A UPC group and B. Braun investigate new inactivation strategies against SARS-CoV-2 virus through functionalized nanoparticles and activation of heat nanosources
June 28, 2020
Exheus, a new spin-off that analyses gene expression via artificial intelligence, to optimise performance, health and nutrition
July 1, 2020The inLab FIB has participated in the development of a system to characterise and model passenger demand on buses. Specifically, it has developed a module for predicting occupation that has been integrated into the application of the Autocorb company, which operates urban and interurban lines in the Barcelona Metropolitan Area. The app enables users to check the estimated occupation of buses throughout the day. The aim is for users to be able to choose the emptiest buses, so that service supply and demand can be balanced. In the context of the COVID-19 health service, this will help to reduce crowds on buses.
The algorithms are based on data-driven methodologies drawn from a wide range of sources (ticketing, the schedule and bus cameras). Classical methods for processing time series have been incorporated into the prediction module. These include the ARIMA method and neural network algorithms that enable important variables such as the school calendar to be included in the occupation time series.
The new functionality is integrated within the Intelibus ecosystem of tools, a real-time information system in the passenger transport system, which uses GPS positions of buses and the ticketing system to provide useful information for public transport users and the service operator.
Testing of the beta version of the app began on 11 May and is available for Android (on Play Store) and iOS devices.
Technology
You want to know more?
Related Projects
- A research team from the Institut de Robòtica i Informàtica Industrial (IRI, CSIC-UPC), together with the Centre de Disseny d'Equips Industrials (CDEI) of the Universitat Politècnica de Catalunya - BarcelonaTech (UPC), are participating in the national CASANDRA project to develop a digital manufacturing solution that will make it possible to establish a bidirectional data flow for continuous digital integration throughout the supply chain across the product life cycle. This integration will be achieved through digital twins and data-based models that are continuously updated thanks to distributed monitoring and control tools.
- The research groups Structural and Materials Technology (ATEM) and the Construction Engineering (EC) at the Universitat Politècnica de Catalunya - BarcelonaTech (UPC) are working on the RE-STEEL project, which aims to develop an efficient methodology for assessing the rehabilitation of existing steel structures.
- The AgroTech research group at UPC, in collaboration with its spin-off Ugiat Technologies, has developed uPlayer, a new multimedia player concept that enables more intuitive video navigation and viewing, intelligently enhancing the user experience, especially on YouTube and other platforms, by integrating as a plugin or advanced player.
- The AgroTech research group at the Universitat Politècnica de Catalunya – BarcelonaTech (UPC), together with its spin-off Ugiat Technologies, have driven DoblAI, an AI platform that integrates transcription, translation, subtitling and video dubbing into a single workflow. The solution, which uses deep learning technology and cloned or default voice models, is specifically designed for the journalism and communications sector.
