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Solution

LiDAR application solution for parking occupancy and camera triggers

Use parking-bay distance change to determine occupancy or trigger a camera, replacing continuous video processing with event-based capture.

Overhead LiDAR detecting occupancy across parking bays

Scenario

Application scenario

A smart-parking system can monitor distance from above or the side, then let a controller determine occupancy and trigger a camera or report status. Vehicle types, angle, and outdoor light require site calibration.

Engineering problem

  • Empty pavement, vehicle types, and parking position produce different distances.
  • Sunlight, weather, contamination, and mounting error affect returns.
  • Distance changes need thresholds, duration, and fault handling before becoming an occupancy event.

Why LiDAR

LiDAR provides direct distance change so a controller can trigger a camera or update occupancy when a vehicle arrives, reducing continuous processing.

Workflow

  1. Define bay coverage, mounting height, and vehicle range.
  2. Record distance distributions for empty and occupied states.
  3. Configure thresholds, duration, debounce, and fault handling.
  4. Validate sunlight, rain or snow, contamination, and off-center parking.

Technology comparison and selection

DimensionConditionLiDARAlternativeAlternative performanceConclusion
Parking occupancy or trigger inputCompare on the real target, mounting path, environment, control logic, and project acceptance criteria; do not compare nominal maximum range alone.Provides distance-change or detection-area input for occupancy logic or camera triggering.Continuous video analytics / magnetic or contact sensingDepend on image processing, magnetic fields, or contact state with different maintenance and data boundaries.

Define occupancy logic and false-trigger handling first, then select sensing by environment, coverage, and maintenance.

公开来源公开来源 · Verified 2026-08-24

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Selection

Product selection guide

Current material supports 3 candidates. Review product facts, rationale and boundaries together.

ModelKey product factsBest fit and rationaleOperating boundaryProduct details
TF-Luna
Output data
Single-point Distance Value
Measuring range
0.2 ~ 8 m
Interface
UART, I/O, I²C
Protection
Without enclosure

For single-point distance-change input at controlled parking bays or trigger points.

Calibrate vehicle types, mounting height, ground, rain or dirt, occlusion, and thresholds on site.

View product
TFmini-S
Output data
Single-point Distance Value
Measuring range
0.1 ~ 12 m
Interface
UART, I/O, I²C
Protection
未注明

For near-range detection or trigger tasks with tight mass and mounting constraints.

Verify the current protection status and field environment together; do not assume outdoor-bay suitability by default.

View product
TF-NOVA
Output data
One-dimensional Area Detection Solution
Measuring range
14 m
Interface
UART, I/O, I²C
Protection
IP65

For parking-bay change or trigger input needing wider horizontal coverage.

Validate line-pattern beam, target geometry, parking position, and control thresholds together.

View product
Continue with a relevant model-difference topic

Installation and integration

  • Define the target, measurement axis, occlusion, wiring, and mounting space first; connect the current product manual to the target controller and record the model, interface, orientation, offset, and delivered revision.

    Smart-parking solution · Target controller or host system · Target hardware and software release verified before deployment公开来源 · Verified 2026-08-24

  • Before connecting business control logic, validate healthy data, timeout handling, stop behavior, and fallback with real targets, worst-case distance, ambient light, and motion.

    Smart-parking solution · Target controller or host system · Field procedure and fault handling verified on the target system公开来源 · Verified 2026-08-24

Operating limits

  • LiDAR provides distance or spatial-sensing input and does not by itself provide system positioning, safety integrity, braking, flight-stack fusion, or business outcomes; design and validate those functions separately on the target system.

    Smart-parking solution公开来源 · Verified 2026-08-24

Sources

Supporting sources

Verifiable TF-Luna reference

Verifies single-point range input and mounting conditions. The current public material supports verification of sensor specifications and interfaces; it does not establish vehicle-level performance, system safety level, or project results.

Use the stated target, reflectivity, ambient-light, mounting, and delivered-revision conditions; revalidate in the field.

TF-Luna Datasheet

Verifiable TFmini-S reference

Verifies lightweight near-range input and delivery conditions. The current public material supports verification of sensor specifications and interfaces; it does not establish vehicle-level performance, system safety level, or project results.

Use the stated target, reflectivity, ambient-light, mounting, and delivered-revision conditions; revalidate in the field.

TFmini-S Datasheet

Verifiable TF-NOVA reference

Verifies wider-horizontal-detection direction and documentation conditions. The current public material supports verification of sensor specifications and interfaces; it does not establish vehicle-level performance, system safety level, or project results.

Use the stated target, reflectivity, ambient-light, mounting, and delivered-revision conditions; revalidate in the field.

TF-NOVA Datasheet

FAQ

Frequently asked questions

Can parking occupancy be based on one empty-versus-occupied distance comparison?

Not reliably. Cover vehicle types, off-center parking, pavement, sunlight, weather, and contamination, then use thresholds, duration, debounce, and invalid-data handling.

Resources

Resources and references

Confirm the selection with real mission conditions

Share the operating height, target surface, environment, mounting space, and flight-stack version. Our engineering team can help plan selection and validation.

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