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u-blox introduces the F11 platform for ultra-low power meter-level GNSS

Tue, Mar 10, 2026

u-blox has announced the launch of the u-blox F11 platform. The new L1/L5 dual-band standard-precision GNSS platform is designed to improve positioning accuracy while reducing power consumption to as low as 7 mW in typical configurations using Low Energy Accurate Positioning (LEAP) mode for tracking and wearable applications.

The u-blox F11 platform marks a step forward in meter-level GNSS positioning, combining ultra-low power operation with intelligent signal management to meet the evolving demands of tracking, wearables, telematics and mobility applications – including micromobility solutions and drones – as well as other industrial use cases. The platform enables device manufacturers to achieve longer battery life, faster and more reliable position fixes, and greater design flexibility.

Expanding power saving capabilities, the u-blox F11 platform is a new situationally aware GNSS architecture (with integrated geofencing and indoor detections) that dynamically balances accuracy and power consumption. By selectively using dual-band L1/L5 operation only when it helps maintain the positioning performance, u-blox F11 platform reduces energy use while providing resilience and maintaining confidence in location data.

Compared to previous generations, the platform delivers up to 40% lower power consumption during signal acquisition and up to 30% lower power consumption in continuous tracking modes, while improving position accuracy by up to 30% in challenging environments such as dense urban areas. For long-life tracking applications (assets, livestock, pets, and people), optimised first-fix performance further reduces GNSS on-time, enabling multi-year battery operation.

The platform supports both single-band and dual-band operation within a single footprint, allowing device manufacturers to simplify designs and scale products across multiple market segments.

Key application areas include:

Asset and fleet tracking
Consumer and fitness wearables
Aftermarket telematics
Livestock tracking
People/pet tracking
Industrial sensing and IoT
Micromobility and mobility services
Consumer drones and action cameras

u-blox.com

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Intel expands Edge AI portfolio with Core Series 2 Processor

Tue, Mar 10, 2026

Intel has launched the Intel Core processor Series 2 with P-cores, an industrial-ready platform engineered for mission-critical edge applications. Intel also announced its latest Edge AI suite for Health & Life Sciences, providing validated reference pipelines and benchmarking tools for AI-powered patient monitoring solutions.

Intel Core Series 2 processors address the critical challenges facing modern industrial operations, which demand processors that can handle multiple critical workloads simultaneously—from safety-critical control systems to real-time data processing—all while maintaining precise timing and deterministic performance.

Traditional processors often force manufacturers to choose between computational power and real-time reliability, leading to complex multi-processor architectures that increase costs and system complexity. Intel Core Series 2 processor take these challenges head-on.

Intel previewed its Health & Life Sciences AI Suite, focused on AI-enabled patient monitoring. As healthcare systems face growing patient volumes and staffing constraints, patient monitoring is evolving from isolated devices to intelligent, connected ecosystems that demand AI-enabled solutions for earlier insights and reliable real-world operation. The suite showcases concurrent, multimodal workloads running locally on Intel processors—including AI-based electrocardiogram (ECG) arrhythmia detection, remote photoplethysmography, and anonymous 3D visual tracking—helping original equipment manufacturers (OEMs), original design manufacturers (ODMs), and independent software vendors (ISVs) evaluate platforms using representative scenarios rather than synthetic benchmarks.

Together with the recently launched Core Ultra Series 3 processors, Intel Core Series 2 processors with P-cores and the new Health & Life Sciences Edge AI Suite demonstrate Intel’s edge portfolio that addresses the full spectrum of customer requirements—from deterministic real-time control to advanced AI acceleration—enabling faster innovation across manufacturing, healthcare, and emerging edge applications.

intel.com

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TI expands MCU portfolio and software ecosystem to enable edge AI in every device

Tue, Mar 10, 2026

Texas Instruments has introduced two new microcontroller (MCU) families with edge artificial intelligence (AI) capabilities, supporting the company’s commitment to enabling edge AI across its entire embedded processing portfolio. The MSPM0G5187 and AM13Ex MCUs integrate TI’s TinyEngine neural processing unit (NPU), a dedicated hardware accelerator for MCUs that optimises deep learning inference operations to reduce latency and improve energy efficiency when processing at the edge.

TI’s embedded processing portfolio is supported by a development ecosystem, including the CCStudio integrated development environment (IDE). Its generative AI features allow engineers to use simple language to accelerate code development, system configuration and debugging through industry-standard agents and models paired with TI data. Altogether, TI is accelerating the adoption of edge AI in any electronic device, from real-time monitoring in wearable health monitors and home circuit breakers to physical AI in humanoid robots. These end-to-end innovations are featured in TI’s booth at embedded world 2026, March 10-12, in Nuremberg, Germany.

Consumers are always looking for everyday technology to be more intelligent, from fitness wearables to home appliances and electrical systems. However, many engineers believe that AI capabilities are exclusive to higher-end applications given high costs, power demands and coding requirements. TI’s new MSPM0G5187 Arm Cortex-M0+ MSPM0 MCU represents a fundamental shift for embedded designers, who can now bring edge AI to a wide range of simpler, smaller and more cost-effective applications.

With local computation, the TinyEngine NPU executes computations required by neural networks in parallel to the primary CPU running application code. Compared to similar MCUs without an accelerator, this hardware acceleration:
• Minimises the flash memory footprint.
• Lowers latency by up to 90 times per AI inference.
• Reduces energy utilisation by more than 120 times per AI inference.

Motor control applications in appliances, robotics and industrial systems increasingly call for intelligent features such as adaptive control and predictive maintenance, but implementing these capabilities has historically required complex, multi-chip designs. TI’s new AM13Ex MCUs are the industry’s first to integrate a high-performance Arm Cortex-M33 core, TinyEngine NPU and advanced real-time control architecture into a single chip.

This degree of integration enables designers to implement sophisticated motor control and AI features simultaneously without external components, lowering bill-of-materials costs by up to 30%. Key enhancements include:
• The ability to maintain precise real-time control loops for up to four motors while the TinyEngine NPU runs adaptive control algorithms for load sensing and energy optimisation.
• An integrated trigonometric math accelerator that performs calculations 10 times faster than coordinate rotation digital computer (CORDIC) implementations, delivering more precise, responsive motor-control performance.

Both MCU families are supported by TI’s CCStudio Edge AI Studio, a free development environment that simplifies model selection, training and deployment across TI’s embedded processing portfolio. This edge AI toolchain gives engineers full flexibility to run AI models on TI MCUs through either hardware or software implementations. Today, there are more than 60 models and application examples available in the tool to help developers start deploying edge AI in any device, with additional tasks and models planned in the future.

www.ti.com

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NXP’s new i.MX 93W fuses edge compute and secure wireless connectivity

Mon, Mar 09, 2026

NXP Semiconductors has announced the i.MX 93W applications processor, expanding NXP’s i.MX 93 family. Purpose-built to accelerate physical AI deployment, the i.MX 93W SoC is the industry’s first applications processor to combine a dedicated AI neural processing unit (NPU) with secure tri-radio wireless connectivity. This high degree of integration allows customers to replace up to 60 discrete components with a single package. Pre-certified reference designs eliminate many common integration challenges, reducing the complexity, cost and risk traditionally associated with RF design. Supported by NXP’s software and industry-leading eIQ AI enablement solutions, the i.MX 93W also supports smaller form factors and is designed to accelerate time-to-market for physical AI applications.

Physical AI requires coordinated AI agents to collaborate locally, taking real-time action with low latency and high reliability. For example, AI agents might coordinate across a smart building’s lighting, HVAC, access control, occupancy and smart energy systems to autonomously optimise comfort, energy efficiency, and operational responsiveness securely in real time.

NXP’s new i.MX 93W addresses this need by integrating scalable edge compute, AI acceleration, and secure wireless connectivity in a single package, supported by NXP’s software, eIQ AI enablement and pre-certified reference designs. This allows coordinated AI agents to locally manage physical environments, such as a group of healthcare agents working together to coordinate wearables, smart diagnostics, sensors and health gateways that deliver real-time healthcare insights and actions. The highly integrated i.MX 93W SoC also allows customers to rapidly scale physical AI across healthcare devices, smart building controllers, industrial gateways, energy infrastructure monitors and smart home hubs.

The i.MX 93W applications processor combines a dedicated AI NPU with secure tri-radio wireless connectivity in a single package. This eliminates the need for up to 60 discrete components, significantly reducing board area, design and supply chain complexity and system-level costs. The i.MX 93W features a dual-core Arm CortexA55 applications processor with a dedicated Arm Ethos NPU capable of up to 1.8 eTOPs. The integrated IW610 tri-radio combines Wi-Fi 6, Bluetooth Low Energy, and 802.15.4 connectivity supporting Matter and Thread deployments. This eliminates complex RF tuning steps and coexistence challenges that traditionally slow development and certification, speeding time-to-market.

The i.MX 93W SoC integrates an EdgeLock Secure Enclave (Advanced Profile), addressing regulatory requirements, including European Cyber Resilience Act (CRA). The embedded EdgeLock Secure Enclave is a hardware root of trust simplifying implementation of security-critical functions like secure boot, secure update, device attestation and secure device access. Combined with NXP’s EdgeLock 2GO key management services, OEMs can securely provision i.MX 93W SoC-based products at device manufacturing or in the field.

NXP’s pre-certified i.MX 93W SoC-based single and dual-antenna reference designs minimise RF tuning effort and eliminating many common integration challenges. Certified across multiple countries and regions, these reference designs reduce the complexity, cost and risk traditionally associated with RF design and wireless certification. By leveraging validated antenna options and pre-approved designs, customers can shorten regulatory approval timelines, reduce development cost, and bring products to market faster.

nxp.com

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u-blox introduces the F11 platform for ultra-low power meter-level GNSS

Intel expands Edge AI portfolio with Core Series 2 Processor

TI expands MCU portfolio and software ecosystem to enable edge AI in every device

NXP’s new i.MX 93W fuses edge compute and secure wireless connectivity

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