SINTEF is leading a research project that will enable the DevOps of trustworthy smart IoT systems, and will test the technology developed on three pilots from the smart buildings, intelligent transportation, and healthcare domains.
Advanced ex vivo analyses and multi-frequency ultrasound technology for improved evaluation and diagnosis of coronary plaque.
There are significant resources of wind power in areas where few people live, and which cannot be exploited due to a weak grid. A solution is to produce hydrogen and export it.
Enabling procurement data value chains for economic development, demand management, competitive markets and vendor intelligence
The subsea industry is constantly pushing towards reduced costs and increased safety in subsea inspection, maintenance and repair operations. Therefore we have established the SEAVENTION project: Autonomous subsea intervention - empowered by people and AI.
AutoActive: Tools and Methods for Autonomous Analysis of Human Activities from Wearable Device Sensor Data
The vision of Sharing Neighbourhoods is digitalization towards a socially inclusive and caring neighbourhood. We will investigate the effects of digital collaborative sharing platforms on the social interactions in neighbourhoods, and the new economic models that these platforms enable in the neighbourhoods.
CO2 storage data consortium – sharing data from CO2 storage projects
Sharing of reference datasets from pioneering CO2 storage projects is essential to accelerate improved understanding, build capacity, reduce costs and minimize uncertainties associated with CO2 storage in deep geological formations.
Currently, maintenance planning in the railroad domain is predominantly performed manually and involves: Crew scheduling (assigning maintenance tasks to crews dependent on skill set) and job shop scheduling (assign time slots for vehicles to depot workstations). These activities should be synchronised and coordinated with vehicles revenue generating activity (where the vehicles are scheduled to transporting goods or passengers). Due to the substantial fixed costs involved, improved planning is expected to generate significant cost savings.