IVA’s 100 List 2019-2024

Between 2019 and 2024, IVA’s 100 List was published annually to shine a spotlight on cutting‑edge research with the potential to create real value — whether through commercialisation, new business and methods, or positive societal impact. In 2026, an enhanced and updated version of the list will be launched.

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Reconfigurable 6G Quality of Service (QoS) and Edge Integration for Robotics and Automation

The 5G cellular technology is being increasingly utilized in many industrial applications. An important functionality is the advanced Quality of Service (QoS) feature. Despite the research in 5G QoS, there is notable absence of real-life industrial research directions and implementations.

Deep tech
Luleå University of Technology
2024
Saphai machine against a gray background

AI enabled Data Driven Change Detection

Our solution represents a comprehensive suite of multisensory visual sensors designed to gather data from diverse sources, including robotized missions, pre-existing legacy traffic systems, and even human activities.

Smart industry
Luleå University of Technology
2024
Energy measurement showing 100%

aktor-e: 1-Click Energy Optimization for Factories

aktor-e aims to equip manufacturing factories with a one-click energy optimization mode. In prior research, we have shown that intelligent control can run manufacturing machines up to 30% more energy-efficiently.

Smart industry
Chalmers University of Technology
2024

SmartBrain — Batteries with dynamic reconfiguration

In our project, we’re pioneering a new way to make batteries smarter, longer-lasting, and more efficient through Dynamically Reconfigurable Battery Systems (DRBS). DRBS addresses common battery issues like uneven cell wear, limited flexibility, and wasted energy.

Smart industry
Chalmers University of Technology
2024
Smart sensors, Artificial Intelligence, Energy storage, Electromobility, Safety, Charging, Cost, Lifetime.

AI and Smart Sensors for Advanced Batteries

As a key technology for electromobility and renewable energy storage, batteries remain costly and face risks of thermal runaway and premature degradation. To tackle these critical challenges, this project develops advanced battery management algorithms by leveraging interdisciplinary knowledge, novel sensors, big data, and artificial intelligence.

Deep tech
Chalmers University of Technology
2024

Infininode - IPs for high-performance, scalable SoC solutions

The memory subsystem in a microprocessor is crucial for scaling the performance/watt of future computing devices. To be efficient, every part of the memory subsystem must be highly optimized, most notably the multi-level cache hierarchy and networks-on-chip.

Deep tech
Chalmers University of Technology
2024
Shows the process for how lithium batteries can be recycled more efficiently.

Circular batteries recycling via green chemistry

Spent Li-ion batteries contain valuable metals such as lithium, cobalt, manganese, nickel, aluminium and copper. Some of these metals are not mined in EU and we depend on their import. Thus, we are obligated to recover them from the waste via sustainable recycling.

Circular economy
Chalmers University of Technology
2024
A qubit

Near-Quantum-Limited Broadband Microwave Amplifiers

In 2023, global public investment in quantum technology reached $42 billion, highlighting immense expectations for quantum computers to revolutionize industries. A critical barrier to building large-scale superconducting quantum computers is achieving near-noiseless qubit readout; without quantum-limited amplifiers, signals become too noisy, degrading performance.

Deep tech
Chalmers University of Technology
2024
Layer Logic's solution, graphene bioscenscors.

Graphene biosensors for speedy detection of pathogens

We have developed novel, scalable graphene-based biosensors that can detect any pathogen within minutes. The food industry’s pathogen detection market is nearly $22 billion but lacks reliable rapid testing methods.

Deep tech
Chalmers University of Technology
2024

Microsampling technology for painless and patient-centric diagnostics

Blood sampling in hospitals via venipuncture is standard for diagnostics, but has a series of drawbacks. Meanwhile, new medical trends are emerging: moving towards decentralized point-of-care applications, shifting from curative to preventive care, exploration of untapped biological information and improved outcomes via personalized medicine. All enabled by advanced analytical tools and sample collection methods.

Deep tech
KTH Royal Institute of Technology
2024

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