On April 9 (Thursday) presentation of Passport Sustainability and Passport Innovation

Library April 7, 2026

On April 9 (Thursday) 14:00 – 15:00, the community of the Faculty of Business Management is invited to a remote meeting with Simona Bernatonytė, a representative of the Passport database (Euromonitor International), subscribed to by VILNIUS TECH. She will present the new products Passport Sustainability  and Passport Innovation.

 

Passport Sustainability measures sustainable product sales data and the prevalence of sustainability claims across multiple categories. It provides you with comprehensive insights into consumer and business attitudes towards sustainability to help you track performance of claims, understand consumer sentiment and craft effective sustainability strategies.

Passport Innovation tracks new brand and sub-brand launches across the global digital shelf and also measures product expansion over time by country, retailer and category to learn when new products proliferate or get discontinued.

 

Microsoft Teams meeting
Join: https://teams.microsoft.com/meet/39177721597335?p=KVbw0xsfqx64KXEwxP
Meeting ID: 391 777 215 973 35
Passcode: K7hg7gr6

 

In addition, from April 9 to April 30, you will have the opportunity to try out these products through the university’s subscription to the Passport database (Euromonitor International).

 

Passport – a database subscribed by VILNIUS TECH, offering comprehensive analysis and forecasts on consumers and various industries. It also provides demographic indicators, and all statistical information covers more than 200 countries. The platform is particularly valued for its regularly updated data, reliable methodologies, and the ability to easily compare markets across countries. Such resources provide a solid foundation for academic research and help lecturers integrate real market data into the study process.

Access is available from VILNIUS TECH computer network or via VPN. 

Related news

New doctoral dissertation
New doctoral dissertation
VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Control of Robot Path Using an Artificial Intelligence System by Fusing Sensor Signal“ („Roboto trajektorijos valdymas dirbtinio intelekto sistema suliejant jutiklių signalus“) prepared at VILNIUS TECH by Vygantas Ušinskis. The dissertation was prepared in 2021–2026. Scientific consultant – Prof. Dr  Vytautas Bučinskas. The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Mechanical Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 10 a.m. on 30 April 2026. The dissertation examines the problem of local robot navigation, where sensor data must be processed in real time to assess the environment and generate an adaptive motion trajectory. The research object is a local navigation system with sensor fusion for mobile robots operating in tunnels and confined channels. Navigation is divided into four parts: environment assessment, localisation, path planning, and motion execution. The analysis of localisation technologies enables the selection of an effective sensor set for obstacle detection. Heuristic and artificial intelligence methods allow generating an optimal trajectory that avoids collisions and maintains the goal. The work addresses navigation and obstacle detection in human-inaccessible environments using a cost-efficient combination of active and passive sensors, with experimental validation of the system’s performance. The dissertation consists of an introduction, three main chapters, conclusions, references, and a list of the author’s scientific publications on the topic of the dissertation. The introduction presents the problem, relevance, research objective and tasks, methodology, scientific novelty, practical significance, and defended statements, as well as the author’s publications and the structure of the dissertation. The First Chapter presents a literature review, including an overview and comparison of global and local path-planning methods, localisation technologies and their combinations, and sensor-fusion approaches used in mobile robots. Key factors affecting reliable navigation are identified, forming the basis for the dissertation tasks. The Second Chapter describes the developed research methodology for autonomous tunnel navigation: the operating principles of the red, green and blue (RGB) channel-camera- and laser-based optical obstacle detection system, sensor-fusion techniques, and the application of modified Vector Field Histogram (VFH) and machine-learning-based path-planning methods. The Third Chapter presents the research results: optical system experiments, path-planning simulations, a comparison between machine-learning and modified VFH methods, and the testing of the constructed robot prototype in a laboratory environment. Five research papers have been published on the topic of the dissertation: three in journals indexed in the Web of Science database, and two in conference proceedings. Additionally, five conference presentations related to the dissertation topic have been delivered in Lithuania and abroad. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.  
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