Imagine your farm tractor driving itself while a drone scouts the field ahead, or a factory floor where machines from different vendors all talk to each other without a hitch — but a human expert can jump in anytime through a VR headset. That's what IntellIoT built: a way to run smart devices at the edge (not in some distant cloud) so they respond fast, stay private, and keep working even when the internet drops. They tested it in three real settings — agriculture with autonomous tractors and drones, hospitals with patient monitoring, and shared manufacturing plants — all coordinated by Siemens and 15 other partners across 9 countries.
By the numbers
EUR 7,997,615
EU funding for development
16
Partners in consortium
9
Countries involved
62%
Industry partner ratio
42
Total project deliverables
3
Tested use case sectors (agriculture, healthcare, manufacturing)
10
Industry partners
The business problem
What needed solving
Businesses in agriculture, manufacturing, and healthcare rely on IoT devices that send everything to the cloud — creating delays, privacy risks, and failures when connectivity drops. Running multiple vendors' equipment in one facility is a compatibility nightmare, and current systems don't let human operators step in seamlessly when AI gets it wrong. Companies need IoT that works reliably at the edge, integrates across vendors, and keeps humans in control.
The solution
What was built
The project delivered deployed and tested use case demonstrators (in both first and final versions) across agriculture (semi-autonomous tractor with drones), healthcare (sensor-based patient monitoring with virtual advisors), and manufacturing (shared multi-tenant automated plants). A total of 42 deliverables were produced, including a distributed AI system, 5G-enabled edge computing infrastructure, W3C WoT-based interoperability layer, and blockchain-based trust mechanisms.
Audience
Who needs this
Agricultural equipment manufacturers (John Deere, CLAAS, AGCO) wanting autonomous field operationsFactory operators running multi-vendor, multi-tenant production facilitiesHealthcare technology companies building remote patient monitoring platformsTelecom operators deploying 5G-enabled industrial IoT servicesSmart city integrators managing diverse IoT device ecosystems
Business applications
Who can put this to work
Precision Agriculture
enterprise
Target: Agricultural equipment manufacturers and large farm operators
If you are a farm operator or equipment maker struggling with unreliable connectivity in rural fields and the high cost of manual tractor operation — this project developed a semi-autonomous tractor-and-drone system that runs AI locally on the machines, not in the cloud. It was tested in real agricultural settings across a 16-partner consortium with Siemens as lead, producing deployed and tested demonstrators. The system uses 5G and edge computing so your equipment keeps working even when connectivity drops.
Smart Manufacturing
enterprise
Target: Factory operators running multi-tenant or shared production facilities
If you are a manufacturer dealing with the complexity of integrating machinery from different vendors into one automated plant — this project built a multi-agent IoT system based on W3C Web of Things standards that automatically resolves compatibility issues between devices. It was tested in a manufacturing use case where multiple tenants share equipment from third-party vendors, backed by 10 industry partners. Blockchain-based smart contracts provide transparency for all actions performed on shared machinery.
Remote Patient Monitoring
mid-size
Target: Healthcare providers and medical device companies
If you are a healthcare provider dealing with delayed patient interventions because sensor data has to travel to a distant cloud server — this project developed a distributed AI system that processes patient sensor data locally, enabling real-time advice from virtual advisors. The system was demonstrated and tested across 2 rounds of use case validation with 42 total deliverables. Privacy-sensitive health data stays on-site instead of being sent to external servers.
Frequently asked
Quick answers
What would it cost to implement this IoT system in our operations?+
The project had an EU contribution of EUR 7,997,615 across 16 partners over roughly 3 years. Deployment costs for an individual company would depend on scale and sector, but the technology uses open W3C Web of Things standards, which reduces vendor lock-in. Contact the coordinator (Siemens) for licensing and integration pricing.
Can this scale to industrial production environments?+
Yes — the manufacturing use case was specifically designed for highly automated plants shared by multiple tenants with third-party vendor equipment. The system was deployed and tested in demonstrators (first and final versions), and the consortium's 62% industry ratio (10 out of 16 partners are from industry) suggests strong orientation toward real-world deployment.
Who owns the intellectual property and how can we license it?+
IP is distributed across the 16-partner consortium led by Siemens AG. With 10 industry partners and 5 universities involved, licensing arrangements would need to be negotiated with the relevant IP holders. Siemens as coordinator is the logical first point of contact for commercial licensing discussions.
How does this handle connectivity issues in remote locations like farms?+
This is a core design feature. The system runs distributed AI directly on IoT devices at the edge, reducing dependence on cloud connectivity. It uses 5G infrastructure with dynamic resource management that optimizes network usage in a closed loop, keeping operations running even with unreliable connections.
Is the technology ready for deployment today?+
The project produced deployed and tested use case demonstrators in both a first and final version across all 3 sectors (agriculture, healthcare, manufacturing). The project closed in January 2024, and with Siemens leading, components may already be feeding into commercial product lines. Based on available project data, the technology has been validated in real environments.
What security measures are built in?+
The system includes integrated security assurance mechanisms and uses distributed ledger technology (blockchain) for smart contracts and action transparency. These run even on resource-constrained IoT devices. The architecture was designed with trust and privacy as core requirements, keeping sensitive data processing at the edge rather than in centralized clouds.
Does it comply with industry standards or is it proprietary?+
The system is built on W3C Web of Things standards for interoperability, which means it can work with equipment from different vendors without proprietary lock-in. The multi-agent architecture automatically resolves incompatibility constraints between devices, reducing integration headaches.
Consortium
Who built it
This is a heavy-hitting consortium led by Siemens AG, one of the world's largest industrial technology companies, with 16 partners across 9 European countries (AT, CH, CY, DE, DK, EL, FI, FR, NL). The 62% industry ratio — 10 industry partners alongside 5 universities — signals that this project was built for real-world deployment, not just academic papers. With only 2 SMEs, the consortium leans toward large established players, which increases the likelihood that results are being absorbed into existing commercial product lines. The geographic spread across Western and Northern Europe covers key manufacturing and agricultural markets. For a business looking to adopt this technology, Siemens as coordinator provides a credible, well-resourced commercialization path.
Want an introduction to the IntellIoT team at Siemens? SciTransfer can arrange a direct meeting with the right people — contact us for a matchmaking consultation.
