Search results for: 'software revenue model'

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...

Disruptive AI models are increasingly challenging traditional assumptions about “classic” cloud data centers. As training clusters scale up to thousands of accelerators and consume tens of megawatts of power, the conventional CPU-centric, air-cooled, monolithic server model is no longer sustainable. This research study explores the megatrend of AI ...

Energy harvesting sensor solutions are emerging as a foundational layer for large-scale ambient IoT, enabling autonomous, battery-free sensing across distributed and infrastructure-intensive environments. By converting ambient energy sources such as light, heat, vibration, and RF into usable power, these sensors eliminate the need for wired power a...

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...

The edge AI accelerator market is scaling rapidly as industries demand low-latency, privacy-aware intelligence for autonomous vehicles, industrial automation, smart cameras, robotics, and other applications. Cloud-based inference faces more limits from bandwidth, latency, and data sovereignty concerns, creating a strong pull for on-device AI proces...

Real-time location solutions (RTLS) provide accurate information on the location of materials, goods, assets, persons, or vehicles. The system includes tags, readers, and a software solution. This study covers different RTLS technologies that assets send radio signals to, such as wireless fidelity (Wi-Fi), RFID, ultra-wideband (UWB), Bluetooth Low ...

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...

24 Jul 2024  |  Global  |  Technology Research

Radar R&D Portfolio Assessment and Opportunity Analysis

Millimeter-Wave Radar and Radar-on-Chip Solutions are Driving Market Growth

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Radar technology will experience rapid growth because of improvements in enabling technologies and growing demand in the automotive, defense, aerospace, consumer electronics, manufacturing, and energy industries. The technology has diverse applications and use is expanding with the adoption of IoT devices and penetration of 5G technology. The lo...

The additive manufacturing sector has seen significant growth in recent years owing to growing demand for customized products and complex geometries in various sectors, including automotive, defense, aerospace, consumer electronics, manufacturing, and energy. AI has a wide range of applications in additive manufacturing at various levels and is a k...