DEDAL, Distributed Ecosystem for Drone Analytics in Life-sciences

DEDAL is a cloud-based solution designed for the UK crop genetics community and UK farmers to process and phenotype drone data. Highly capable drones, which provide valuable insights into plant health, have become so cost-effective that they are now considered consumable items. However, delivering usable scientific insights from drone images is often hindered by several challenges: the high cost of proprietary software licenses for data processing, the hardware requirements to run such software, and the complexity of setting up various open-source solutions and adopting the best practices of the community. DEDAL addresses these challenges by offering a cloud-based solution tailored for UK academics. Powered by a robust OpenNebula platform, DEDAL consists of two key services to provide documented solutions to common drone phenotyping tasks. Leveraging OpenDroneMap, users can process raw drone data to generate orthomosaics and plant health indices, which users can view and download for further analysis in other software. Further to this, a specialised environment is provided to host open-source projects such as FieldImageR.extra for integrating processed drone orthomosaics to extract meaningful insights, such as vegetation indices, plot height, and more. Ongoing work aims to expand DEDAL's capabilities by incorporating AI models for phenotyping tasks, including yield estimation and disease scoring. Our mission at JIC is to foster scientific advancements and empower the community with tools like DEDAL that drive innovation in fields such as agriculture, environmental science, and beyond. The service is proudly maintained by the JIC Bioinformatics team . This dedicated team leverages its expertise to ensure the robustness and accessibility of DEDAL, supporting cutting-edge research and fostering collaboration across disciplines. DEDAL and DEDAL-Lab, developed by Miguel Gonzalez Sanchez, Research Software Engineer at the JIC, April 2025. Acknowledgments NBI Research Computing and Core Computing Teams.Sarah Brookes, designer of the DEDAL icon and the splash image.Dr. Alba Pacheco Moreno. OpenDroneMap Authors ODM: ODM – OpenDroneMap/ODM GitHub Page, 2020.Pawar P. & Matias F.I. for their work on FIELDimageR.Extra: The Plant Phenome J., 2023. For inquiries, contact us at [email protected]. Note: DEDAL and DEDAL-Lab are not officially associated with OpenDroneMap or its products.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-07
DOI
https://doi.org/10.5281/zenodo.15846332
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DEDAL, Distributed Ecosystem for Drone Analytics in Life-sciences

Zenodo (CERN European Organization for Nuclear Research)
Smart Agriculture and AI
article

DEDAL, Distributed Ecosystem for Drone Analytics in Life-sciences

article en

Abstract

DEDAL is a cloud-based solution designed for the UK crop genetics community and UK farmers to process and phenotype drone data. Highly capable drones, which provide valuable insights into plant health, have become so cost-effective that they are now considered consumable items. However, delivering usable scientific insights from drone images is often hindered by several challenges: the high cost of proprietary software licenses for data processing, the hardware requirements to run such software, and the complexity of setting up various open-source solutions and adopting the best practices of the community. DEDAL addresses these challenges by offering a cloud-based solution tailored for UK academics. Powered by a robust OpenNebula platform, DEDAL consists of two key services to provide documented solutions to common drone phenotyping tasks. Leveraging OpenDroneMap, users can process raw drone data to generate orthomosaics and plant health indices, which users can view and download for further analysis in other software. Further to this, a specialised environment is provided to host open-source projects such as FieldImageR.extra for integrating processed drone orthomosaics to extract meaningful insights, such as vegetation indices, plot height, and more. Ongoing work aims to expand DEDAL's capabilities by incorporating AI models for phenotyping tasks, including yield estimation and disease scoring. Our mission at JIC is to foster scientific advancements and empower the community with tools like DEDAL that drive innovation in fields such as agriculture, environmental science, and beyond. The service is proudly maintained by the JIC Bioinformatics team . This dedicated team leverages its expertise to ensure the robustness and accessibility of DEDAL, supporting cutting-edge research and fostering collaboration across disciplines. DEDAL and DEDAL-Lab, developed by Miguel Gonzalez Sanchez, Research Software Engineer at the JIC, April 2025. Acknowledgments NBI Research Computing and Core Computing Teams.Sarah Brookes, designer of the DEDAL icon and the splash image.Dr. Alba Pacheco Moreno. OpenDroneMap Authors ODM: ODM – OpenDroneMap/ODM GitHub Page, 2020.Pawar P. & Matias F.I. for their work on FIELDimageR.Extra: The Plant Phenome J., 2023. For inquiries, contact us at [email protected]. Note: DEDAL and DEDAL-Lab are not officially associated with OpenDroneMap or its products.

Zenodo (CERN European Organization for Nuclear Research)
John Innes Centre (GB)
Openalex Percentile: Top 69%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.