Search results for: 'c2 farm comput'

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...

The study evaluates photonic and optical computing technologies as critical enablers of next-generation AI infrastructure, addressing growing bandwidth, latency, power consumption, and scalability constraints associated with copper-based interconnects. The analysis covers photonic integrated circuits (PICs), optical I/O chiplets, co-packaged optics...

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...

With the global population expected to reach 9 billion by 2050, the farming industry is under pressure to boost productivity. Digital solutions, encompassing autonomous farming equipment, real-time monitoring, and artificial intelligence (AI), are revolutionizing operations by diminishing manual labor reliance and improving efficiency. Farmers ackn...

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...

06 Sep 2017  |  North America  |  Market Research

Intelligence at the Edge—An Outlook on Edge Computing

Edge Computing Solutions will Redefine Analytics for Manufacturing OEMs

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Manufacturing, across the globe, is at the brink of a revolution. Advances in technologies are not only making manufacturing effective, but are enabling work to be “smarter”. The focus of this research on edge analytics is to analyse the industrial manufacturing market from a technology standpoint. The report could be extremely helpful to the...

AI maturity, implementation, and AI-enabled or AI-augmented operations are increasing year over year, moving from pilot to production. Because AI delivers the biggest business outcomes, it is a top outcome driver. The impact of AI can be seen in quality control and computer vision in smart manufacturing as well. AI-powered visual inspection transfo...

This study explores potential growth opportunities for robots in the agriculture industry. Driven by advancements in AI/ML, machine vision, and autonomous navigation, agricultural robots are executing tasks such as planting, weeding, harvesting, spraying, and crop monitoring with greater precision and efficiency. Designed for workforce augmentation...

The Advanced Manufacturing Technology Opportunity Engine provides profiles of innovations related to autonomous mobile robots (AMRs) enabling pallet and trolley transportation across dynamic intralogistics environments; compact 6-axis robotic systems supporting modular and flexible laboratory automation; autonomous agricultural unmanned ground vehi...