Free e-book: Discover the world of AIoT
E-book: Discover the world of AIoT

The UWB RTLS Network Planning and Optimization Guide

for High-Density Industrial Environments (featuring Qorvo QM35)

Download our definitive guide for industrial engineers and system integrators to achieve unparalleled localization precision, operational efficiency, and a strategic business advantage in dense industrial environments.

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The Next Generation of Industrial Precision

Traditional localization technologies often fall short in responding to demand for granular insight into asset movements, personnel safety, and workflow optimization, especially in high-density industrial environments. They are hampered by signal interference, multipath propagation, and insufficient accuracy.

Our guide provides a comprehensive framework for deploying and optimizing Ultra-Wideband (UWB) RTLS, leveraging the advanced capabilities of the Qorvo QM35 chipset to meet these challenges head-on.

Key Takeaways from the Guide:

  • Learn methodologies for environmental assessment, multipath analysis, and RF noise mapping to build a solid foundation for your network.
  • Understand how to use algorithms and geometric principles to perfect anchor placement for maximum accuracy.
  • Compare wired and wireless strategies to ensure your anchors work in perfect harmony.
  • Discover techniques for managing co-channel interference, a critical step in large-scale deployments.
  • Follow clear procedures for benchmarking, testing, and calibrating your system to achieve peak performance.

Master the Core Pillars of UWB Network Design

Move beyond basic planning with an in-depth look at the sophisticated techniques required for a successful UWB RTLS deployment in high-density industrial environments.

Key Insights Inside:

Go beyond a basic site survey: Learn to conduct a comprehensive environmental assessment, including mapping machinery, analyzing the material composition of obstructions like steel and concrete, and accounting for dynamic elements like forklifts and AGVs. The guide details how to use specialized UWB channel sounding tools to create heatmaps of multipath intensity, allowing you to design a network that avoids destructive interference proactively.
Optimize anchor geometry with GDOP: Discover why Geometric Dilution of Precision (GDOP) is a critical metric that can amplify minor ranging errors. We explain how to optimize anchor placement by applying the Convex Hull Principle, implementing anchor redundancy, and using varied anchor heights to ensure high accuracy in full 3D environments.
Choose the right architecture (TDoA vs. TWR): Understand the trade-offs between Time Difference of Arrival (TDoA) and Two-Way Ranging (TWR) systems. TDoA relies on precisely synchronized anchors for ultimate precision, while TWR offers simpler synchronization requirements. The ebook also covers hybrid approaches for complex facilities.
Select the best synchronization strategy: Compare wired synchronization using Precision Time Protocol (PTP)—which offers unparalleled accuracy but requires complex cabling—with flexible wireless synchronization enabled by the Qorvo QM35 chipset. A detailed comparison table helps you choose the best fit for your application, whether it's for robotic control or flexible asset tracking.

Why Read This Ebook?

It's a strategic guide for transforming your industrial operations. By reading, you will learn to:

01

Implement a proven framework for reaching the sub-10cm precision that enables a new generation of use cases, from autonomous robot navigation to enhanced worker safety.

02

Utilize software tools and simulation techniques to visualize signal propagation and GDOP maps, allowing you to refine your network design before physical installation, saving significant time and money.

03

Translate technical precision into a tangible competitive advantage through enhanced operational efficiency, improved resource utilization, and data-driven decision-making.

Actionable Strategies for Advanced Deployments

Our guide provides advanced strategies for ensuring your system's long-term success and reliability.

Mitigate Co-Channel Interference

Learn to manage large-scale deployments with strategies like dynamic UWB channel selection, optimizing transmitter power levels, using directional antennas, and implementing advanced filtering algorithms.

Implement Rigorous Validation & Calibration

Define key performance indicators (KPIs) like static and dynamic accuracy, latency, and robustness. Follow our methodologies for collecting error data, calculating standard deviation and confidence intervals, and identifying outliers to pinpoint root causes of inaccuracy.

Ensure Long-Term Performance

Calibration is not a one-time event. The guide outlines how to perform on-site calibration by fine-tuning anchor positions post-installation and establishing continuous, long-term monitoring dashboards to track system health, network latency, and interference levels in real-time.

Frequently Asked Questions (FAQ)

This guide is written for industrial engineers and RTLS system integrators facing the complexities of deploying and optimizing UWB systems in high-density environments.

The procedures detailed in this guide are specifically for achieving and validating sub-10cm accuracy.

Yes. It provides a complete framework that covers every stage of deployment, from physical site surveys and hardware placement algorithms to software simulation, post-installation calibration, and long-term maintenance.

Time Difference of Arrival (TDoA) systems use a network of highly synchronized anchors to calculate a tag's position based on the different arrival times of its signal, making it ideal for high-precision applications. Two-Way Ranging (TWR) involves a direct communication handshake between a tag and an anchor to measure distance and is less sensitive to synchronization errors.

GDOP quantifies how the geometry of your anchor placement can multiply small ranging errors into large positional inaccuracies. A low GDOP value is essential for achieving high localization accuracy.

For the most accurate results, the guide recommends using specialized equipment like spectrum analyzers to measure the RF noise floor and UWB channel sounders to identify and map multipath-prone areas.

Free e-book: The UWB RTLS Network Planning and Optimization Guide
for High-Density Industrial Environments

featuring Qorvo QM35

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Please provide your details to receive immediate access to "The UWB RTLS Network Planning and Optimization Guide for High-Density Industrial Environments" and learn how to position your organization for market leadership.

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At needCode, we don't just integrate technology; we empower innovation.

As a trusted Qorvo Partner, we bring deep expertise in the Aliro standard, UWB technology, and specifically, Qorvo's QM35825 module. We are a leading system integrator and the go-to company for UWB implementation, helping manufacturers like you navigate the complexities of cutting-edge wireless technology.
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Specialized Expertise:

We possess unparalleled knowledge of Aliro, UWB, and the QM35825, ensuring optimal performance for your products.

Proven Partnership:

Our strong, established relationship with Qorvo means you benefit from direct access to the latest advancements and dedicated support.

End-to-End Solutions:

We provide comprehensive integration services that accelerate your time-to-market and de-risk your development process.

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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.