Edge & Computing

projects

member of:

red riscv Nvision
microprocessors for Iot

NVISION performs research and development on Edge Computing and provide System-On-Chip solutions.

  • RISC-V Architectures: We customize the best architectures for specific applications.
  • AI Accelerators: We develop AI accelerator chips that operate stand alone or linked with a RISC-V architecture.
  • EDA Tools: We select, customize, and develop tools to map AI algorithms to RISC-V accelerators.
  • Algorithm Optimization: We mathematically optimize algorithms at software level for to implement the best hardware strategies.
  • Quantum Computing: We work on toolsets that provide developers the capability to harness the power of Quantum Computing for accelerating code fragments.

 

Our team is composed of experts on Edge Computing, High Performance Computation, Parallel Processing, Numerical Modelling, IC Design Flow, RISC-V, Artificial Intelligence, IoT, and Operating Systems, building solutions in applications such as Digital Health, Samrt Cities, Smart Energy, Industry 5.0, and Computer Vision.

• projects •

A-IQ READY

EC/MINCOTUR

Cutting-edge quantum sensing, edge continuum orchestration of AI and distributed collaborative intelligence technologies to implement the vision of intelligent and autonomous electronic components and systems in the digital

BUILDMA

MICINN

Building intelligent Management System, based on edge computing and explainable AI, that will be designed and validated by conducting a pilot test in a real environment. Estimates and predictions will be recommended to users following a social computing approach, maximizing indoor comfort, and adapting to changing patterns.

core one

European Commission

Use of graphene sensor networks in Ambient Assisted Living environments to detect human activities, and integration into a monitoring system to feed AI and decision support algorithms

edge

European Commission

Monitoring of Activities of Daily Living (ADL) of elders living alone at home, using gas sensors and applied AI to design identification algorithms through ML techniques