Findings use case Weed Robot

Findings use case Weed Robot

This content was created by the Data Sharing Coalition, one of the founding partners of the CoE-DSC.

Today, the Data Sharing Coalition presents a report on the most important findings of the Weed Robot use case where agricultural IoT data is shared across domains. In the agricultural industry, IoT data sharing use cases consist of different data services from scanning, analysing, and acting parties, which are combined to create value to an end user. This report consists of the use case design, insights on the context of the use case and insights on how the use case can be implemented in a scalable way to other use cases with similar roles.

Harmonisation of data services and a low- latency data exchange infrastructure are key

Through multiple workshops, KPN and the Data Sharing Coalition created a use case design (including a data sharing interaction model and an overview of business, legal, operational, functional, and technical requirements for sharing data) for sharing IoT data to combat ‘volunteer potato’, a specific type of weed.

In this use case, a Service Provider combines the data services of scanning, analysing, and acting parties to provide a simple and concrete service to a Farmer (e.g. a clean hectare of field with limited use of pesticide). For the ‘volunteer potato’ a robot drives across the land with cameras mounted on the front (scanning) and pesticide spot sprayers on the back to combat these weeds (acting). Therefore, realising an infrastructure that facilitates low-latency data sharing is essential to realising the use case. The KPN Data Services Hub, combined with their 5G network, provides an infrastructure which supports this low-latency data sharing.

To realise this use case, various data services need to be integrated (scanning, analysing, acting), which all adhere to differing rules and standards. This means that the Service Provider needs bespoke implementations for each data service, which is an inefficient and costly process. Harmonised multilateral agreements on various aspects of each data service (e.g. security, business model, authorisations) minimises these differences.

This use case is a first step towards many-to-many sharing of agro-robotic data

The use case is designed in such a way that it is generically applicable to other data sharing use cases that combine scanning, analysing, and acting parties. The main difference with these other use cases is the nature of the scanning, analysing, and acting data service: What raw data results from the scanning service, what analysis is performed on this data and what action is performed based on the instructions from the analysing service. This means that most of the design for this data sharing use case can be reused to enable other use cases, as long as agreements that apply specifically to a certain data service are modified (e.g. data standards, service level agreements, etc.). KPN is actively working on potential use cases based on this generic design, including emergency services and predictive maintenance.

More details on the findings can be found in the report.

Download the report

If you would like to get involved in the use case (e.g. as an agro-robot manufacturer or analysing party), please send us an email: info@coe-dsc.nl

Share:

Read more

Data sharing
From fragmentation to scalable value from data

How can we prevent the growing landscape of data spaces and data-sharing initiatives from becoming a source of fragmentation itself? The challenge is not to make everything the same, but to make conscious decisions about what can be reused, where harmonisation is needed, and where there should remain room for domain-specific choices.

From privacy to trust: what is needed to bring PETs to the next phase

Privacy Enhancing Technologies (PETs) make it possible to extract value from sensitive data without exposing the underlying information, but large-scale adoption remains limited despite successful pilots. According to Sarah van Drumpt (TNO) and Dave Buckley (OpenMined/UN PET Lab), the main challenge is no longer the technology itself, but creating the right conditions around governance, legal certainty and organisational readiness.

Hyperion: building data-driven collaboration for more sustainable aviation

According to Linda Bos, Director of the KLM Engineering & Maintenance Technology Hub, aviation cannot wait for new generations of electric or hydrogen-powered aircraft to become more sustainable. Through the Hyperion project, KLM and its partners are exploring how data sharing and collaboration can contribute to more sustainable and future-proof aircraft maintenance.

Is your business already working with data spaces?

Discover how secure data sharing can unlock new opportunities for organisations in the built environment. This sector-focused event explores the European Data Strategy, the role of data spaces, and practical approaches to trusted data sharing. Gain valuable insights, learn from real-world examples, and connect with experts driving innovation across the Dutch built environment.