Search results for: 'edge measur in acut'

The October 2025 edition of the CST Technology Opportunity Engine highlights transformative innovations shaping the future of edge computing. The study explores the evolution of decentralized data processing models that enable ultra-low latency, localized intelligence, and real-time decision-making across industries.Driven by the convergence of IoT...

The escalating compute and power demands of edge AI are exposing the limits of conventional von Neumann architectures. Manufacturers deploying always-on sensing, real-time inference, and autonomous decision-making at the edge are constrained by the energy, latency, and memory-bandwidth ceilings of standard NPUs and MCUs. Traditionally, edge AI work...

Quantum sensing is transitioning from laboratory research to industrial deployment, driven by the need for ultra-precise, reliable measurement in high-impact sectors such as healthcare, defense, and advanced manufacturing. This shift reflects a broader move from controlled, research-grade environments toward scalable, field-ready systems that meet ...

This study focuses on heterogeneous computing architectures for automotive and robotics applications, examining how centralized and zonal compute architectures, heterogeneous SoCs integrating CPUs, GPUs, NPUs, DSPs, FPGAs, and dedicated safety islands, as well as robotics edge-AI controllers and mixed-criticality computing platforms, are enabling t...

Micro-sensors are no longer just components that capture data—they are becoming the intelligence behind connected products and autonomous systems. As industries demand faster decisions, greater reliability, and continuous monitoring, sensing platforms are evolving by combining embedded AI, advanced materials, low-power design, and connected archite...

This Frost & Sullivan research service analyzes the global industrial automation market from 2020 to 2025, with 2020 as the base year. The deliverable offers an in-depth look at the dynamics influencing and challenging the growth of the industrial automation market and analyzes the process automation technology segments across process, discrete, an...

Multimodal sensor fusion is an advanced perception technology that combines data from multiple sensors, including cameras, LiDAR, radar, ultrasonic sensors, thermal cameras, and inertial measurement units (IMUs), to give robots and autonomous systems a more accurate, reliable, and comprehensive understanding of their environment. It overcomes the l...

The increasing volatility of global supply chains is driving interest in microfactories and distributed manufacturing. Manufacturers aim to improve production flexibility, reduce reliance on lengthy logistics routes, and enhance resilience in times of disruption. Traditionally, manufacturing networks have been optimized for centralized production, ...

This study examines the emerging landscape of neuromorphic computing and its role in enabling low-power, real-time, brain-inspired intelligence across edge and autonomous systems. It reviews advancements in spiking neural networks, memristor-based computing in memory, event-driven vision sensors, and hybrid neuromorphic and conventional architectur...