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The Guide to Understanding the Technologies Defining the Next Phase of Edge AI

The 2026 Edge AI Technology Report Just Launched

This white paper focuses on practical design choices that improve battery life and maintain stable operation across changing load conditions.

Efficient Power Management for Portable and IoT Devices

Exploring the design, development, connectivity, security, and more aspects of IoT devices

Internet of Things: A Comprehensive Guide to its Engineering Principles and Applications

This article is a practical PLC programming guide covering the five IEC 61131-3 languages, the scan cycle that governs how your code actually runs, ladder and structured text examples, and the mistakes that cost engineers the most commissioning time.

PLC Programming: Languages, Scan Cycles, and Working Ladder Logic

An STM32 development board (left) alongside an ESP32 development board (right)

STM32 vs ESP32 compared on architecture, Wi-Fi, power, peripherals, toolchains, safety, and longevity. Current 2026 specs from vendor datasheets, plus a decision table.

STM32 vs ESP32: Choosing the Right Microcontroller for Your Design

This article explains what is a PLC, what's inside it, how the scan cycle works, which programming languages the current IEC standard defines, and how to choose the right controller for your application.

What Is a PLC? A Complete Guide to Programmable Logic Controllers

Schmitt trigger with positive feedback and hysteresis.

A Schmitt trigger is a circuit that converts slow or noisy inputs into clean digital signals using two switching thresholds. This guide explains hysteresis, op-amp and transistor designs, equations, real 74HC14, CD40106B, and 555 timer examples, and common design mistakes.

Schmitt Trigger Circuit: Hysteresis, Design Equations, and Applications

The electric wire behind the control board.

What a programmable automation controller is, how PACs are built and programmed, and how to choose between a PLC and a PAC.

What Is a Programmable Automation Controller (PAC)?

Industrial Robot Arms Assemble EV Battery Pack on Automated Production Line

This guide explains industrial automation systems, the automation pyramid, core technologies, types, applications, benefits, and Industry 4.0 trends shaping smart manufacturing in 2026.

What Is Industrial Automation? Complete Guide (2026)

Nvidia’s CUDA cores are specialized processing units within Nvidia graphics cards designed for handling complex parallel computations efficiently, making them pivotal in high-performance computing, gaming, and various graphics rendering applications.

Understanding Nvidia CUDA Cores: A Comprehensive Guide

A Schmitt trigger is a comparator circuit with built-in hysteresis that uses two switching thresholds to eliminate noise and ensure stable output transitions. It is widely used for signal conditioning, waveform shaping, and robust digital and analog circuit design.

Schmitt Trigger: Robust Comparator Design with Hysteresis

CUDA cores are Nvidia GPUs' core FP32/INT32 processing units, powering parallel computing across HPC, gaming, and graphics rendering tasks.

Understanding Nvidia CUDA Cores: A Comprehensive Guide for 2026

A voltage reference is a precision circuit that delivers a stable output voltage independent of temperature, power supply, and load variations. This article covers key reference technologies, specifications, selection criteria, PCB design, and applications in ADCs, DACs, and calibration systems.

Voltage Reference: A Survey for Precision Engineers

Discover what is an FPGA and how field-programmable gate arrays empower engineers to create custom digital hardware. This guide combines a beginner-friendly definition with architectural insights, process technology, and design methodologies.

What Is an FPGA? Complete Guide to Field Programmable Gate Arrays for Engineers

Variable Speed Drive Controller used in Factories

This guide explains what is a VFD, further detailing how it works, compares types and vendors, provides application and selection advice, surveys 2026 trends, and responds to common questions.

What Is a VFD (Variable Frequency Drive)? Complete Engineering Guide to VFD Drives (2026)

Active high-pass filters remove unwanted low-frequency signals while preserving useful higher frequencies. This article covers first- and second-order filter design, Sallen-Key and multiple-feedback topologies, and practical applications in audio electronics, instrumentation, and signal processing.

Active High Pass Filter: Theory, Design, and Applications

<p id="isPasted">Industrial Ethernet networks must be resilient in order to withstand disturbances, faults and failures that can lead to unplanned downtime. </p><p>It’s hard enough at the best of times to keep a network resilient and continuously available. When you’re operating in industrial situations, you’ll likely be facing additional challenges such as harsh environmental conditions, electrical interference, extreme temperatures and unforeseen network outages.</p><h2>What Is Network Redundancy?</h2><p>People often treat network resilience and network redundancy as the same thing, but redundancy is actually a subset of network resiliency. There are four of these subsets, sometimes called the “four Rs”: </p><ul><li><p> Redundancy</p></li><li><p> Rapidity</p></li><li><p> Resourcefulness</p></li><li><p> Robustness</p></li></ul><p>Network redundancy operates on the same principle as backing up your files <a href="https://www.rowse-automation.co.uk/blog/post/why-you-should-backup-your-plc" target="_blank" rel="noopener">or your PLC</a>: you set up a duplicate network, either physical or virtual, of your system hardware and connections. If you suffer an unexpected failure of a device or connection, you have a spare to take over its task and resume normal network operation. If you don’t have an effective redundancy backup or disaster recovery plan, you’ll suffer far more trouble getting your systems up and running again.</p><p>Redundant firewalls represent a common example of redundancy. These operate in both active and standby modes at the same time, by way of a primary firewall and a secondary backup unit. This backup unit remains in standby mode while at the same time monitoring the active primary firewall’s functional health. If it detects a failure in the active unit, the backup unit takes over, changing its status from standby to active.</p><p>Alternatively, you can set both units to operate actively, sharing equal responsibility for routing and enforcing <a href="https://medium.com/@RocketMeUpNetworking/best-practices-for-configuring-firewall-rules-6e0e89340e74" target="_blank" rel="nofollow noopener">firewall security rules</a>. If one unit goes down, the other unit continues to perform both its own tasks and those of the failed unit. </p><h2>Ethernet Switching Redundancy Protocols</h2><p>Another example of network redundancy is found in <a href="https://www.rowse-automation.co.uk/blog/post/understanding-industrial-ethernet-switching" target="_blank">industrial Ethernet switching</a>. In this scenario, any failure in the switching between links is covered by an alternative data path available in the redundant network. </p><p>For example, in a star topology, you have a single switch or hub forming the centre node of the star. This operates as a server to which every connected device or client node is linked. Any device in the network wanting to connect to another must first send its data to the star’s central node, the network switch, which sends the data on to whatever device is designated to receive it. </p><p>This means providing multiple paths from the central server node or network switch to the client nodes. But this has the obvious disadvantage of simultaneous failure of all connected nodes if the network switch fails, disabling network communication between multiple data centres. All single-path network designs are subject to this major drawback: failure of any aspect disrupts every type of network communication, whether it’s a disconnected cable, a power outage, or hardware failure.</p><p>To improve network redundancy, you can either add extra industrial switches or segments, or just use an altogether different topology, such as redundant rings, link aggregation or mesh. However, any computers that are exchanging data over a LAN that has redundant pathways may be subject to looping issues. This could eventually lead to a broadcast storm.</p><h2>Broadcast Storm</h2><p>Broadcast storms don’t happen so much these days, since the evolution of better quality and more robust Ethernet devices. They occur when a legitimate network is flooded with bogus frames, which disrupt the traffic of important frames to and from the network. This is often (but not always) caused by Ethernet device failure, improper network configuration, or malicious denial-of-service <a href="https://www.rowse.co.uk/blog/post/improving-cybersecurity-in-factories" target="_blank">cyberattacks</a>. </p><p>The problem is called a broadcast, because bogus frames go out to everyone, via a switch giving access to all ports. This is more avoidable now because switches are designed with broadcast storm protection. This recognises and suppresses suspiciously large transmissions of broadcast frames, preventing the bogus frames from spreading through the network. The switch protection resets once the threat has subsided so that normal traffic may resume. Most modern switches have this feature as a default setting, although there are some rare applications where broadcast traffic is expected, and you have to turn the protection off to permit it.</p><h2>Spanning Tree Protocols</h2><p>Network administrators have been figuring out for a long time how to avoid broadcast storms and break looping cycles. One of the most popular ways of doing this is the layer two <a href="https://www.geeksforgeeks.org/computer-networks/introduction-of-spanning-tree-protocol-stp/" target="_blank" rel="nofollow noopener">Spanning Tree Protocol (STP)</a>. This protocol blocks all the ports on a redundant network to prevent the occurrence of network loops. In such a network, it’s still possible for a single device to receive data when a port is blocked, but it can’t transmit that data to any other devices connected to the network. Any links not on the spanning tree are disabled, so that any two network nodes have only a single primary path of communication and one active channel between them. STP can circumvent network failures by rerouting data around the failed node so that connected devices can continue to communicate. </p><h2>Why Design A Redundant Ethernet Network?</h2><p>In our interconnected modern world, an industrial outage can have catastrophic effects, causing serious losses in production and profitability. According to recent research, manufacturers in the UK and Europe are estimated to lose at least £80 billion this year in unplanned downtime. While some of this is due to problems like equipment failure or supply chain delay, some 31% of manufacturers suffered a financial impact in 2024 from cyberattacks and other issues affecting OT/IT systems. </p><p>Resilient industrial networks can help prevent this costly downtime by restoring interrupted network functions: designing a redundant industrial network forms an important part of this resiliency. The goal of resilient network infrastructures is to achieve the “five nines” of network availability. This stands for a 99.999% goal of uninterrupted operation, equating in manufacturing terms to about six minutes of annual network downtime. Although this seems like an impossible target, designing a redundant industrial Ethernet network is a critical contributing factor.</p>

Network redundancy is one of the key strategies for achieving resilience, helping your network to provide uninterrupted services at an acceptable level. Such services include the efficient management of factory infrastructures and critical processes.

How Do You Design A Redundant Industrial Ethernet Network?

<h2 id="isPasted"><br /></h2><p>As industrial IoT deployments expand into remote and distributed environments, the challenge is not always how to process more data at the edge, but how to reliably collect it in the first place. Many sensing applications operate under strict constraints, including limited power, intermittent connectivity, and minimal infrastructure. This article explores an alternative approach to industrial sensing, focused on low-power, long-range data acquisition, where simplicity, reliability, and efficiency take priority over local intelligence.</p><h2>Not Every Sensor Needs to Be Smart</h2><p>Industrial sensing is often framed around edge computing, real-time analytics, and autonomous decision-making. These capabilities are critical in applications where latency must be minimized, and systems must react instantly to changing conditions.</p><p>However, a significant portion of sensing deployments operate under very different requirements. In remote environments such as pipelines, agricultural fields, water systems, and environmental monitoring sites, the primary challenge is not making decisions at the edge. It is ensuring that data can be captured and transmitted reliably from locations where infrastructure is limited or nonexistent.</p><p><span class="fr-img-caption fr-fic fr-dib"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1786656732160-Large+Long+Range+Satellite+Dishes.jpg" class="fr-fic fr-dib" alt="Large Long Range Satellite Dishes" /><span class="fr-inner">Large Long Range Satellite Dishes</span></span></span></p><p>These environments introduce constraints that fundamentally change system design. Power is often limited to batteries that must last for years. Connectivity may be intermittent, low bandwidth, or entirely dependent on long-range wireless technologies. Physical access for maintenance may be difficult or infrequent.</p><p>Under these conditions, complexity at the edge can become a liability rather than an advantage. The focus shifts from intelligence to efficiency, from processing to persistence, and from real-time control to reliable data acquisition.</p><h2>The Constraints of Remote Sensing</h2><p>Deploying sensors in remote environments requires careful consideration of power, connectivity, and system simplicity.</p><p>Power consumption is often the most critical constraint. Battery-powered devices must operate for extended periods without replacement, which requires minimizing energy usage at every stage of operation. This is typically achieved through aggressive power management strategies, where devices remain in low-power sleep states for the majority of their lifecycle and wake only at defined intervals to perform measurements and transmit data.</p><p>Connectivity presents a different challenge. Remote locations rarely have access to high-bandwidth networks, and even cellular coverage may be inconsistent. Low-power wide-area network technologies have emerged to address this gap, providing long-range communication with minimal energy consumption. These networks are optimized for small data payloads and infrequent transmissions, which aligns well with many sensing applications but requires a different approach to data handling.</p><p>Simplicity is equally important. Devices deployed in the field must be easy to install, configure, and maintain. Complex software, programmable logic, or frequent configuration changes can increase the likelihood of failure and make troubleshooting more difficult. In many cases, the most effective solution is one that performs a single function reliably over a long period of time.</p><h2>A Different Model for Industrial Sensing</h2><p>These constraints are driving a complementary model to traditional edge computing. Instead of processing data locally, systems are designed to efficiently collect and transmit data for centralized analysis.</p><p>In this model, sensor data is acquired at defined intervals rather than continuously streamed. Devices wake from low-power states, capture readings from connected sensors, and transmit that data using energy-efficient communication methods. Once the transmission is complete, the device returns to a low-power state, conserving energy until the next scheduled cycle.</p><p>Data acquisition methods vary depending on the sensor type and protocol. Analog inputs may require scaling and conversion, while digital inputs capture discrete states or pulse counts. Protocols such as Modbus introduce structured data that is typically accessed through periodic polling. Regardless of the source, the goal is to capture accurate data with minimal processing overhead at the device level.</p><p>This approach reduces power consumption, minimizes network usage, and simplifies device design. It also shifts data processing and analysis to centralized systems, where computational resources are not constrained.</p><p>In remote deployments, store-and-forward mechanisms are often used to ensure data reliability. If connectivity is temporarily unavailable, sensor readings can be buffered locally and transmitted once the connection is restored. This ensures that data continuity is maintained without requiring constant network availability.</p><h2>The Role of Low-Power Sensor Gateways</h2><p>Supporting this model requires a different class of device, one that prioritizes efficiency and reliability over local intelligence.</p><p>Low-power sensor gateways are designed to act as a bridge between field sensors and centralized systems. They provide the necessary interfaces to connect industrial sensors, while managing data acquisition and transmission in a way that optimizes power usage and communication efficiency.</p><p><span class="fr-img-caption fr-fic fr-dib"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1786956289154-Digi+Connect+Sensor+XRT-M+Diagram.png" style="width:100%px" class="fr-fic fr-dib" alt="Digi Connect Sensor XRT-M Diagram" /><span class="fr-inner">Digi Connect Sensor XRT-M Diagram</span></span></span></p><p>Devices such as the <a href="https://www.mouser.com/new/digi-international/digi-connect-xrt-m-sensors/" target="_blank">Digi Connect Sensor XRT-M</a> exemplify this approach. Rather than functioning as programmable edge controllers, these devices are optimized for long-term, low-power operation in remote environments. They spend most of their time in sleep mode, waking on a defined schedule to capture sensor readings and transmit them over long-range wireless networks.</p><p>By supporting common industrial interfaces and protocols, these platforms enable a wide range of sensors to be connected without requiring additional hardware. At the same time, their streamlined design minimizes energy consumption and reduces system complexity.</p><p>This architecture intentionally avoids unnecessary processing at the edge. Instead, it focuses on delivering accurate and timely data to centralized platforms, where it can be aggregated, analyzed, and acted upon.</p><h2>Real-World Applications of Remote Sensing</h2><p>This approach to sensing is particularly well suited to applications where data is collected over large geographic areas and does not require immediate local processing.</p><p>In energy and utilities, infrastructure such as pipelines, water systems, and substations often extends across remote regions. Sensors deployed in these environments monitor conditions such as pressure, flow, and temperature. Data collected at regular intervals provides visibility into system performance, while centralized analytics can identify trends and anomalies over time.</p><p>Agricultural applications also benefit from low-power sensing. Soil moisture, temperature, and environmental conditions can be monitored across large fields using distributed sensors. Long battery life and long-range communication allow these systems to operate throughout growing seasons without intervention.</p><p><span class="fr-img-caption fr-fic fr-dib"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1786656208702-Air+Pollution%2C+Weather+Monitor%2C+Wind+Information+Data+Collection+from+Sensor+Station+Outdoor.jpg" style="width:100%px" class="fr-fic fr-dib" alt="Air Pollution, Weather Monitor, Wind Information Data Collection from Sensor Station Outdoor" /><span class="fr-inner">Air Pollution, Weather Monitor, Wind Information Data Collection from Sensor Station Outdoor</span></span></span></p><p>Environmental monitoring systems rely on similar principles. Applications such as air quality measurement, water level tracking, and weather observation require reliable data collection from locations that may be difficult to access. In these cases, efficient data transmission and long-term operation are more important than local processing.</p><p>Smart infrastructure deployments, including transportation and urban utilities, often combine both centralized and distributed sensing. Low-power gateways can collect data from widely dispersed assets, feeding centralized systems that provide visibility and long-term analysis.</p><h2>Balancing Simplicity and Intelligence</h2><p>The evolution of industrial sensing is not defined by a single architectural approach, but by the ability to match the solution to the application.</p><p>In some cases, edge intelligence is essential. Systems that require immediate response or closed-loop control benefit from local processing and decision-making capabilities.</p><p>In other cases, simplicity provides greater value. When the primary goal is reliable data collection from remote assets, minimizing power consumption and system complexity becomes more important than adding processing capabilities at the device level.</p><p>Many real-world deployments combine these approaches. Intelligent edge systems handle time-critical processes, while low-power sensor gateways extend visibility into remote areas where traditional infrastructure is not practical.</p><p>Understanding where each approach fits is key to designing scalable and effective sensing systems.</p><h2>Conclusion</h2><p>Industrial sensing is often associated with increasing intelligence at the edge, but this is only part of the story. For many applications, especially those involving remote and distributed assets, the priority is reliable, efficient data collection.</p><p>Low-power sensing devices provide a practical solution by focusing on long battery life, efficient communication, and simple operation. By reducing complexity at the device level and leveraging centralized analytics, these systems enable organizations to extend sensing capabilities into environments that would otherwise be difficult to monitor.</p><p>Technologies such as the <a href="https://www.mouser.com/new/digi-international/digi-connect-xrt-m-sensors/" target="_blank">Digi Connect Sensor XRT-M</a> demonstrate how this approach can be applied in real-world deployments, providing a foundation for scalable, resilient sensing across a wide range of industries.</p><hr /><p><em><strong>Alistair Craven </strong>is <strong>Director of Sales Engineering for EMEA </strong>at <strong>Digi International</strong>, leading the technical sales team across Europe, the Middle East, and Africa. With an MSc in Software Development and a BEng (Hons) in Electrical and Electronic Engineering from Huddersfield University, he brings over 20 years of experience in connectivity solutions. Alistair began his career at Sarian Systems, a pioneer in cellular routers, and advanced through technical and leadership roles following Digi's acquisition in 2008. He now plays a key role in supporting customers, enabling sales, and guiding technical strategy across the region.</em></p>

Engineer Specialist Operating Pilot Drone on Wind Turbine Farm

Explore how low-power sensor gateways enable reliable, long-range data collection for remote and distributed industrial IoT assets.

Rethinking Industrial Sensing for Remote and Distributed Assets

A compact, battery-powered sensing platform that wirelessly brings environmental and equipment-condition data from locations where traditional monitoring is difficult or impossible.

Autosen Minion: A Customisable and Self-Sufficient IIoT Sensing Platform

Real-time water monitoring and leak detection just got streamlined thanks to the nRF9151 – Nordic's low-power cellular IoT solution

NOWi - Leveraging Nordic's cellular IoT solutions to detect pipe leaks and save water

<p id="isPasted">Europe and other regions have begun sunsetting 2G networks, and large-scale IoT deployments need a replacement connectivity solution before 2G goes dark. But replacing  2G fallback is not as simple as swapping in LTE-M (LTE for Machines) or NB-IoT (Narrowband IoT) with NTN (Non-Terrestrial Network) satellite fallback, because those standards don’t work for all applications and use cases. </p><p>Cat 1 bis is a 4G standard that sits squarely between narrowband IoT and full LTE options. With a single-antenna design, global availability, and lower cost than original Cat 1, Cat 1 bis is a powerful solution to replace legacy 2G fallback solutions used today. Fortunately, Nordic Semiconductor offers a Cat 1 bis platform that can take engineers from simple evaluation all the way through to a certified product.</p><h2>2G Devices Are Leaving A Gap</h2><p>When most IoT devices are designed for field lifetimes of 10 years or longer, obsolete connectivity or lack of supplier support can be a threat to service life. Unfortunately, upgrading to a new network is not as simple as flashing new firmware to the board. Instead, designers need new cellular hardware, new certifications, and a connectivity roadmap that holds up for the next decade.</p><p>The two most common replacements for 2G are LTE-M and NB-IoT, but both standards are meant for low-power, low-data-rate IoT applications. While many networks exist globally, LTE-M or NB-IoT are not currently available in all markets with 2G solutions. LTE-M tops out at 1 Mbps downlink, and NB-IoT has even less bandwidth, trading data rate for range and deeper indoor penetration. While many sensor or metering applications can work within those constraints, more sophisticated asset trackers or security cameras, for example, may need sustained multi-megabit throughput that exceeds those specifications. When application requirements outgrow LTE-M or NB-IoT, engineers have fewer options.</p><p>One alternative is LTE Cat 1. While the original standard delivered up to 10 Mbps over existing 4G infrastructure, it required dual-antenna MIMO (Multiple-Input Multiple-Output), which added complexity and costs that rendered it impractical for IoT deployments. Additionally, Cat 1 and higher LTE categories are optimized for downlink-centric use cases versus the typical uplink-centric data flow needed in most IoT deployments. </p><p>As a result, IoT engineers often face a trade-off between too little bandwidth or too much hardware.</p><h2>Cat 1 bis Offers a Better Option </h2><p>One powerful option for designers is Cat 1 bis, a 3GPP (3rd Generation Partnership Project) amendment to the original LTE Cat 1 standard. By dropping the MIMO requirement, Cat 1 bis unlocks single-antenna designs that reduce module size and bill of materials (BOM) costs compared to the original. And, with up to 10 Mbps downlink and 5 Mbps uplink rates, that reduced footprint still provides enough headroom for video streaming and responsive data exchange. </p><p>Another meaningful benefit of Cat 1 bis is its compatibility with existing global 4G infrastructure. As a result, engineers can leverage the standard to build a single hardware configuration that supports global deployment rather than maintaining separate regional variants for different network environments.</p><p>Even so, Cat 1 bis does not suit every application. For example, Cat 1 bis draws higher peak power than LTE-M and NB-IoT due to its inherent full-duplex radio configuration and complexity. Standards bodies and mobile network operators have also extended LTE-M and NB-IoT with NTN satellite options that extend beyond traditional terrestrial network footprints, providing those standards with better coverage in remote areas also as part of 5G. </p><p>Where deep indoor coverage or sub-1 Mbps data rates are sufficient, LTE-M or NB-IoT may deliver adequate performance at lower power consumption. But, for applications that genuinely require multi-megabit throughput, global 4G availability, and a compact single-antenna form factor, Cat 1 bis fills a gap that narrowband standards simply can’t match.</p><h2>Nordic Semiconductor's Cat 1 bis Platform</h2><p>To support Cat 1 bis deployments, Nordic Semiconductor offers its nRF93M1 Smart Modem module. A dedicated Cat 1 bis solution, the module simplifies hardware design and extends the bandwidth ceiling beyond their existing nRF9151 LTE-M / NB-IoT / NB-NTN offering. </p><p><span class="fr-img-caption fr-fic fr-dii"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1784310287216-lgNordic+nRF93M1.png" width="287" class="fr-fic fr-dii" style="width:515px;height:505.721px" /><span class="fr-inner">Product: nRF93M1. Source: Nordic</span></span></span></p><p>In an effort to simplify Cat 1 bis adoption, Nordic built the nRF93M1 around a single-antenna architecture, where the modem, RF front-end, and power management are all integrated into a single module with a feature set enabling optimized and robust designs. Nordic also built the nRF93M1 to support flexible SIM options, letting teams quickly choose and swap the best connectivity model for their specific deployment. </p><p>Thanks to this flexible and highly integrated architecture, the nRF93M1 offers low cost of ownership and a simplified solution for Cat 1 bis deployments with pin-compatible multi-regional and global SKU options.</p><p>Beyond connectivity, Nordic integrates nRF Cloud location services into the nRF93M1 to support asset tracking, covering low-power Wi-Fi positioning and cellular-based location. Fleet management, remote monitoring, and security teams can use these services to deliver location context and theft alerts alongside the connectivity payload. The nRF93M1 also features integrated observability features that let teams remotely monitor device and network parameters to identify performance issues without requiring a site visit. Long-term support is available through a CRA-certified firmware update solution, providing the compliance audit trail required to maintain IoT devices in the field.</p><p>And, to support development, Nordic offers the nRF93M1 Development Kit with pre-provisioned connectivity from <a href="https://onomondo.com/?utm_campaign=campaign_%7C_nrf93_release_0826&amp;utm_medium=media&amp;utm_source=Media_Supplyframe&amp;utm_content=nordic">Onomondo</a>. The kit features Nordic’s BLE nRF54L device as a host platform. Onomondo's non-steered SIM technology pairs with the nRF93M1 to ensure devices connect to the strongest available 4G network at each location, rather than being locked to a predetermined operator by roaming agreements, maximizing the power efficiency gains Cat 1 bis is designed for. This pre-provisioned connectivity approach is a true enabler for single-SKU global deployment: one hardware design, one SIM, and consistent coverage wherever LTE exists. </p><p>Backed with the open-source nRF Connect SDK, including reference designs, host application examples and pre-built support for standard IoT security protocols, Nordic’s AI-assisted development flow significantly reduces deployment risk and speeds up time to market. Teams get ongoing lifecycle support through maintained firmware, updated certifications, and security patches, so products shipped today can stay compliant without needing updated  hardware.</p><h1>A Practical Path for Long-Term Global Connectivity</h1><p>As 2G networks sunset throughout Europe and other regions, IoT product teams should consider Cat 1 bis as the connectivity solution for their next generation of hardware. With <a href="https://www.nordicsemi.com/Products/nRF93M1">Nordic’s nRF93M1</a>, designers can easily integrate Cat 1 bis into their next generation IoT deployments to keep them running today and be supported for decades to come.</p>

A Cat 1 bis platform that provides engineers with a practical path for long-term Global connectivity.

Nordic Semiconductor Makes the Case for Cat 1 bis in IoT

<p id="isPasted">The Internet of Things (IoT) has moved beyond early-stage pilots and proof-of-concept deployments. Today, connected devices support critical infrastructure across energy, logistics, mobility, and healthcare. In these and other sectors, IoT devices can operate for 10 to 20 years, often in remote locations or sealed environments where physical access is difficult or impossible.</p><p>Yet traditional connectivity models weren’t designed for this longevity, scale, or operational complexity. That’s especially true when tied to fixed Subscriber Identity Module (SIM) profiles. Earlier Embedded SIM (eSIM) standards helped, but traditional SIM provisioning locks devices into a single mobile network operator, creating:</p><ul><li><p>Vendor lock-in</p></li><li><p>High maintenance costs</p></li><li><p>Limited flexibility</p></li><li><p>Exposure to long-term risks as networks evolve</p></li></ul><p>The industry needed a standard that’s built specifically for the  operational realities of the IoT. SIM Group Protocol 32 (SGP.32), a global eSIM specification for IoT devices, is that standard. Developed by the GSM Association (GSMA), SGP.32 represents a foundational shift in how devices are connected, provisioned, and managed.</p><p>SGP.32 isn’t just a technical upgrade. It enables IoT devices to be managed like modern cloud infrastructure—remotely, securely, and at scale, even across global fleets. For organizations that are seeking a partner to implement it,<a href="https://www.gi-de.com/en/digital-security/connectivity-iot"> Giesecke+Devrient (G+D)</a> delivers a full‑stack, SGP.32‑native ecosystem and consolidates device management into a single pane of glass. </p><h2>IoT Has Outgrown Legacy Connectivity Models</h2><p>As IoT deployments scale, legacy SIM provisioning creates friction at every stage of the device lifecycle. Manual provisioning incurs high operational costs. Vendor lock-ins limit flexibility and negotiating power. There’s an inability to adapt to provider coverage changes, pricing shifts, and regulatory requirements. There are also long-term risks as networks sunset and new technologies emerge.</p><p>Earlier standards like SGP.02 allowed cellular network profiles to be securely downloaded and managed on embedded Universal Integrated Circuit Cards (eUICCs) without requiring physical SIM swaps. Yet they required costly onboarding and Short Message Service (SMS) integration. Consumer eSIM standards assume user interaction and short device lifespans, but neither applies to IoT.</p><p>As a result, many IoT deployments were static, rigid, and expensive to maintain. That’s changing because SGP.32 enables scalable, secure IoT connectivity, and G+D simplifies its management.</p><p><span class="fr-img-caption fr-fic fr-dii"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1782843802798-1782843802798.jpeg" width="624" height="249" class="fr-fic fr-dii" /><span class="fr-inner">SIM card on circuit board with electronic components. Source: AdobeStock.</span></span></span></p><h2>SGP.32: A Purpose‑Built GSMA Standard for IoT</h2><p>As the GSMA’s IoT-optimized eSIM Remote SIM Provisioning (RSP) Standard, SGP.32 is engineered specifically for IoT’s operational realities. It’s the first standard designed for IoT devices without a user interface, or that depend upon constrained, low-power hardware. SGP.32 also supports long operational lifetimes and large, globally distributed fleets.     </p><p>SGP.32’s key capabilities include:</p><ul><li><p>Secure remote profile download</p></li><li><p>Remote activation and deactivation</p></li><li><p>Operator switching without physical access</p></li><li><p>Lightweight protocols that work even with intermittent connectivity</p></li></ul><p>This makes SGP.32 fundamentally different from earlier approaches. SGP.32 removes the assumptions of user interaction, high bandwidth, or short device life. Instead, it enables zero‑touch provisioning and remote lifecycle control across millions of devices. For engineering teams, this means simpler integration, lower overhead, and a more predictable operational model.</p><h2>Why SGP.32 Matters: From Static to Dynamic Connectivity</h2><p>SGP.32 transforms connectivity from a one‑time static decision into a dynamic, remotely managed capability. It also reduces operational burdens, provides flexibility across global deployments, and supports future-proofing. There are benefits for IoT manufacturers, service providers, and end users.</p><h3>Remote Lifecycle Management</h3><p>SGP.32 lets organizations update connectivity profiles throughout the device lifecycle. It adapts to coverage changes or pricing shifts, responds to regulatory changes like roaming restrictions, and supports long-term deployments without hardware redesigns. Remote lifecycle management is especially critical for IoT devices in sealed enclosures, underground vaults, or remote industrial sites.</p><h3>Reduced Operational Burdens</h3><p>SGP.32 reduces the operational burden of field visits, manual maintenance, and downtime caused by connectivity issues. By reducing truck rolls, the dispatch of field technicians to customer locations, device manufacturers and service providers can reduce labor costs. Across large fleets, these savings can compound dramatically over time.</p><h3>Flexibility Across Global Deployments</h3><p>SGP.32 enables IoT devices to switch to the best local operator and avoid region-specific hardware variants. The benefits include more consistent behavior across markets and simpler manufacturing and logistics. This flexibility is essential as deployments scale globally and to millions of devices.  </p><h3>Futureproofing</h3><p>As networks evolve, SGP.32 ensures that IoT devices remain viable despite 2G and 3G sunsets, 5G rollouts, and shifting regulatory landscapes. Instead of replacing hardware, organizations can update connectivity profiles remotely. This extends device life and reduces total cost of ownership.</p><h2>The Architecture Behind SGP.32: eIM and IPA</h2><p>SGP.32 introduces a modern, cloud-aligned architecture built around two core components: the eSIM IoT Manager (eIM) and the IoT Profile Assistant (IPA). Together, they provide a secure, lightweight architecture that’s optimized for constrained IoT hardware with limited processing power, memory, or power. It also enables zero-touch provisioning and reduces integration complexity.  </p><h3>eIM (eSIM IoT Manager)</h3><p>The eIM acts as the central control for IoT connectivity and serves as the cloud orchestrator. It manages bootstrap connectivity, profile downloads, operating switching, and activations and deactivations. The eIM is designed for large-scale deployments of thousands or even millions of devices and enables centralized, over-the-air provisioning.  </p><h3>IPA (IoT Profile Assistant)</h3><p>The IPA is the on‑device or on‑SIM agent that executes commands from the eIM. It ensures secure communication and acts as the local executor. There are two IPA models: IPA on Device (IPAd) and IPA embedded in the eSIM (IPAe).</p><ul><li><p><strong>IPAd</strong> runs in the device operating system and offers greater control over how connectivity is managed. It’s ideal for devices with more capable processors or custom connectivity stacks.</p></li><li><p><strong>IPAe</strong> runs inside the eSIM or eUICC. It’s pre-certified for standard behavior and is ideal for constrained devices or simple architectures.</p></li></ul><h2><br /></h2><p><span class="fr-img-caption fr-fic fr-dii"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1782844055284-1782844055284.jpeg" width="624" height="312" class="fr-fic fr-dii" /><span class="fr-inner">Smart industrial park with connected warehouses. Source: AdobeStock</span></span></span></p><h2>SGP.32 Use Cases</h2><p>SGP.32 is not theoretical. It directly addresses real‑world challenges across utilities and smart metering, automotive and telematics, logistics and asset tracking, and industrial IoT and smart infrastructure.</p><h3>Utilities and Smart Metering</h3><p>Utility meters operate for 10 to 20 years in sealed or inaccessible locations. SGP.32 enables remote changes, long-term lifecycle management, and compliance with evolving regulations. Built-in fallback and switchback capabilities ensure meters automatically maintain connectivity by switching to backup networks when needed and returning to the primary network when available. This reduces maintenance costs and ensures meters remain connected throughout their lifespan.</p><h3>Automotive and Telematics</h3><p>Vehicles cross borders, roam across networks, and require consistent connectivity. SGP.32 supports seamless operator switching, global fleet consistency, and reduced warranty and service costs. <a href="https://www.gi-de.com/en/about-us/press/press-releases/giesecke-devrient-rivian-and-att-collaborate-to-bring-sgp32-and-5g-connectivity-to-rivians-r2-vehicle" target="_blank" rel="noopener noreferrer">Manufacturers can avoid in-person updates</a> while maintaining control over connectivity.</p><h3>Logistics and Asset Tracking</h3><p>Like vehicles, assets move across regions and among operators. SGP.32 enables dynamic, location-aware profile management. It also supports lower operational overhead, which is essential for global supply chains and high-value asset tracking.</p><h3>Industrial IoT and Smart Infrastructure</h3><p>Industrial IoT devices often operate in harsh environments with strict uptime requirements. SGP.32 ensures reliable long-term connectivity, remote lifecycle control, and reduced downtime. This supports factories, substations, and remote industrial sites.</p><p><span class="fr-img-caption fr-fic fr-dii"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1782843802812-1782843802812.jpeg" width="624" height="349" class="fr-fic fr-dii" /><span class="fr-inner">Security for Industrial IoT. Source: AdobeStock.</span></span></span></p><h2>Why G+D Is the Partner of Choice for SGP.32 Deployments</h2><p>SGP.32 is powerful, but even more so when it’s implemented by a partner that can deliver the full stack. G+D is uniquely positioned to help organizations realize the standard’s full value. In addition to eSIM hardware and eSIM management platforms, G+D offers connectivity services and SGP.32-native orchestration. All layers are aligned, ensuring predictable behavior and seamless integration.</p><h3>A Single Pane of Glass for IoT Connectivity</h3><p>G+D provides a unified interface for profile management, operator switching, fleet-wide monitoring, and security oversight. This single pane of glass for connectivity consolidates management for globally deployed connected devices. The benefits include reduced complexity, accelerated deployment, and simplified operations for engineering teams.</p><p>The eSIM IoT Manager (eIM) becomes the central interface for device identity, profile status, operator assignments, and lifecycle events. Devices ship with a bootstrap profile that provides minimal connectivity, and eIM uses that link to push the correct production profile once the device is deployed. Everyone works for the same interface instead of juggling multiple portals. </p><h3>End‑to‑End Ownership</h3><p>Hardware, software, and connectivity from a single provider means fewer integration points, clear accountability, and consistent performance across the entire stack. G+D’s approach is especially valuable for global deployments with strict reliability requirements.</p><h3>Future‑Proof Architecture</h3><p>In addition, G+D supports capability‑aware SIMs, next‑generation IoT deployments, and both IPAd and IPAe models. This ensures customers can adopt SGP.32 today while still preparing for tomorrow’s connectivity landscape.</p><h2>SGP.32 Is the Foundation for Scalable, Secure IoT Connectivity</h2><p>SGP.32 transforms IoT connectivity from a static, hardware‑bound decision into a dynamic, remotely managed lifecycle capability. It reduces operational costs, increases flexibility, and supports long‑lived deployments across industries. With G+D’s full‑stack, SGP.32‑native ecosystem, organizations gain a scalable, secure, future‑proof foundation for global IoT.</p><p>By <a href="https://pages.gi-de.com/global-iot-with-gd" target="_blank" rel="noopener noreferrer">partnering with G+D to implement SGP.32</a>, organizations can make connectivity an enabler instead of a constraint.</p>

The G+D Single Pane of Glass Delivers Secure, Remote, SGP.32-Driven IoT Management

How SGP.32 Enables Scalable, Secure IoT Connectivity

<p>The first half of 2026 has highlighted a marked shift in the perception of mobile. It is no longer just a smartphone in your pocket, mobile now represents an ecosystem of connected devices that include robots, wearables, extended reality, and vehicles that operate in real-world scenarios.</p><p>Right at the start of the year, we have seen the shape of things to arrive: One of the most visible examples of this shift was NVIDIA’s announcement at CES 2026 of the Isaac GR00T platform for humanoid robots.<sup>[1]</sup> Additionally, companies such as Hyundai and Boston Dynamics demonstrated the updated Atlas humanoid, with plans to deploy it in manufacturing plants by 2028.<sup>[2]</sup> Similarly, LG showcased the CLOiD robot, a seven-axis arm device designed for household chores.<sup>[3]</sup> The trend highlights how AI is pairing digital intelligence with physical action.<sup>[4]</sup></p><h2>Understanding Physical AI and Its Requirements</h2><p>To operate effectively in dynamic environments, these systems rely on physical AI. It generally involves the combination of AI models with sensors and actuators that enable robots or vehicles to act upon real-world environments.<sup>[5]</sup> For instance, in autonomous vehicles, physical AI uses cameras, lidar sensors, and AI mapping to adapt to traffic and weather for navigation.</p><p>For contextual awareness, which includes location, motion, and environmental conditions, AI systems require a continuous stream of sensor data. This contextual awareness must be maintained in real time to ensure safe and predictable behaviour.</p><p>To put this in perspective, a single autonomous mobile robot (AMR) or vehicle can generate upwards of 4 terabytes of data per day when high-resolution cameras, lidar, and telemetry are combined.<sup>[6]</sup> In the absence of reliable connectivity, AI models end up operating on outdated data, which may lead to performance issues and safety risks.</p><h2>Always-On Connectivity Is Not Optional</h2><p>The stakes are significantly higher when AI systems are physical. For instance, in a purely digital setting, a GPT model with outdated data might lead to errors in your article or presentation. In contrast, when AI is controlling a vehicle or robotic arm, lost connectivity can lead to delayed data, equipment damage or production downtime.  </p><p>This is why physical AI systems cannot rely on best-effort connectivity. In real-world deployments, even brief connection losses can compromise situational awareness, delay critical updates, and create blind spots across deployed IoT device fleets. That’s why, always on cellular connectivity essential for continuous monitoring, timely updates, and effective incident response.</p><p>The 2024 autopilot-related incidents involving Tesla serve as a reminder of how delayed sensor fusion can escalate into real-world risks.<sup>[7]</sup></p><p><span class="fr-img-caption fr-fic fr-dii"><span class="fr-img-wrap"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1782124981740-1782124981740.png" width="602" height="301" class="fr-fic fr-dii" /><span class="fr-inner">Always-on connectivity enables seamless and real-time interaction. Source: Kigen. </span></span></span></p><h2>The Role of Edge AI</h2><p>The industry standard for safe latency is under 10 milliseconds, while a typical cloud round trip could average 60–100 ms.<sup>[8]</sup> Edge AI addresses this gap by processing data locally, enabling immediate response and a more fluid, responsive user experience. </p><p>By keeping sensitive data on the device, edge intelligence also supports privacy by design, while allowing systems to adapt to individual users and environments for greater personalisation.</p><p>For instance, at CES 2026 ARM powered wearables demonstrated real-time health monitoring reducing cloud dependency.<sup>[9]</sup></p><p>That said, the connection to the cloud is still critical. It is just that its role has evolved. For example, if a person steps in front of an industrial robot, the edge AI will stop the robot immediately for the safety of the person. The connected cloud server, on the other hand, will process the incident data across the fleet and train the models to better recognize and avoid similar situations in the future.</p><p>The cloud becomes the layer for fleet level visibility and model training. Critical reactions happen at the edge, while insights learned across deployments continuously improve system performance over time.</p><h2>How eSIM Moves Control to the OEMs</h2><p>With fleets of physical AI devices on the rise, connectivity management becomes more critical than ever. In traditional SIM models, control mostly lies with network operators. IoT devices are often locked to a single carrier or a single region. This is not an ideal situation for OEMs deploying robots or vehicles across multiple countries. </p><p>The eSIM technology changes this dynamic by moving control from network operators to device makers. Earlier, changing a network operator for a fleet of vehicles or robots used to be a time-intensive task, as it involved downtime to physically swap SIMs. With integrated eSIM solutions, OEMs can switch operators with minimal friction.</p><h2>Clearing the Confusion Around eSIM</h2><p>In the industrial space, there is often confusion regarding eSIM. It is not a carrier plan in itself. eSIM, as its name suggests, is a digital yet hardware backed secure SIM (hardware part often is referred to as eUICC) that replaces the traditional removable SIM card with a programmable version. The difference is not what network you use, but how connectivity is managed across devices over their entire lifecycle through the assurance of security. This connectivity is enabled on the device as the eSIM now binds the unique identity of the device with a network, and can be allowed to switch over. The eSIM serves as the trust anchor: it’s primary function being security, and connectivity being secondary. This highlights how eSIMs play their role in autonomous systems that need to be secured from evolving cyber threats. Industrial robots and eSIM enabled devices remain operational for decades so remote programmability is essential to maintain connectivity.</p><p>Over the period of time, change in factors such as network, pricing, and performance may prompt OEMs to switch network operators. eSIM makes this transition easy by allowing users to securely download and activate network operator profiles. This capability also enables IFPP (in-factory profile provisioning) based on the region and requirements.<sup>[10]</sup> OEMs get the option of securely injecting mobile network profiles at the manufacturing stage. They can ship their products to different destinations network settings pre-configured for optimum coverage. As a result, manufacturers can reduce logistical complexity with one global SKU.</p><h2>Achieving Interoperability and Scale</h2><p>Unlike the prior eSIM standard such as M2M (SGP.02) that relies on complex SMS-based triggers, and single network integrations, the latest SGP.32 standard is purpose-built for IoT devices that have more constraints in memory available or may run on low-power networks. It offers eIM (eSIM IoT remote Manager), which allows for zero-touch provisioning of thousands of devices at once. It also supports iFPP (In-Factory Profile Provisioning), enabling profiles to be flashed during manufacturing.</p><p>Since SGP.32 is an open standard, designed with interoperability in mind, from the GSMA, the industry body of all mobile sector players, chipmakers and network providers are all building compatible solutions. This reduces the risk for OEMs of investing in a proprietary technology that might disappear down the line.</p><h2>Conclusion</h2><p>If you’re building physical AI, connectivity cannot be an afterthought. Cellular IoT offers the strongest globalised coverage, inclusive of satellite connectivity, far more suitable to protect IP that resides on the physical AI nodes with assurance of security and network availability. New eSIM standards such as GSMA SGP.32 shift connectivity upstream in the product lifecycle, enabling it to be designed in from the outset rather than bolted on after deployment.</p><p>By defining connectivity strategy early, teams can manage network profiles over the air, select local operators as devices move across regions, and support global deployment without increasing total cost of ownership. For physical AI systems that depend on continuous monitoring, updates, and safety controls, this approach delivers long-term resilience and control. With SGP.32 enabled tooling and in factory profile provisioning, connectivity is aligned with product vision from day one.</p><p>To dive deeper into how OEMs can build resilient, scalable connectivity strategies for physical AI, explore the ABI Research's report, developed in collaboration with Kigen:<a href="https://kigen.com/resources/white-papers/oem-iot-esim-guide/"> https://kigen.com/resources/white-papers/oem-iot-esim-guide/</a></p><hr /><h3>Resources:</h3><ol><li><a href="https://nvidianews.nvidia.com/news/nvidia-isaac-gr00t-n1-open-humanoid-robot-foundation-model-simulation-frameworks" target="_blank" rel="noopener noreferrer"> https://nvidianews.nvidia.com/news/nvidia-isaac-gr00t-n1-open-humanoid-robot-foundation-model-simulation-frameworks</a></li><li><a href="https://www.hyundai.com/worldwide/en/newsroom/detail/boston-dynamics-atlas-named-%2527best-robot%2527-in-best-of-ces%25E2%2584%25A2-2026-awards-by-cnet-group-0000001105" target="_blank" rel="noopener noreferrer">https://www.hyundai.com/worldwide/en/newsroom/detail/boston-dynamics-atlas-named-%2527best-robot%2527-in-best-of-ces%25E2%2584%25A2-2026-awards-by-cnet-group-0000001105</a></li><li><a href="https://www.lg.com/global/newsroom/news/home-appliance-and-air-solution/lg-electronics-presents-lg-cloid-home-robot-to-demonstrate-zero-labor-home-at-ces-2026/" target="_blank" rel="noopener noreferrer">https://www.lg.com/global/newsroom/news/home-appliance-and-air-solution/lg-electronics-presents-lg-cloid-home-robot-to-demonstrate-zero-labor-home-at-ces-2026/</a></li><li><a href="https://www.forbes.com/sites/ronschmelzer/2026/01/10/physical-ai-made-waves-at-ces-2026-what-is-it/" target="_blank" rel="noopener noreferrer">https://www.forbes.com/sites/ronschmelzer/2026/01/10/physical-ai-made-waves-at-ces-2026-what-is-it/</a></li><li><a href="https://www.ibm.com/think/topics/physical-ai" target="_blank" rel="noopener noreferrer"> https://www.ibm.com/think/topics/physical-ai</a></li><li><a href="https://medium.com/@autodriveai/autonomous-cars-will-collect-approximately-4-tb-of-data-every-hour-of-driving-3819aba33204" target="_blank" rel="noopener noreferrer">https://medium.com/@autodriveai/autonomous-cars-will-collect-approximately-4-tb-of-data-every-hour-of-driving-3819aba33204</a></li><li><a href="https://www.usatoday.com/story/money/legal/2025/06/24/tesla-lawsuit-autopilot-crash/84336338007/" target="_blank" rel="noopener noreferrer">https://www.usatoday.com/story/money/legal/2025/06/24/tesla-lawsuit-autopilot-crash/84336338007/</a></li><li><a href="https://www.omnitron-systems.com/blog/understanding-network-latency-and-its-impact-on-industrial-applications" target="_blank" rel="noopener noreferrer">https://www.omnitron-systems.com/blog/understanding-network-latency-and-its-impact-on-industrial-applications</a></li><li> <a href="https://www.arm.com/markets/consumer-technologies/wearables" target="_blank" rel="noopener noreferrer">https://www.arm.com/markets/consumer-technologies/wearables</a></li><li><a href="https://kigen.com/resources/white-papers/ifpp/" target="_blank" rel="noopener noreferrer">https://kigen.com/resources/white-papers/ifpp/</a></li></ol><h2 id="isPasted"><br /></h2>

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