MyZubster Is Not Trying to Build Another App — We're Exploring a Verifiable Digital Ecosystem

MyZubster is not attempting to develop another standalone application; instead, the team is investigating the creation of a digital ecosystem that provides verifiable evidence. The architecture being explored connects various layers, including the real world, data, provenance, AI, evidence, and digital services. The goal is not to combine every conceivable technology into a single application, but rather to establish connections between these layers.

A key principle being employed is that artificial intelligence should not serve as the source of truth; instead, evidence should be the foundation for AI to interpret and verify information. This approach becomes particularly significant when applied to the Internet of Things (IoT). Collecting sensor data, such as soil measurements, water meters, weather data, field observations, and GPS information, is just the beginning.

Additional factors, like provenance (where, when, by which device, using which method, and who/what processed it) and reproducibility (can the calculation be reproduced?) must be considered. This allows raw measurements to be transformed into meaningful digital evidence. The concept of Measurement, Reporting, and Verification (MRV) is of growing interest.

A simplified pipeline might involve: REAL EVENT → MEASUREMENT → RAW DATA → PROVENANCE → PROCESSING → KPI → REPORT → VERIFICATION. This model has potential applications beyond environmental projects, including sustainability, circular economy, agriculture, digital identity, decentralized systems, IoT, supply chains, community contributions, and public-interest infrastructure.

The project is currently in the exploration phase, with no announcement of EU funding or a finalized consortium. MyZubster is actively developing, with code, repositories, prototypes, and architectural proposals in place. However, it is important to differentiate between these components and recognize that the project does not yet claim production status.

The focus remains on understanding what can realistically be measured and validated, and identifying environmental problems where the architecture can demonstrate useful results. Open-source principles extend beyond code inspection; developers, researchers, machines, and communities should all be able to examine the implementation, methodology, structured evidence, and reproducibility for trust.