Deep learning powered holographic microscopy for biothreat detection on field
HoloZcan brings a new tool for security actors (police, relief workers, disaster managers, crisis managers, stakeholders responsible for public safety, critical infrastructure, and service providers) notably in the fields of autonomous detection and response capabilities.
The project will increase (environmental and exhaled) bio-aerosol sensing/measurement capability of CBRN practitioners by developing a high resolution, large throughput, automatic and highly portable detection system for making automatic classification of pathogens and particles. 
HoloZcan develops of a novel holographic microscopy and imaging technology for rapid and cost-efficient screening of potential biological threats and unknown, potentially dangerous substances, combined with methods of artificial intelligence and machine learning. It establishes a framework of a dynamic feature selection and validation algorithm to support the continuous innovation capability of the system in the field of adaptive learning and database optimization for specific bioinformatic applications. The project also develops comprehensive and innovative means of respiratory, ventilation and environmental biological data sampling that can be used in real-time, standoff or in mobile bio-detection context. 
The project indicates the HoloZcan technique versatility for a wide range of applications and demonstrates its technical feasibility. The project responses to the actual needs of European practitioners and technological gaps identified by the ENCIRCLE project as indicated in the ENCIRCLE Catalogue of Technologies and addresses several shortcomings of the current approaches to bio-threat agent detection. 
The HoloZcan project applies a flexible adaptive approach to design and CBRN practitioners are engaged as project partners or as external stakeholders in the process.