Field margins, floral plantings, and crops offering nectar and pollen to insects may contribute to ecosystem service delivery (pollination) and ecological intensification of agriculture. The application of machine learning on data collected using low-cost RGB cameras represents a new opportunity to investigate, evaluate, and optimize the attractiveness of such cropping systems to beneficial insects.

Robotic systems play a major role for realizing the vision of sustainable crop production. While Unmanned Aerial Vehicles (UAVs) are increasingly used to monitor the health status of agricultural fields using sensors like RGB cameras, multi-spectral cameras, and LiDAR, it is often still necessary to literally walk into the field to do close-up inspections of individual plants or even leaves for the detection of diseases or nutrient deficiencies in early stages of plant growth. 

Agriculture today faces significant challenges that require new ways of thinking, such as smart digital technologies that enable innovative approaches. However, research gaps limit their potential to improve agriculture.

One of PhenoRob's aims is to translate research into practice. Pheno-Inspect GmbH is a 2020 start up, with a strong connection to PhenoRob, working on how to interpret image-data recorded in agricultural fields and from there on out build smart AI systems to do the same to and provide services in the agricultural industry.

IROS 2024 Best Agri-Robotics Paper Award for the PhenoRob paper "BonnBeetClouds3D: A Dataset Towards Point Cloud-Based Organ-Level Phenotyping of Sugar Beet Plants Under Real Field Conditions" presented by Elias Marks and finalist for the IROS 2024 Best Agri-Robotics Paper Award for the PhenoRob paper "Spatio-Temporal Consistent Mapping of Growing Plants for Agricultural Robots in the Wild" presented by Luca Lobefaro at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024) in Abu Dhabi.

University of Bonn’s Institute for Geodesy and Geoinformation (IGG) joins global efforts in advancing Geodesy as a Partner of the United Nations Geodetic Centre of Excellence (UN-GGCE) in Bonn.

Jensen et al. (2024), including IGG scientists Helena Gerdener and Jürgen Kusche, evaluate trends in terrestrial water storage over 1950–2100 in CMIP6 climate models against the IGG GLWS2.0 global reanalysis from assimilating GRACE and GRACE-FO satellite observations into a hydrological model. The results were now published in the journal npj climate and atmopsheric sciences.

In 2023, the International Journal of Computer Vision created an “Outstanding Reviewer award” program in order to celebrate and highlight reviewers in our community that provided exceptional service to the journal with their reviews.