SciTransfer
Organization

LIGHTRICITY LTD

Oxford deep-tech SME developing self-powered miniaturised sensors using photovoltaic energy harvesting for industrial IoT and smart-city applications.

Technology SMEdigitalUKSMENo active H2020 projectsThin data (2/5)
H2020 projects
2
As coordinator
1
Total EC funding
€631K
Unique partners
7
What they do

Their core work

Lightricity is an Oxford-based deep-tech SME specialising in photovoltaic energy harvesting and power management electronics for miniaturised, battery-free or battery-assisted wireless sensors. Their core technology converts ambient light into usable electricity at the micro-watt scale, enabling autonomous IoT devices that require no external power source or frequent battery replacement. They design complete sensor systems — from the PV harvester and power management circuit through to edge intelligence and communication — targeting environmental monitoring, industrial asset tracking, smart homes, and smart cities. In EU projects they contribute as both technology developers and systems integrators, bridging hardware miniaturisation with real-world deployment scenarios.

Core expertise

What they specialise in

Photovoltaic energy harvesting for IoTprimary
2 projects

Both AMANDA and MEANINGFUL centre on PV-based energy harvesters enabling self-powered miniaturised sensors, reflecting Lightricity's core commercial technology.

Miniaturised autonomous sensor systemsprimary
2 projects

AMANDA explicitly targets autonomous self-powered miniaturised intelligent sensors for environmental sensing and asset tracking at multi-year scale.

Power management electronicsprimary
1 project

AMANDA keywords include 'power management electronics' and 'rechargeable battery', indicating expertise in low-power circuit design for energy-constrained devices.

Edge intelligence for sensingsecondary
1 project

AMANDA lists 'edge intelligence' as a keyword, suggesting on-device processing capability integrated into their sensor platform.

Smart city and industrial IoT applicationssecondary
2 projects

MEANINGFUL targets industrial, global retail, and smart-city applications; AMANDA covers environmental sensing and asset tracking across the same deployment contexts.

Evolution & trajectory

How they've shifted over time

Early focus
PV-powered miniaturised autonomous sensors
Recent focus
No later-period data available

Lightricity's entire H2020 portfolio falls within a single year (2019), so a meaningful chronological shift cannot be established from this data alone. Both projects address the same core theme — miniaturised, self-powered sensors using PV energy harvesting — with MEANINGFUL (SME Phase 1 feasibility, €50k) likely preceding or running alongside AMANDA (RIA, €580k) as a proof-of-concept that justified the larger collaborative project. All keywords cluster in that founding period, suggesting the company entered EU funding with an already well-defined technology thesis rather than evolving through successive projects.

Based on available data, Lightricity is on a trajectory from feasibility validation (MEANINGFUL, SME-1) toward full system integration in larger collaborative research (AMANDA), suggesting growing ambition to productise their energy-harvesting sensor platform for industrial and smart-city markets.

Collaboration profile

How they like to work

Role: specialist_contributorReach: European6 countries collaborated

Lightricity operates both as consortium leader (MEANINGFUL) and as a specialist partner (AMANDA), indicating flexibility depending on project scale. With only 7 unique partners across 2 projects, they work in lean, focused consortia rather than large multi-stakeholder networks. This profile is typical of a technology SME that joins collaborations to validate and de-risk a specific proprietary technology, contributing depth in a narrow but critical area.

Lightricity has worked with 7 unique partners across 6 countries, a modest but internationally spread network for a two-project SME. The geographic spread across 6 countries suggests they actively seek complementary partners beyond the UK, likely pairing their hardware expertise with academic or systems-integration partners from continental Europe.

Why partner with them

What sets them apart

Lightricity occupies a rare niche at the intersection of photovoltaic micro-energy harvesting and intelligent miniaturised sensing — a combination that most IoT hardware firms or academic groups tackle only in part. As an Oxford-based deep-tech SME, they offer the agility of a startup with the rigour needed for EU collaborative research, and their participation in both a Phase 1 feasibility study and a multi-year RIA in the same year suggests they can operate across the full commercialisation readiness spectrum. For consortium builders, they are a credible provider of the "self-powered sensing node" component that many smart-infrastructure projects need but few partners can supply end-to-end.

Notable projects

Highlights from their portfolio

  • AMANDA
    The largest project by far (€580,625, 2019–2022) and their most technically ambitious, aiming to deliver a fully autonomous, self-powered miniaturised sensor integrating PV harvesting, edge intelligence, and wireless communication for environmental and asset-tracking use cases.
  • MEANINGFUL
    Notable as the project where Lightricity served as coordinator — an SME Phase 1 grant (€50k) that validated the commercial and technical feasibility of their energy-harvesting sensor concept across industrial, retail, and smart-city verticals.
Cross-sector capabilities
environment (autonomous environmental monitoring sensors)manufacturing (industrial asset tracking and predictive maintenance)smart cities and infrastructure (batteryless sensing nodes for urban deployments)
Analysis note: Only 2 projects, both starting in 2019, with no later-period keyword data available. The expertise profile is internally consistent and credible, but cannot assess how the organisation has evolved since 2019 or whether they have pursued additional R&D activities outside H2020. Confidence is limited by sample size, not by data quality within what exists.