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UWB RTLS for Worker Safety and Geofencing in Hazardous Environments

An ATEX/IECEx Compliance and Deployment Guide

Move beyond reactive safety protocols. Download the guide, which provides an actionable framework for deploying Ultra-Wideband (UWB) Real-Time Location Systems (RTLS) in ATEX/IECEx-rated environments, enabling the prevention of incidents before they occur.

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Legacy Safety Systems Have Reached Their Operational Limits

Legacy positioning technologies, such as Wi-Fi, RFID, and GPS, are struggling to meet the contemporary challenges of workplace safety. In the multipath-rich industrial facilities, these systems produce location errors of several meters, an unacceptable ambiguity when a worker’s proximity to a high-risk zone is in question.

Our guide introduces Ultra-Wideband (UWB) Real-Time Location Systems (RTLS), a transformative technology that enables you to transition from passive monitoring to proactive, preventative safety.

Key Takeaways from the Guide:

  • Obtain reliable location data (with an accuracy of 10-30 cm) to power dependable geofencing and provide accurate locations during emergencies.
  • Facilitate immediate collision avoidance alerts between personnel and vehicles and trigger automated system shutdowns when geofences are breached.
  • Deploy a system that delivers consistent performance in complex, metallic structures where other RF technologies fail.
  • UWB tags feature multi-year battery life, minimizing maintenance burdens and ensuring system uptime.

Master the UWB RTLS Deployment for Workplace Safety in Dense Environments

This guide demystifies the complexities of deploying UWB RTLS in dangerous environments with actionable, technical details.

Key Insights Inside:

Navigate ATEX/IECEx Compliance: Understand the engineering principles of Intrinsic Safety (IS) for UWB hardware. The guide outlines the rigorous design process necessary to prevent explosions by limiting electrical and thermal energy, encompassing power limitation circuits, component selection, and thermal management.
Implement a Phased Deployment Roadmap: Learn a strategic, three-phase approach to rollout that mitigates risk and ensures success. The process covers initial RF site assessment and pilot programs, scaled deployment with enterprise system integration (DCS/SCADA), and long-term operational optimization through data analytics.
Monetize Your Safety Investment: Discover how the high-fidelity operational data generated by UWB RTLS delivers a quantifiable ROI. By analyzing workflow patterns and asset utilization, you can turn a mandatory safety expenditure into an investment that drives operational excellence and strengthens the business case for executive stakeholders.
Future-Proof Your Architecture: Learn how industry standards like FiRa and omlox ensure an interoperable, multi-vendor ecosystem. This de-risks adoption and provides a clear path for future expansion by decoupling your location hardware from the consuming software applications.

Why Read This Ebook?

Get a clear, business-focused framework for evaluating and implementing UWB RTLS technology for worker safety and geofencing in hazardous environments.

01

For safety and compliance officers: Get a blueprint for reducing OSHA-recordable incidents, decreasing evacuation times, and generating automated reports for 100% compliance in access control audits.

02

For operations managers: Learn to transform your safety system into a continuous improvement engine. Utilize analytics to analyze personnel flow, identify near-miss hotspots, and refine workflows to minimize operational downtime.

03

For technical leaders & engineers: Gain a deep understanding of the underlying physics of UWB (ToF vs. RSSI), the architectural trade-offs between TDoA and TWR systems, and the technical design constraints for creating Intrinsically Safe hardware for ATEX/IECEx zones.

Unlock the Full Value of Location Data

A successful UWB RTLS is the nervous system of a modern, data-driven industrial safety program.

Master Data Security and Privacy

Learn how to secure data transmission using end-to-end encryption and the IEEE 802.15.4z standard's inherent spoofing resistance. The guide also outlines a "Privacy by Design" approach, utilizing data anonymization and Role-Based Access Control (RBAC) to foster workforce trust and buy-in.

Leverage Advanced Analytics

Discover how to use analytics platforms to transform raw location data into preventative safety intelligence. Generate heatmaps to identify congestion, analyze spaghetti diagrams to find workflow inefficiencies, and study near-miss incident data to mitigate risks before a collision occurs.

Integrate with Core Plant Systems

Learn how to utilize APIs to transmit RTLS data into your plant’s DCS/SCADA systems for automated safety interlocks—such as halting a robot if a worker enters its designated geofence. Provide emergency response teams with unparalleled situational awareness through real-time tracking of muster points.

Frequently Asked Questions (FAQ)

UWB RTLS achieves centimeter-level accuracy, typically ranging from 10 to 30 cm. This precision is possible because UWB uses Time-of-Flight (ToF) measurements, which are highly resilient to the signal reflections (multipath) common in industrial environments.

Yes. The guide provides a detailed technical overview of designing Intrinsically Safe (IS) UWB hardware that complies with ATEX and IECEx standards. It focuses on the core IS principle of preventing an explosion by designing circuitry that cannot release enough energy to cause ignition, even under fault conditions.

Wi-Fi and Bluetooth rely on Received Signal Strength Indicator (RSSI), which estimates distance based on signal power. This method is unreliable in industrial facilities, where signal reflections can lead to location errors of 5-10 meters. UWB utilizes Time-of-Flight (ToF), which precisely measures the travel time of a radio pulse, allowing the system to discard reflected signals while maintaining high computational accuracy.

UWB is explicitly designed for coexistence. It operates under a very low power spectral density, spreading its energy across a vast bandwidth. This makes its transmissions appear as low-level background noise to most narrowband systems, creating minimal to no interference.

While safety is the primary driver, the high-fidelity location data generates a significant and quantifiable ROI. By analyzing this data, organizations can identify workflow bottlenecks, optimize asset utilization, and streamline processes, turning a safety expenditure into an investment in operational excellence.

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

Proven Partnership:

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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.