. Keep the matrix short enough that reviewers can audit it.
23.8 Incremental Examples
23.8.1 Room Temperature/Humidity Node
A classroom comfort sensor needs temperature and humidity updates every few minutes, not pressure or high-rate motion. A BME280 can be a viable candidate if the product also needs barometric pressure; a Sensirion SHT31-DIS-style humidity sensor may be a better-focused candidate when pressure is irrelevant. The first gate is not brand preference. It is whether the sensor’s humidity and temperature ranges, supply/I/O levels, interface, package exposure, condensation recovery guidance, and calibration plan fit the enclosure and the required confidence.
23.8.2 Motion Wake for Wearables
A wearable fall-detection prototype might compare LIS3DH and ADXL345-style accelerometers. The gate table should check selectable range, output data rate, interrupt behavior, FIFO support, I2C/SPI access, supply/I/O limits, package orientation, and current by mode. Weighted scoring can then compare driver ecosystem, integration effort, interrupt flexibility, and power headroom, but only after both candidates can capture the required motion without saturating or waking the host too often.
23.8.3 Vibration Monitoring Asset
A predictive-maintenance node needs more than “an accelerometer with high resolution.” The selection review should check sensor bandwidth, noise, dynamic range, mounting stiffness, temperature exposure, connector/cable behavior, sampling jitter, timestamp alignment, and whether the MCU can move samples without dropping data. An ADXL355-class low-noise accelerometer may be appropriate for some vibration tasks, but the release claim still depends on target-machine measurements, fixture resonance checks, and firmware traces from the actual sampling path.
23.9 Weighted Scoring Is a Trade-off Tool
Weighted scoring is useful when the remaining candidates all meet the gates. It should not pretend to be more precise than the evidence supports.
The Weighted Scoring Is a Trade-off Tool argument uses Figure 23.2 to compare Mandatory Gates. Look next for reject hard failures before accepting Weighted scoring belongs after mandatory gates and before bench validation, not before basic fit is proven as a design claim.
Read Figure 23.2 downward from mandatory gates, which reject hard failures before comparison. The evidence matrix supplies rows and conditions for a weighted score covering valid trade-offs. Sensitivity review checks weights and assumptions before bench validation.
Example gates: supply range, measurement range, required accuracy, bus compatibility, package fit, operating temperature. Example preferences: extra margin, lower current, stronger ecosystem, easier calibration, better availability, lower integration effort.
23.10 Power Review Without False Precision
For battery systems, record every state that the firmware can enter. Average current is only meaningful when the duty cycle is realistic.
I_avg = (I_state_1 x time_1 + I_state_2 x time_2 + ... + I_state_n x time_n) / total_time
23.11 Try It Now
Rewrite this weak selection claim into a gate-based review note:
“Use the cheaper humidity sensor because it has low power and good accuracy.”
A stronger answer should name the measured quantity, required range, deployment environment, supply/I/O constraints, package exposure, accuracy condition, power states, interface checks, and the bench measurement that must confirm the choice.
23.12 Pick the Non-Negotiable Gate
For each project, write the first gate you would check before scoring candidates:
First: A refrigerated medicine cabinet that must alert before contents warm beyond the allowed storage band.
Next: A soil-moisture node installed outdoors for a full growing season.
Then: A wrist-worn gesture controller that must wake the host only on deliberate movements.
23.13 Interface and Firmware Checks
The selected sensor must match both hardware and firmware, not just the block diagram.
23.14 Application Snapshots
Treat these as patterns. The best sensor depends on the project requirements and final evidence.
Accelerometer or IMU
Gate on range, output data rate, current states, package, interface, interrupt behavior, and mounting orientation. Score power margin, motion features, driver support, and availability.
Pressure, humidity, temperature
Gate on operating range, accuracy over temperature, recovery from condensation, enclosure airflow, supply, current, and calibration needs.
Proximity or vibration
Gate on environmental exposure, EMC, mechanical mounting, cable length, supply transients, response time, and service lifetime.
Decision-support sensors
Gate on diagnostics, failure state, documentation, supplier control, and validation plan. A scorecard cannot replace safety analysis.
23.15 Selection Summary Template
23.16 Practice Checks
23.17 Common Pitfalls
Feature-rich sensors can be poor choices if the deployment needs low power, a specific interface, simpler calibration, or a more robust package.
Apply hard gates first. A failed supply, range, package, or interface requirement is not a low score; it is a blocker.
Use guaranteed min/max values and stated conditions for release decisions. Typical values can support early estimates and sensitivity checks.
The datasheet may support I2C or SPI, but the final product still needs address planning, timing traces, reset behavior, driver tests, and fault handling.
Breakout-board demos and datasheets are not release evidence. Measure the final board under realistic power, timing, mounting, and environmental conditions.
23.18 Summary
Sensor selection is a controlled, evidence-led process. Start from the sensing claim, define mandatory gates, build a datasheet evidence matrix, score only viable trade-offs, verify the selected candidate on the bench, and publish a selection summary that names assumptions and residual risks. This keeps weighted scoring useful without letting it hide requirement failures.
23.19 References
First: STMicroelectronics LIS3DH Product Page - official product page and datasheet access for a low-power digital accelerometer example.
Next: Analog Devices ADXL345 Product Page - official product page and datasheet access for a digital accelerometer example.
Then: Bosch Sensortec BME280 Data Sheet - official environmental sensor datasheet used as an example of range, interface, and power evidence.
23.20 See Also
First: Specification Sheet Fundamentals: review the datasheet rows and conditions that feed the gate table.
Next: Accelerometer Datasheet Case Study: apply the selection route to a concrete motion-sensor datasheet.
Then: Simulation-Driven Testing and Validation: plan the bench checks that confirm the selected part in context.
After that: End-to-End Test Strategy: turn the selection summary into repeatable validation evidence.
23.21 What’s Next
| If you want to… | Read this |
|---|---|
| Review datasheet vocabulary and limits | Specification Sheet Fundamentals |
| Walk through a real accelerometer datasheet | Accelerometer Datasheet Case Study |
| Apply selection evidence to automotive constraints | Automotive Datasheet Qualification |
| Verify selected parts before hardware release | Simulation-Driven Testing and Validation |
| Turn selected parts into validation records | End-to-End Test Strategy |
| Previous | Current | Next |
|---|---|---|
| Specification Sheet Fundamentals | Sensor Selection Process | Accelerometer Datasheet Case Study |
23.22 Key Takeaway
Sensor selection should compare the measurement need with range, accuracy, resolution, drift, response time, power, interface, calibration, and environmental limits. Price alone is not a selection criterion.
23.23 Continue Your Route
This final part closes the route from Requirements Before Parts through Key Takeaway. Return to Sensor Selection: Evidence Before Preference or continue from the design-methodology module index.
