Free e-book: IEEE 802.15.4ab vs IEEE 802.15.4z
Free e-book: IEEE 802.15.4ab

A door chime doesn't save a sleeping child. Sensing one does

needCode builds in-cabin child presence detection on UWB radar - sensing a living presence by its breathing and micro-movement, so a sleeping or covered child is detected where a door-sequence reminder is not. Euro NCAP direct-sensing aligned, AI-classified to reject false alarms, and able to share a single sensing node across child presence, seatbelt reminder, and intrusion. From a certified Qorvo partner with deep UWB engineering.
needCode IoT

We work with Industry Leaders

Reminders assume the driver forgot. The dangerous case is the one no one remembers.

Most in-cabin safety systems are reminders - they chime based on a door-and-seatbelt sequence, on the assumption that the driver simply needs prompting. The cases that cause tragedies are different: a child left asleep, quiet, sometimes covered, that no sequence logic and no simple motion sensor reliably detects. Euro NCAP has recognised this, scoring direct sensing of the child well above indirect reminders.

Direct sensing is a radar problem. UWB radar can detect the micro-movement of breathing, which means it can find a still, sleeping child where motion and weight sensors miss them - then pair that signal with AI classification to tell a child from a coat, a pet, or an empty seat. needCode builds exactly that, on the UWB depth in-cabin sensing depends on.

Detects breathing, not just motion

UWB radar senses the micro-movement of respiration - so a sleeping, still child is detected rather than missed.

Euro NCAP direct-sensing aligned

Built for the assessment that scores detecting the child above reminding the driver.

One node, several functions

The same UWB radar covers child presence, seatbelt reminder, and intrusion - fewer parts, one integration.

How UWB radar detects a child

In-cabin presence detection is a sensing-and-AI problem in four parts. We build all four.

UWB Radar Sensing

UWB operates as an impulse radar, illuminating the cabin and reading reflections - not ranging to a tag, but sensing the space itself. IEEE 802.15.4ab adds the sensing capabilities this builds on, turning a positioning radio into a perception sensor.

Micro-Movement & Vital-Sign Detection

The radar resolves the tiny chest motion of breathing - the signal that separates a living presence from an object, and the reason it detects a child who is asleep and otherwise still. This is why radar succeeds where motion and weight sensors fail.

AI Classification

Edge ML interprets the radar returns to tell a child from an adult, a pet, a bag, or an empty seat - the layer that turns a raw signal into a reliable decision and keeps false alarms low. A radar return is only useful once it's classified.

Single-Node Multi-Function

One UWB sensing node serves child presence, seat occupancy, seatbelt-reminder logic, and intrusion detection - consolidating several safety features onto one radio and one integration instead of a sensor per function.

Building child presence detection or radar sensing?

Book a discovery call with our CEO

Beyond the cabin: where presence sensing goes.

The same UWB radar that finds a child in a car senses human presence and vital signs anywhere - and, because it reads movement rather than images, it does so without a camera. The capability extends well past automotive.

Automotive Child Presence

In-cabin child presence, seat occupancy, and intrusion to Euro NCAP direct-sensing - the flagship, regulation-driven application.

Smart Home Occupancy & Security

Presence-based lighting, HVAC, and intrusion detection that works in the dark and through stillness, where PIR motion sensors drop out - without a camera in the room.

Healthcare & Eldercare Monitoring

Contactless vital-sign monitoring - breathing and movement - plus fall and bed-occupancy sensing, without a wearable on the patient or a camera on the room.

Building Presence & Intrusion

People-presence and intrusion sensing for secure and smart buildings - single-sensor, and privacy-preserving where a camera isn't acceptable.

Why presence-detection teams bring in needCode

UWB radar depth, not just ranging

Most UWB work is ranging and positioning; in-cabin sensing is radar - a distinct discipline. As the largest dedicated UWB team in Central Europe, we work across both, including the IEEE 802.15.4ab sensing capabilities presence detection is built on.

Detection plus classification

A radar return is only useful once it's classified. We pair UWB sensing with edge ML so the system reliably distinguishes a child from a false alarm - the difference between a safety feature and a nuisance that gets switched off.

One radio you may already have

If a vehicle carries UWB for CCC digital key, child presence detection can run largely as a sensing-and-software addition on the same radio - consolidating child presence, occupancy, seatbelt, and intrusion onto one node and cutting BOM against multiple single-purpose sensors.
Direct access to UWB silicon (QM33 / QM35) and roadmap, including sensing-capable parts, so your bring-up starts ahead of the public SDK.

Four ways to bring needCode in

From a sensing feasibility study to a standing team. We match the engagement to where the system is.

01

Feasibility & Sensing Study

  • Duration:
    2–4 weeks
  • Best for:
    Validating radar-sensing feasibility and a detection/classification approach for your cabin or space
  • Deliverable:
    Feasibility assessment, sensing/classification approach, integration path, leadership readout

02

Detection & Classification Build

  • Duration: 
    Phased
  • Best for:
    Building the UWB radar firmware and edge-ML classification on target silicon
  • Deliverable:
    Sensing firmware, trained classifier, test results, demo

03

Productization & Euro NCAP Readiness

  • Duration: 
    Phased
  • Best for:
    Taking a prototype to production firmware and assessment readiness
  • Deliverable:
    Hardened firmware, validation, conformity and Euro NCAP readiness support

04

Embedded Team

  • Duration: 
    Multi-year, retainer-based
  • Best for:
    Product teams who want a dedicated UWB-sensing and edge-AI squad
  • Deliverable:
    An embedded team in your cadence - the model behind the 30-FTE Qorvo programme

What we ship on

We pick the silicon and stack that match your sensing target and environment.

Sensing

UWB radar (IEEE 802.15.4ab sensing)
impulse radar
micro-movement / vital-sign detection

AI

Edge ML classification
sensor fusion
on-device inference
Ambiq Apollo
Google Coral / Astra

Silicon

Qorvo QM33 / QM35 (sensing-capable)
NXP
STMicroelectronics
Infineon
legacy DW3000

Functions

Child presence
seat occupancy
seatbelt reminder
intrusion
vital-sign monitoring

Standards & assessment

Euro NCAP direct-sensing
FiRa
IEEE 802.15.4ab

RTOS

Zephyr
FreeRTOS
ThreadX

Case studies

needCode doesn't publish named child-presence programmes. What we can show is the UWB and edge-AI capability presence sensing is built on.

Qorvo: RF Leadership

Context: Rapid scaling for new chipset bring-up.
  • Scale: Grew from <10 to 30 FTEs.
  • Output: Supported bring-up of 9 new hardware platforms (SDKs, Drivers, Stacks).
  • Retention: Zero-churn core team retained for 5+ years.
Dedicated Development Center for RF Solutions
Bluetooth Mesh Smart Lighting Control System

Smart Lighting: Core R&D Extension

Context: Client needed deep, specialized expertise to pivot from proprietary tech to a new global standard.
  • Service: Deployed a dedicated squad of embedded engineers to function as the client's core R&D team.
  • Output: Co-authored official Bluetooth SIG protocols and delivered the world’s first certified BLE Mesh stack.
  • Value: Enabled the client to secure Series A funding and defined the industry standard for smart buildings.

Creative Werks: Innovation rescue

Context: Hardware obsolescence threatened production shutdown.
  • Action: Full-stack takeover (PCB redesign + Firmware + Mobile App).
  • ROI: 1230% ($1.6M value generated).
  • Speed: Payback period of 2–3 months.
NeedCode-case study - IoT Solution for Boat Lift Modernization - cover2s
needcode-powerpolen-case-study-cover2s

PowerPollen: AgTech automation

Context: Lack of internal expertise stalled a critical automation project.
  • Action: Re-architected system using unified MCU and ISOBUS standards.
  • ROI: 13.8x ($2.9M value generated).
  • Impact: Enabled $1.9M increase in harvester value.

Strategic Partnership

needCode is an official business partner of Qorvo, bringing over 8 years of proven expertise and trusted service to the technology sector.
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UWB-Alliance-logo-banner

Members of the UWB Alliance

In 2025 we became a member of the UWB Alliance. This strategic step reinforces our commitment to pioneering Ultra-Wideband (UWB) technology.

Proudly Certified for Excellence and Security

needCode is officially certified for:
ISO 9001:2015 – Quality Management
ISO/IEC 27001:2022 – Information Security
ISO certifications reflect our focus on delivering reliable IoT solutions, smart product development, and secure technology services.
ISO 9001_2015ISO - IEC 27001_2022

Testimonials

“I think the key takeaway from needCode is their ability to adapt and understand the customer's requirements. That took away probably a large portion of what could have been a lot of development time and expense for both companies.”
Bob Folkestad
Bob Folkestad
President at Creative Werks
“One aspect that truly sets needCode apart is its profound expertise in firmware development. Their proficiency in various programming languages, embedded systems and hardware architecture is truly impressive. When faced with difficult problems, their strong problem-solving skills and analytical mindset shine through, allowing them to overcome obstacles with remarkable ease.”
avatar Semeh Sarhan
Semeh Sarhan
CEO at Xtrava
“I worked with needCode while leading the NWTN-Berlin team in 2018. A big chunk for our FW development has been outsourced to them and they had proven to iterate very quickly, following specs and deliver on time. It was great working with them. I recommend working with needCode’s team on any Embedded SW development.”
avatar Marco Salvioli Mariani
Marco Salvioli Mariani
CTO at NWTN Berlin GmbH
“needCode Team proved to be one of the best engineers I have ever met. The part I like the most about the team is the more difficult an obstacle seems to be, the more motivated they were to find a solution and a way forward.”
A Testimonial picture
Szymon Słupik
CTO at Silvair
“needCode is an outstanding partner. Their quick follow-up, scalability, and extensive professional network set them apart. Their expertise in wireless technologies has been valuable, supporting us from low-level drivers to architecture discussions.”
avatar Tim Allemeersch
Tim Allemeersch
Director at Qorvo, Inc.
“needCode did a great job improving the firmware of the Vai Kai connected toys and developing new features, surpassing our expectations multiple times. I would definitely recommend hiring Bartek and needCode for the embedded software projects!”
avatar Matas Petrikas
Matas Petrikas
CEO & Co-founder
at Vai Kai UG

Insights

FAQ

UWB radar detects a child by operating in sensing mode - emitting impulses and reading the reflections from the cabin to perceive movement, including the micro-movement of breathing. Because it senses respiration rather than only gross motion, it can detect a child who is asleep and still, where door-sequence reminders and basic motion sensors fail. needCode pairs this with edge AI classification to confirm a child rather than an object.

Yes - detecting a still, sleeping child is the core reason to use radar, and UWB radar does it by sensing the tiny chest movement of breathing. A child who isn't moving still breathes, and that signal is what the system reads, which is exactly the case that defeats motion- and weight-based approaches. This is the difference between reminding a driver and actually detecting the child.

A reminder relies on indirect logic - a door opened, a seatbelt unbuckled - and assumes the driver simply needs prompting, so it cannot detect a child no one remembered. Direct sensing detects the child itself, which is why Euro NCAP scores it well above indirect reminders. needCode builds the direct-sensing approach, using UWB radar and AI classification.

UWB radar child presence detection is built for Euro NCAP's direct-sensing assessment, which rewards detecting the occupant over indirect reminders. needCode develops the firmware and classification with that assessment in mind and supports validation and readiness, though the exact scoring and timeline should be confirmed against the current Euro NCAP protocol. Direct sensing is the category Euro NCAP scores most highly.

False alarms are handled with edge ML classification that interprets the radar signature to distinguish a child from a pet, a bag, a coat, or an empty seat, rather than triggering on any movement. A reliable system has to reject these cases, because a CPD feature that cries wolf gets switched off. needCode's UWB-plus-edge-AI approach is built specifically to keep false alarms low.

Each has trade-offs: 60GHz mmWave radar is a mature, high-resolution dedicated sensing technology; cameras raise privacy concerns; and PIR motion sensors miss a still child. UWB radar's distinct advantage is that it can reuse a UWB radio a vehicle may already carry for digital key, adding child presence as a largely software and sensing feature on one multi-function node - and it senses presence without a camera. needCode helps weigh UWB against 60GHz for a given programme rather than claiming one always wins.

Yes - a single UWB sensing node can serve child presence, seat occupancy, seatbelt-reminder logic, and intrusion detection together, instead of a separate sensor per function. This consolidates several safety features onto one radio and one integration, reducing BOM and complexity. needCode designs the node to cover the functions a programme needs.

Yes - UWB radar senses movement and presence rather than capturing images, so it can detect a person, and even vital signs, without a camera in the cabin or the room. That makes it suitable for privacy-sensitive settings such as vehicle interiors, bedrooms, and eldercare. needCode treats this no-camera property as a core advantage of radar sensing.

Yes - the same micro-movement sensing that detects a child's breathing can be used for contactless vital-sign monitoring, including respiration and movement, in healthcare and eldercare settings. It enables fall detection and bed-occupancy sensing without a wearable on the patient. needCode builds these from the same UWB sensing and edge-AI foundation.

needCode works with sensing-capable UWB silicon, including Qorvo QM33 and QM35, alongside platforms from NXP, ST, and Infineon, building on IEEE 802.15.4ab sensing capabilities. As a certified Qorvo partner with nine hardware-platform bring-ups completed, needCode starts from chipset-level knowledge. The right part depends on whether the radio is shared with a digital-key or positioning function.

Let's work on your next project together

Book a demo and discovery call with our CEO
to get a look at:
Strategic Expertise
End-to-End Solutions
Advanced Technology
Custom Hardware Devices
Bartek Kling
Bartek Kling / CEO
© 2026 needCode. All rights reserved.

Manufacturing

Modern manufacturing machines are typically equipped with IoT sensors that capture performance data. AIoT technology analyzes this sensor data, and based on vibration patterns, the AI predicts the machine's behavior and recommends actions to maintain optimal performance. This approach is highly effective for predictive maintenance, promoting safer working environments, continuous operation, longer equipment lifespan, and less downtime. Additionally, AIoT enhances quality control on production lines.

For example, Sentinel, a monitoring system used in pharmaceutical production by IMA Pharma, employs AI to evaluate sensor data along the production line. The AI detects and improves underperforming components, ensuring efficient machine operation and maintaining high standards in drug manufacturing.

Logistics & supply chain

IoT devices - from fleet vehicles and autonomous warehouse robots to scanners and beacons - generate large amounts of data in this industry. When combined with AI, this data can be leveraged for tracking, analytics, predictive maintenance, autonomous driving, and more, offering greater visibility into logistics operations and enhancing vendor partnerships.

Example: Amazon employs over 750,000 autonomous mobile robots to assist warehouse staff with heavy lifting, delivery, and package handling tasks. Other examples include AI-powered IoT devices such as cameras, RFID sensors, and beacons that help monitor goods' movement and track products within warehouses and during transportation. AI algorithms can also estimate arrival times and forecast delays by analyzing traffic conditions.

Retail

IoT sensors monitor movement and customer flow within a building, while AI algorithms analyze this data to offer insights into traffic patterns and product preferences. This information enhances understanding of customer behavior, helps prevent stockouts, and improves customer analytics to drive sales. Furthermore, AIoT enables retailers to deliver personalized shopping experiences by leveraging geographical data and individual shopping preferences.

For instance, IoT sensors track movement and customer flow, and AI algorithms process this information to reveal insights into traffic patterns and product preferences. This ultimately leads to better customer understanding, stockout prevention, and enhanced sales analytics.

Agriculture

Recent research by Continental reveals that over 27% of surveyed farmers utilize drones for aerial land analysis. These devices capture images of crops as they are and transmit them to a dashboard for further assessment. However, AI can enhance this process even further.

For example, AIoT-powered drones can photograph crops at various growth stages, assess plant health, detect diseases, and recommend optimal harvesting strategies to maximize yield. Additionally, these drones can be employed for targeted crop treatments, irrigation monitoring and management, soil health analysis, and more.

Smart Cities

Smart cities represent another domain where AIoT applications can enhance citizens' well-being, facilitate urban infrastructure planning, and guide future city development. In addition to traffic management, IoT devices equipped with AI can monitor energy consumption patterns, forecast demand fluctuations, and dynamically optimize energy distribution. AI-powered surveillance cameras and sensors can identify suspicious activities, monitor crowd density, and alert authorities to potential security threats in real-time, improving public safety and security.

For example, an AIoT solution has been implemented in Barcelona to manage water and energy sustainably. The city has installed IoT sensors across its water supply system to gather water pressure, flow rate, and quality data. AI algorithms analyze this information to identify leaks and optimize water usage. Similarly, smart grids have been introduced to leverage AI to predict demand and distribute energy efficiently, minimizing waste and emissions. As a result, these initiatives have enabled the city to reduce water waste by 25%, increase renewable energy usage by 17%, and lower greenhouse gas emissions by 19%.

Healthcare

Integrating AI and IoT in healthcare enables hospitals to deliver remote patient care more efficiently while reducing the burden on facilities. Additionally, AI can be used in clinical trials to preprocess data collected from sensors across extensive target and control groups.

For example, intelligent wearable technologies enable doctors to monitor patients remotely. In real-time, sensors collect vital signs such as heart rate, blood pressure, and glucose levels. AI algorithms then analyze this data, assisting doctors in detecting issues early, developing personalized treatment plans, and enhancing patient outcomes.

Smart Homes

The smart home ecosystem encompasses smart thermostats, locks, security cameras, energy management systems, heating, lighting, and entertainment systems. AI algorithms analyze data from these devices to deliver context-specific recommendations tailored to each user. This enables homeowners to use utilities more efficiently, create a personalized living space, and achieve sustainability goals.

For example, LifeSmart offers a comprehensive suite of AI-powered IoT tools for smart homes, connecting new and existing intelligent appliances and allowing customers to manage them via their smartphones. Additionally, they provide an AI builder framework for deploying AI on smart devices, edge gateways, and the cloud, enabling AI algorithms to process data and user behavior autonomously.

Maintenance (Post-Release Support)

When your product is successfully launched and available on the market we provide ongoing support and maintenance services to ensure your product remains competitive and reliable. This includes prompt resolution of any reported issues through bug fixes and updates.

We continuously enhance product features based on user feedback and market insights, optimizing performance and user experience.

Our team monitors product performance metrics to identify areas for improvement and proactively addresses potential issues. This phase aims to sustain product competitiveness, ensure customer satisfaction, and support long-term success in the market.

Commercialization (From MVP to Product

Our software team focuses on completing the full product feature range, enhancing the user interface and experience, and handling all corner cases. We prepare product software across the whole lifecycle by providing all necessary procedures, such as manufacturing support and firmware upgrade.

We also finalize the product's hardware design to ensure robustness, scalability and cost-effectiveness.

This includes rigorous testing procedures to validate product performance, reliability, and security. We manage all necessary certifications and regulatory compliance requirements to ensure the product meets industry standards and legal obligations.

By the end of this phase, your product is fully prepared for mass production and commercial deployment, with all documentation and certifications in place.

Prototyping (From POC to MVP)

Our development team focuses on implementing core product features and use cases to create a functional Minimum Viable Product (MVP). We advance to refining the hardware design, moving from initial concepts to detailed PCB design allowing us to assemble first prototypes. Updated documentation from the Design phase ensures alignment with current project status. A basic test framework is established to conduct preliminary validation tests.

This prepares the product for real-world demonstrations to stakeholders, customers, and potential investors.

This phase is critical for validating market readiness and functionality before proceeding to full-scale production.

Design (From Idea to POC)

We meticulously select the optimal technology stack and hardware components based on your smart product idea with detailed use cases and feature requirements (Market Requirements Document / Business Requirements Document). Our team conducts thorough assessments of costs, performance metrics, power consumption, and resource requirements.

Deliverables include a comprehensive Product Requirements Document (PRD), detailed Software Architecture plans, an Initial Test Plan outlining validation strategies, Regulatory Compliance Analysis to ensure adherence to relevant standards, and a Proof of Concept (POC) prototype implemented on breakout boards.

This phase aims to validate the technical feasibility of your concept and establish a solid foundation for further development.

If you lack a validated idea and MRD/BRD, consider utilizing our IoT Strategic Roadmap service to gain insights into target markets, user needs, and desired functionality. Having a structured plan in the form of an IoT Strategic Roadmap before development begins is crucial to mitigate complications in subsequent product development phases.