Introduction Methodology Results Next steps References Acknowledgements A - Samples of diﬀerent insects (Honeybees, Solitary Bees and Bumblebees) were scanned in TIF format 16bit depth, 1920x1920 pixels. B - CT scans in Raw setup, without ﬁltering. In some cases was required in this process using python scripts (Figure 1). C - 3D model processed in the Blender 3D software, using automatic and manual tools for cleaning up (Figure 2). D - Model after cleaning up and with internal armature for rigging (Figure 3). E - Model in natural position, with wings ﬁxed, ready to be exported. F - Render model made in Blender cycles for scientiﬁc illustration. G- Voxelized model in Sim4Life ready for simulations (3.5GHz, 20M cells). 25 CT scans were processed in to 3D models STL format, ready to be used in RF-EMF simulations. Models were tested for compatibility with Sim4Life software. For some models reconstruction of missing parts as such wings and legs were necessary. Those were done using references from literature. For manual tasks, python scripts using Blender API workﬂows were created where was possible to automate the work. Scripts can generate simple structures like antennas and legs segments. [1] Thielens, et al. Scientiﬁc Reports 8(1), 3924, 2018. [2] Thielens, PE 690.021, 2021, doi: 10.2861/318352. - Insects are crucial for the sustainability of ecosystems. - Telecommunication antennas emit Radio-Frequency Electromagnetic Fields (RF-EMFs) that could aﬀect insects. As telecommunications evolve (from 4G to 5G), the exposure of insects to RF-EMFs is likely to vary [1]. - Near powerful antennas, pollinators like bees face relatively high levels of RF-EMF exposure. This exposure can cause biological reactions in insects [2], yet the consequences of RF-EMF exposure on insects remain uncertain [2]. ETAIN has received funding from the European Union’s Horizon Europe research and innovation program under grant agreement No. 101057216 To assess the absorption of RF-EMFs in insects by utilizing detailed anatomical 3D models derived from CT scans, and to develop adaptable models compatible with EMF simulation software for various simulation scenarios. In this poster we focus on the process of extracting CT scan data to 3D models. Conduct simulations across each model at frequencies (1.8, 3.5, and 26 GHz) to verify whole-body averaged absorbed power, speciﬁc absorption rates and absorbed power densities. This will facilitate the analysis of how the distinct shapes of insects inﬂuence the results of these simulations. Implement simulations on heterogeneous models by assigning varied dielectric properties to diﬀerent parts of the insects. This approach will enable a more detailed and accurate representation of real-world conditions. Additionally, undertake simulations that focus on the internal structures of insects, thereby providing deeper insights into the internal eﬀects of RF-EMF exposure. By executing these steps, the project aims to shed light on the complex interactions between electromagnetic ﬁelds and biological entities, oﬀering valuable data for both scientiﬁc understanding and practical applications in the ﬁeld of bioelectromagnetics. Goals Figure 3. Illustration of the processing method of a CT scan of Osmia bicornis. Figure 1. Bombus terrestris CT scan ﬁltering method. 1.1 - Raw CT scan ﬁle. 1.2 3D model extracted from 1.1. The insect fur creates extra volume and issues to process the 3D model. 1.3 Filtered CT scan with lower density structures as the fur removed. 1.4 Updated 3D model without problematic fur meshes. Figure 2. 3D Models processing steps in Blender. Scripts have been implemented to streamline data aggregation into a uniﬁed table, capturing species name, collection site, and date. Additionally, it compiles morphological metrics calculated in Blender alongside Sim4Life simulation parameters and outcomes, providing a consolidated view of each sample's characteristics and simulation data. 3D Models were created using C