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ICT-Agri-Food Joint Call
Call1 FP
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Bing Han
Netherlands
Wageningen Bioveterinary Research
Research Institute
Animal infectious diseases, Machine Learning, Prediction, Monitoring, Time series data, animal disease behavioral and molecular markers, Sensor, micro-sampling
Topic 1 - Data technologies and data management
Delivering expertise in time-series analytics, real-time sensor data pipelines, and machine-learning applied to animal health monitoring, enabling development of AI-driven disease detection, progression modeling, and decision-support tools.
We focus on infectious-disease–associated behavioral and pathophysiological dynamics in animals and support consortia through:
• Advanced multimodal time-series analytics integrating behavioural, physiological, and molecular signals.
• Design and implementation of real-time sensor data pipelines for automated data collection, processing, feature extraction, and quality control.
• Application of machine-learning and AI methods for early disease detection, classification, anomaly detection, and disease progression prediction.
• Method development and validation within controlled experimental infection models to ensure biological interpretability and robustness.
Our contribution aligns with Topic 1 C-R&I-As 1.1, 1.6, 1.9, 1.10, 1.20, 1.23, and 1.25, through data integration frameworks, sensor-stream processing, robust AI for heterogeneous data, uncertainty handling, and digital twin development.
It also aligns with Topic 3 C-R&I-As 3.3, 3.6, and 3.10, enabling development of disease and welfare indicators, automated monitoring methodologies that reduce reporting burdens, and scalable approaches for integrating precision sensor data into policy-relevant assessment tools.
We focus on infectious-disease–associated behavioral and pathophysiological dynamics in animals and support consortia through:
• Advanced multimodal time-series analytics integrating behavioural, physiological, and molecular signals.
• Design and implementation of real-time sensor data pipelines for automated data collection, processing, feature extraction, and quality control.
• Application of machine-learning and AI methods for early disease detection, classification, anomaly detection, and disease progression prediction.
• Method development and validation within controlled experimental infection models to ensure biological interpretability and robustness.
Our contribution aligns with Topic 1 C-R&I-As 1.1, 1.6, 1.9, 1.10, 1.20, 1.23, and 1.25, through data integration frameworks, sensor-stream processing, robust AI for heterogeneous data, uncertainty handling, and digital twin development.
It also aligns with Topic 3 C-R&I-As 3.3, 3.6, and 3.10, enabling development of disease and welfare indicators, automated monitoring methodologies that reduce reporting burdens, and scalable approaches for integrating precision sensor data into policy-relevant assessment tools.
Wageningen Bioveterinary Research (WBVR), within Wageningen University & Research (WUR), is the Netherlands’ leading veterinary research institute integrating infectious disease biology with sensor technologies, real-time data pipelines, time-series analytics, machine learning, and bioinformatics to support advanced animal health monitoring and digital decision tools.
Our facilities enable controlled animal studies under high biosafety conditions (up to BSL-3), supporting the investigation of disease mechanisms and host-pathogen responses at behavioral, physiological, and molecular levels. WBVR maintains in-house expertise spanning virology and bacteriology, sensor technology, real-time data infrastructure, bioinformatics, epidemiology, time-series statistics, and machine learning. This multidisciplinary setup allows us to translate complex biological observations into scalable digital monitoring and analytical frameworks.
We routinely collaborate in international public–private research consortia and provide scientific coordination, experimental validation platforms, and data-driven method development that bridge fundamental research with technology implementation and decision-support applications.
Our facilities enable controlled animal studies under high biosafety conditions (up to BSL-3), supporting the investigation of disease mechanisms and host-pathogen responses at behavioral, physiological, and molecular levels. WBVR maintains in-house expertise spanning virology and bacteriology, sensor technology, real-time data infrastructure, bioinformatics, epidemiology, time-series statistics, and machine learning. This multidisciplinary setup allows us to translate complex biological observations into scalable digital monitoring and analytical frameworks.
We routinely collaborate in international public–private research consortia and provide scientific coordination, experimental validation platforms, and data-driven method development that bridge fundamental research with technology implementation and decision-support applications.