EFICAS introduces a generic and scalable software platform supporting energy-efficient deployment of AI algorithms on the multicore heterogeneous computation technologies. It supports all technology solutions, including localised and distributed computation settings as well as cloud offloading. It addresses Predictive maintenance and resource allocation at runtime as well as hybrid coherent operation with optimised task allocation at design time.

The project aim to develop local powerful GPU server at SDU where researchers, and students will be provided with hands on experience when interacting with real world data for training and testing different scenarios and getting valuable results. The main purpose of setting up the local server is to help researcher/students to reduce the unforeseen cost.

The project aims at building a light-weight energy harvester to tap energy from the powerline and perform inspection by using state-of-the-art machine-learning algorithms to optimize the inspection results thereby it is possible to only store the relevant inspection data on-board of the drone.

The aim of Drones4Safety is to develop a system of autonomous, self-charging, and collaborative drones that can inspect a big portion of transportation infrastructures in a continuous operation

HealthyLivestock will carry out a research programme to study the contributions of enhanced animal health and welfare on reducing the need to use antimicrobials in pigs and poultry. To develop, validate and deploy automated behaviour and live weight analyses systems that enable trait specific monitoring for early detection of both generic health challenges and specific diseases.