Drone Data Analytics Library

An open-access repository

In the European Project ICAERUS we are working on a Drone Data Analytics Library (DDAL). We envision this library as an open-access repository of the most significant existing and emerging drone data analytics models and algorithms. Analytical models of UAVs are often published behind closed doors, or completely developed in-house. This limits wider adoption, evaluation and further optimisation of the insights these models can provide.

As the UAV domain can be quite broad when it comes to models. We have chosen to focus on a wide array of analytics-implementations of UAV applications. This can range from Photogrammetry, Statistical models, UAV spraying simulations, Machine Learning/Deep Learning Algorithms, or even Vegetation Indices calculation, fleet management optimisation algorithms and Travelling Salesman Problem. Additionally datasets are also seen as an essential part in sharing and collaborating of UAV analytical applications.

Available now
at github and Zenodo

The beginning of this library is available at the following location:

Furthermore, there are already a few openly available datasets at the ICAERUS zenodo:

These datasets are also tracked in the following GitHub repository:

We invite anyone to explore the library, and the various models and implementations. From re-using datasets, adapting code-implementations or copying analytics implementations for a different application. It is code and data, and it is openly available: so use it!

The library is currently being populated from existing work from the five Use Cases that are part of ICAERUS. However, we also welcome outside contributions to this library. Through GitHub anyone can become a member of the ICAERUS organisation and contribute to this library, first steps can be found at the github homepage.

The ICAERUS DDAL is also automatically linked to the ICAERUS Platform.

This platform makes it easy to find different models and datasets. The library gives access to cutting-edge models and algorithms. analytics. This can be valuable for enhancing their own research or applications. Participation also opens doors for collaboration with the initiative’s stakeholders. By contributing models, algorithms, and techniques to the library, individuals and organisations can accelerate the overall progress of research and development in the field. Contributing to the library also allows individuals and organisations to share their expertise and knowledge with a broader community. This collaborative approach fosters a culture of knowledge exchange and learning from one another.

Drone Stakeholders survey (e.g. Drone manufacturers, Drone service providers, Software developers)

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      Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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