The objective is to develop the Romanian students’ abilities to work as to improve the insertion of specialists from the field of artificial intelligence in the national and European work market.
POSDRU/109/2.1/G/81772, 2012-2013
University-funded, UPB-EXCELENȚĂ-2016 ID 391.
Duration: 2016-2017.
Some Past Research Grands: AGATE, SCIPA, CATIIS, A-ROADS, ADEPT, MIRA, RLN Negotiation Framework, ICARUS, ARGUMENT, AGENT-FISHBANK, AGCOR, COOP…
Some Older Development Projects: CANTI, I_TRACE, CEC-WYS, Agents Intelligents, Représentation Logique des Connaissances pour les Agents Intelligents, Continuous Education Program on Intelligent Agents Technology and Knowledge Processing, INT200…
Nemodrive brings together a group of motivated researchers with the required resources and support to build a self-driving car that will be tested on the UPB campus streets. The prototype will be developed to tackle the particularities of campus and other local roads. In this context, some of the most recurring challenges of self-driving cars will be empirically put to test, in a small scale, un-controlled environment.
Nemodrive is founded on a desire that drives both its theoretical as well as empirical aspirations: to continuously drive interest and understanding of machine learning, duration: 2018-2020.
IONIS will offer fully integrated and validated solutions for health monitoring, home automation, personal agenda with reminders, alerts, caregiver administrative tools. The platform will integrate technologies and services that can address dementia specific challenges and offer support to both caretakers and caregivers: location based services for indoor localization, LBS for object localization by integration of own solutions based on embedded Linux and commercial Bluetooth tags, LBS for outdoor localization and geofencing to allow dementia sufferers to enjoy outdoor activities and perform essential task such as shopping or visiting, alerting and easy communication through one-button calls to designated caregivers, sleep quality monitoring through non-wearable sensors, recommending outdoor activities according to the level of indoor effort extracted from mobility patterns and sleep quality. AI-MAS is member of the consortium.
The IONIS project is founded by the EU Active and Assisted Living Programme, duration: 2017-2020.
Member of EU-ROBOTICS
SPARC is developed in cooperation with CITST company that aims at exploiting robotic technology as a service offer for its potential clients. The envisaged applications are product promotion and/or clients’ assistance in public places such as malls, museums, exhibitions by means of an autonomous robot. In this context, the main goal of the project is the design and implementation of a robotic platform to achieve integrated planning of robot tasks and robot interaction with the clients.
The SPARC project is financed by “Bridge Grant” programme, PNIII, duration: 2016-2018.
The main goal of ERRIC is to achieve excellence in research in selected areas of Intelligent Information Technologies: agreement technologies, semantic and collaborative technologies for the web, advanced grid technologies, large scale distributed system services, and adaptive intelligent control.
FP7-ICT No. 264207, 2010-2013.
NETIO Objectives: development of innovative products and services in the domain of IoT and Big Data, empowering innovation activities of companies in the domains of IoT and Big Data through knowledge transfer and common research activities with UPB, implication of UPB staff in all stages of technological transfer for IoT and Big Data based products and services. Duration: 2017-2020
Project co-financed by the European Fond for Regional Development in the framework of the Operational Programme for Competitiveness 2014-2020.
Consortium composed of six universities from four countries: France (University of Pierre and Marie Curie Paris 6, University of Lyon Lumière Lyon 2, Polytec’Nantes), Romania (University Polithenica of Bucharest), Italy (University of East Piedmont) and Spain (Technical University of Catalonia).
The Master in DMKM is based on experience in multi-site teaching gained from the Master’s degree in Knowledge Extraction from Data, which has been running since 1999 within three members of the consortium.
Erasmus Mundus Project 2010-2016.
Member of ICT COST Action TD1202 Mapping and the citizen sensor, 2012-2016.
Member of COST Action IC0801: Agreement Technologies. Agreement Technologies refer to computer systems in which autonomous software agents negotiate with one another, typically on behalf of humans, in order to come to mutually acceptable agreements. 2008-2012.
ROBIN is a user centered project which develops systems and services for the use of robots in an interconnected digital society. It comprises 5 sub-projects. ROBIN-Social develops integrated and configurable solutions for the personalization of assistive and social autonomous robots. ROBIN-Car develops computer vision methods devoted to autonomous driving and a prototype systems to be tested on an electric car. ROBIN-Context creates a support platform for the semantic representation and management of data that becomes context in scenarios of personalized robotic assistance and AADS. ROBIN-Dialog develops a set of scenarios for micro-worlds and the technology for the Romanian language processing to achieve situational dialogs in these micro-worlds. ROBIN-Cloud builds a support platform for collecting data coming from the sensors of robotic systems and IoT devices that offers Cloud Edge and Cloud Robotics computing.
The ROBIN project is financed by UEFISCDI “Complex Projects” programme, PNIII, duration: 2018-2020.
Mobile@Old extracts a mobility pattern for each user and generates remainders and alerts regarding his/her physical and other daily activities.
In case of low physical activity, the user is advised to increase the level of physical exercise.
The exercises are performed interactively, as an adaptive game, specifically designed for elderly persons.
The intensity level of the recommended physical exercises is generated and adapted based on both vital parameters of the user (analyzed using a medical expertise) and also on the observed behavior by a team of psychologists.
Mobile@Old is financed by PCCA programme, PNII, duration: 2014-2017.
CAMI is offering a fully integrated Ambient Assisted Living solution by offering services for health management, home management and wellbeing (including socialization, and reduced mobility support). CAMI builds an artificial intelligence ecosystem, which allows seamless integration of any number of ambient and wearable sensors with a mobile telepresence system endowed with multimodal interaction (touch, voice, person detection), including a telepresence robot. This will allow older adults to self-manage their daily life and prolong their involvement in the society while allowing their informal caregivers to continue working whilst caring for their loved ones.
The consortium comprises 8 partners from Romania, Sweden, Switzerland, Denmark, and Polland. AI-MAS is the consortium coordinator.
The CAMI project is founded by the EU Active and Assisted Living Programme (Call 2014 – “Care for the Future”), duration: 2015-2018.
The aim of the AmIciTy initiative is to create a software infrastructure for Ambient Intelligence applications, that handles context at its constructive level, that works naturally with the user’s tasks and activities, and that manifests the robustness and reliability that is required for future ambient systems. Internal project, since 2014.
A robotic platform designed to be used in a heterogeneous robotic swarm and that has many hardware and software state of the art features. Internal project, since 2015.
The objective of this project is the creation of an open source context management middleware solution presenting rich features that alleviate context-aware application development. Based on the existing platform CONSERT, developed in the AIMAS laboratory, the work improves upon CONSERT with: performance improvement and modularisation of the reasoning engine to support applications of variable complexity requirements, development of an IDE for context modeling and deployment to facilitate context-aware application programming based on the CONSERT Middleware, and advanced options for OSGi and Docker based deployments of CONSERT processing units to address dynamic change of context within an application.
The CONSERT project is financed by “Exploratory Grants” programme, PNIII, duration: 2016-2018.
