New technological solutions for the effective, objective and cost-sensitive monitoring of cultural heritage are needed. Accordingly, a new methodological approach based on laser scanning, 3D photogrammetry, artificial intelligence and GIS interaction is presented in this paper. The main goal is to develop a software that could detect and compare various architectural and urban elements by comparing 2D and 3D data of objects and places of the same cultural heritage from different time periods. This represents a breakthrough technological tool for governments to track the broad-scale status of heritage and act in a timely and proactive manner. The methodological approach was to inspect changes comprised of geometrical alterations in 3D data and pixel-based information changes in 2D data. The proposed solution was developed as part of a project financed by the Research Council of Lithuania entitled Automated monitoring of urban heritage implementing 3D technologies. The first results of the project are presented in this article. All pictures and tables in this paper were prepared by the authors.

Artificial intelligence (ai) is rapidly transitioning from the realm of science fiction to the reality of our daily lives, and is taking the world by storm. Unlike more specialized innovations, ai is becoming a true general-purpose technology and is evolving into a utility that is likely to ultimately scale across every industry and sector of our economy, as well as nearly every aspect of science, society and culture. It fills human space silently and invisibly. The hype during the last few years relating to ai has helped society to understand that it is entering a new era of ai. However, as Clarke’s third law states, any sufficiently advanced technology is indistinguishable from magic (Clarke 1962).ai has evoked many issues in the past and will continue to do so. The way to go safe is to take precautions. A great deal of introspection, science, and capital are being invested in ethical research, economics, and the philosophy of ai. Researchers and industrialists have begun to recognize the appropriate role of ai in society. However, government policies have not yet attained a substantial stature. I agree with the opinion of Denise Feldner who stated that “now is the time for us to think about the crucial questions of being human in the Hybrid Age as we are, at the moment, profoundly ill prepared for future technologies.”[...]

The paper presents research results for solving the task of targeted aspect-based sentiment analysis in the specific domain of Lithuanian social media reviews. Methodology, system architecture, relevant NLP tools and resources are described, finalized by experimental results showing that our solution is suitable for solving targeted aspect-based sentiment analysis tasks for under-resourced, morphologically rich and flexible word order languages.