Dual Detection (Magnetometer + Nanoradar)

Perex: A dual‑detection parking sensor fuses a 3‑axis geomagnetic element with a compact mmWave / nanoradar module to give redundant, high‑confidence occupancy decisions for on‑street and garage parking. This guide covers standards, procurement notes, installation steps, maintenance, trends and real project references for municipal and integrator procurement teams.

Why dual detection parking sensor matters in smart parking

Combining a 3-axis magnetometer with a nanoradar yields complementary sensing physics: geomagnetic sensing excels at stationary vehicle presence (including low-RCS vehicles) while short‑pulse mmWave returns detect small clearances and moving vehicles. The fusion reduces false positives from metallic clutter, transient magnetic noise and partial occlusion. Where single‑sensor solutions fail under specific urban failure modes, a fused decision logic gives the robust, court‑defensible occupancy signal procurement teams require.

Standards and radio conformity remain procurement gating factors; short‑range device (SRD) rules (EN 300 220 family) and product safety (EN 62368‑1) should be explicitly required in tender documents. See ETSI guidance on SRD harmonised standards for details.

Practical procurement instruction: attach test‑report excerpts (RF/EMC/safety) to the tender evaluation matrix and score devices for lab‑verified behaviour under extreme temperatures and duty cycles.

Types of dual detection parking sensor (procurement categories)

• Flush / in‑pavement dual sensors (geomagnetic + nanoradar) — on‑street curbside where IP68 ingress protection and IK10 impact resistance are required; primary use: metered bays and residential zones. Easy installation notes apply.
• Low‑profile mini dual mode occupancy sensor — compact diameter for constrained footways; often optimised for LoRaWAN connectivity.
• Surface / screw‑in dual technology sensor — private lots/garages (lower snowplough risk); energy/battery options vary. See battery‑powered parking sensor.
• Hybrid camera + dual sensor nodes (edge‑AI + magnetometer + radar) — used where enforcement or complex intersections require richer evidence (see edge‑ai parking sensor and multi-sensor fusion).

Key differentiators you must capture in tender language: detection method (magnetometer + nanoradar), network options (LoRaWAN / NB‑IoT / LTE‑M), battery chemistry and capacity, ingress/impact ratings, OTA capability and the availability of device black‑box logs.

System components and procurement checklist

A system‑level procurement should list the components and minimally required evidence:

• dual detection sensor node (magnetometer + nanoradar)
• Local network: LoRaWAN connectivity or NB‑IoT connectivity with private APN options
• Backend with OTA and fleet management (OTA firmware updates / firmware over the air)
• Parking guidance and real‑time displays (parking guidance system)
• Installation kit and easy‑install instructions (Easy installation)
• Acceptance test protocol and sample field logs (camera / manual spot checks)

Operational features to require in tender:

• Onboard coulombmeter and battery health telemetry (for scheduled replacements) — tie to Battery life calculator
• Autocalibration with remote telecommands (Autocalibration)
• Black‑box logging and remote diagnostics for post‑event analysis
• Documented dual‑fusion algorithm (not just voting logic) and sample logs for inspection

How dual detection sensors are installed, measured and commissioned (step‑by‑step)

1. Site survey & RF check: measure network RSSI and take magnetic baseline samples. Confirm gateway placement and interference sources. (Document minimum RSSI in the tender.)
2. Slot preparation: ensure drainage, clean recess, and correct recess depth for flush mounts.
3. Sensor configuration: set reporting interval, radar duty cycle, magnetometer thresholds and network activation details (OTAA/ABP or operator profile).
4. Mechanical mounting: epoxy or screw in; verify orientation and torque specs per installation manual.
5. Autocalibration & baseline capture: allow 24–72 h baseline capture; avoid installation during special events that could bias baseline.
6. Field tuning: use the backend (or mobile diagnostic app) to tune radar thresholds for local vehicle mix (EVs, steel/composite bodies).
7. Acceptance test: compare sensor logs with camera/manual observations over 1–2 weeks, record false positive/negative rates.
8. Go‑live & monitoring: enable OTA and scheduling for battery maintenance and verification alarms.

(These steps are also suitable for inclusion in vendor Statement of Work and acceptance protocol.)

Maintenance and performance considerations

• Battery lifecycle: vendor claims are usage‑model dependent (transmit interval, radar duty cycle); require coulombmeter telemetry and a vendor battery‑life calculator as a contract deliverable. See the sensor datasheet for vendor battery options and the recommended calculation method.
• Snow & ice masking: radar lens performance can drop when covered in water/ice; specify snow‑plough marking and routine lens inspection in SLAs. See cold-weather performance.
• False positive elimination & fusion: insist on firmware that fuses magnetometer and radar at event level (temporal fusion + anomaly flags) and provide sample logs during tender evaluation (False positive elimination, multi-sensor fusion).
• Remote diagnostics & OTA: require remote reboot, recalibration telecommands and black‑box export via the fleet backend (firmware over the air).

Deployment tip — autocalibration + black‑box logs: demanding autocalibration and field log export reduces service calls and shortens mean‑time‑to‑repair (MTTR). Ask vendors to provide a sample 7‑day log extract for the evaluation phase and include it as a pass/fail deliverable.

Current trends and what to specify in tenders

• LoRaWAN regional parameter updates and new regional profiles are improving network efficiency and device battery life — require vendors to declare supported LoRaWAN regional parameter set and uplink profiles in the tender.
• Tight on‑device fusion and adaptive radar duty cycles (event‑driven radar pulses) reduce continuous radar power draw and extend field life.
• Energy harvesting and smarter power management are becoming viable for non‑high‑duty sites; still verify expected duty cycle and uplink profile.
• Demand firmware updateability, algorithm descriptions and recorded field test logs (cold / wet weather) as part of acceptance.

Summary / Procurement checklist (short)

• Require: autocalibration, coulombmeter telemetry, EN/IEC test reports (EN 300 220, EN 62368‑1), OTA management and sample field logs.
• Score devices on: detection reliability (lab + camera coverage), cold‑weather behaviour, battery telemetry, and ease of field service.

Frequently Asked Questions

1. What is a dual detection parking sensor?

A fused on‑slot device with a magnetometer and nanoradar module that publishes a single occupancy decision. It reduces single‑sensor failure modes and false positives.

2. How is a dual detection sensor implemented in a smart parking rollout?

Follow the site survey → mount → autocalibrate → tune → acceptance test flow. Capture baseline data for 24–72 hours and validate with manual or camera observations.

3. How long does the battery last in cold climates?

Battery life depends on chemistry, transmit profile and radar duty cycle. Require vendor calculators and coulombmeter telemetry; model worst‑case cold‑soak scenarios in acceptance tests.

4. Are dual sensors resilient to snowploughs and water ingress?

Specify IP68 ingress protection and IK10 impact resistance for on‑street devices. Note the radar lens can be masked by snow/ice—include plough marking and lens inspection schedules in maintenance SLAs.

5. How do systems integrate with LoRaWAN / NB‑IoT backends?

Integration uses standard stacks (LoRaWAN / NB‑IoT / LTE‑M). Ask for private APN options, secure transport, sample telemetry schema and API/MQTT integration guides. For LoRaWAN best practices see the LoRa Alliance guidance.

6. What is required for maintenance and recalibration?

Remote OTA, a device health dashboard, scheduled battery replacement windows based on coulombmeter telemetry, and a recalibration SLA for magnetometer drift.

Referencies

Below are short, procurement‑oriented summaries of relevant projects from recent Fleximodo deployments (selected entries from provided project data). These examples are helpful when writing tender evaluation scenarios or POC acceptance protocols.

• Pardubice 2021 — 3,676 sensors (SPOTXL NB‑IoT)

  • Deployed: 2020-09-28
  • Sensor type: SPOTXL NBIOT (large NB‑IoT rollouts are typical when operator coverage and roaming costs allow)
  • Notes for procurement: scale testing practices (multi‑thousand sensor rollouts) and NB‑IoT integration requirements are proven here; include NB‑IoT integration and private APN verification in the tender.
  • Useful link for tender language: NB‑IoT parking sensor and private APN security

• RSM Bus Turistici (Roma Capitale) — 606 sensors (SPOTXL NB‑IoT)

  • Deployed: 2021-11-26
  • Suggestion: validate device behaviour in mixed vehicle fleets (coaches, buses) and document detection limits.

• Kiel Virtual Parking 1 — 326 sensors (mixed SPOTXL LORA / NBIOT)

  • Deployed: 2022-08-03
  • Suggestion: mixed network strategies (LoRa + NB‑IoT) support resilience; require gateway and network fallover procedures in tender.

• Chiesi HQ White & Via Carra (Parma) — SPOT MINI / SPOTXL LORA

  • Include underground parking sensor considerations (attenuation, multi‑path) and require underground acceptance test with in‑garage sensors: see underground parking sensor.

• Skypark 4 Residential Underground Parking (Bratislava) — SPOT MINI

  • Example of interior deployment constraints and battery calibration requirements for low‑ceiling environments.

(Use these project entries to craft acceptance tests: number of bays, vehicle mix, camera cross‑validation duration and battery telemetry windows.)

Callouts — field experience & practical takeaways

Cold‑weather lab validation: test to -40°C and require the report

Fleximodo lab tests and datasheets include temperature condition coverage to -40 °C and +75 °C for RF behaviour and safety tests. Require the same test ranges in the tender and include cold‑soak acceptance checks during the warranty period.

Deployment takeaway — autocalibration + black‑box logs

Requiring autocalibration routines and remote exportable black‑box logs reduces field visits and accelerates fault diagnosis. Include a contract clause that the vendor must provide a 7‑day diagnostic log sample during evaluation.

Learn more (internal glossaries / follow‑ups)

• 3-axis magnetometer • nanoradar technology • dual detection (this page)
• LoRaWAN connectivity • NB‑IoT connectivity • firmware over the air
• battery life calculator • autocalibration • false positive elimination

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Author Bio

Ing. Peter Kovács — Technical freelance writer

Ing. Peter Kovács is a senior technical writer specialising in smart‑city infrastructure. He writes for municipal parking engineers, city IoT integrators and procurement teams evaluating large tenders. Peter combines field test protocols, procurement best practices and datasheet analysis to produce practical glossary articles and vendor evaluation templates.