Active Computing & AI Engineering

Imperial College of Science, Technology and Medicine and Tangi0 Limited KTP 24_25_R2

In plain English

AI plain-English summary

A single chip design will be embedded into a UK company to power the next generation of internet-connected devices, from traffic sensors to factory robots. This project addresses a fundamental bottleneck in the Internet of Things (IoT): the need for a chip that is both highly energy-efficient and flexible enough to handle vastly different tasks. Current chips often sacrifice performance for low power, or vice versa. The research will transfer specialised knowledge of FPGA (Field-Programmable Gate Array) design into a small company, Tangi0 Limited, enabling them to create a custom "hub chip" that can be reconfigured for specific applications without wasting energy. If successful, the chip could improve the sustainability and performance of smart city infrastructure—such as adaptive street lighting or air quality monitors—as well as industrial automation systems and local AI processing hubs. These are systems that quietly manage traffic, reduce energy waste, and keep factories running efficiently. The project is applied commercial research, not fundamental science; its direct goal is a market-ready product that makes connected devices cheaper, greener, and more adaptable.

View original technical description
To embed cutting-edge knowledge of FPGA design and optimisation to deliver an innovative IoT (Internet of Things) hub chip to provide a sustainable, high-performance, energy-efficient, and customisable solution for diverse IoT applications including smart cities, AI Hub, and industrial automation.

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Related Research

Grants with similar aims, by meaning.

University of Portsmouth Higher Education Corporation and Tangi0 Limited KTP 23_24 R4
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Buckinghamshire New University and Adam Equipment Co Limited KTP 24_25 R3
Cranfield University and Contexis Limited KTP 22_23 R5
Cycle London Cambridge

Original classification

Knowledge Transfer Partnership

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