Future apt LIVING Lab for Autonomous Public Transport. LivingLAPT will deliver sustainable driver-less shuttle/logistics services among various European cities by phasing out the need for safety drivers in shuttles and moving towards remote operators who overlook a number of services simultaneously. IPI will evaluate the safety near autonomous public transport. This applied research builds on our sensor fusion technology whose ongoing development is co-financed by the Flanders AI research program. EIT Urban Mobility, 1/2022 - 12/2022
IPI researches integrated sensors and data analysis fault detection tools for photovoltaic plants. See the project results. ICON project, 10/2019 – 9/2022
CHARAMBA aims to solve the problem of costly and labour-intensive sampling and chemical analysis of complex material/waste streams EIT RawMaterials, 1/2020 - 12/2021 Press release on the project results
In the COSMO project, researchers are designing, developing, and evaluating effective, personalized, and scalable AR and VR technologies for support and training in manufacturing operations
ICON project, 5/2019 - 4/2021
Framework of Key Enabling Technologies for Safe and Autonomous Drones
IPI contributes to a novel framework of key enabling technologies for safe and autonomous drones. We focus on hyperspectral imaging from manually flown drones for inspection of offshore turbines structure to detect imperfections, such as corrosion deterioration of paint.
ECSEL JU, 10/2019 – 1/2023
Demand for image sensors in automobiles, the Internet of Things, medicine or security and surveillance applications is challenging businesses to improve the performance of their integrated systems. EXIST is developing breakthrough image sensors that will expand the functionality of future vision systems.
ECSEL JU, 5/2015 - 12/2018
PANORAMA will deliver solutions for applications in medical imaging, broadcasting systems and security & surveillance, all of which face similar challenging issues in the real time handling and processing of large volumes of image data.
ENIAC JU, 4/2012 - 12/2015
The SONOPA project - SOcial Networks for Older adults to Promote an Active Life - employs technologies to develop an end-to-end solution for stimulating and supporting activities at home.
EU, 5/2013 - 4/2016
The VIL project aims to improve print quality, reduce waste, and cut the cost of additive metal manufacturing
ICON project, 4/2020 - 3/2022
This project develops tools for X-ray imaging of dynamic processes in materials, with the goal of helping materials scientists to develop better and more sustainable materials.
IPI's focus is on developing algorithms capable of handling large 3D datasets including research on GPU processing, (ROI) CT reconstruction, and efficient optimization algorithms with the emphasis on huge amounts of data.
FWO-SBO, 1/2018 – 12/2022
**iPlay**: Interactive sports platform for comprehensive, 3D monitoring of athletes, 2017-2019 **ARIA**: Augmented Reality for Industrial Maintenance Procedures, 2016-2018 **BAHAMAS**: A toolset for the processing, compression and analysis of big data in life and materials science applications, 2015-2016 **HD2R**: Creating Images with Higher Dynamic Range and Richer Colors for Cinemas and Living Rooms, 2015-2017 **wE-MOVE**: Games to improve children’s rehabilitation and fitness level, 2015-2016 **GIPA**: Laying the foundation for a generic, state-of-the-art augmented reality (AR) platform, 2014-2015 **FIAT**: Unlocking the potential of ‘functional imaging’ to quantify tumor response to treatment earlier and more accurately, 2014-2015
**AVCON**, 2018-2019
**EMDAS** (Autonomous vehicles), 2015-2016
**3DLicorneA**, Brussels Institute for Research and Innovation, 2015-2018
Researchers in ACHIEVE are designing highly integrated hardware-software components for the implementation of ultra-efficient embedded vision systems as the basis for innovative distributed vision applications
For IPI, the first goal of this project is to design algorithms for distributed multiple targets tracking through a decentralized approach. The second goal is to improve object detection and tracking using a multi-sensor approach. Thermal cameras have promising potential in surveillance applications, especially when combined with optical cameras. The third goal of the project is to provide solutions for behaviour analysis and action recognition. The research will use high-level analysis to automatically determine which cameras observe the same or similar action, such as pedestrians waiting to cross the street. Deep learning is a promising approach.
H2020-MSCA-ITN, 10/2017 – 9/2021