The paper presents category classification of mobile travel applications accessible at the moment for tourists in application stores for most popular mobile operation systems (Android and iOS). The most interesting category is "Travel Guides" that combines "Information Resources" and "Location-Based Services" category. Authors propose application "Tourist assistant - TAIS" that is related to "Travel Guides" category and recommends the tourist attractions around. Information about attractions is extracted from different internet sources.

The real-time driving behavior monitoring plays a significant role in intelligent transportation systems. Such monitoring increases traffic safety by reducing and eliminating the risk of potential traffic accidents. Vision-based approach including video cameras for dangerous situation detection is undoubtedly one of the most perspective and commonly used in sensing driver environment. In this case, the images of a driver, captured with video cameras, can describe its facial features, like head movements, eye state, mouth state, and, afterwards, identify a current level of fatigue state. In this paper, we leverage the built-in front-facing camera of the smartphone to continuously track driving facial features and early recognize driver's drowsiness and distraction dangerous states. Dangerous state recognition is classified into online and offline modes. Due to efficiency and performance of smartphones in online mode, the driving dangerous states are determined in real time on the mobile devices with aid of computer vision libraries OpenCV and Dlib while driving. Otherwise, the offline mode is based on the results of statistical analysis provided by a cloud service, utilizing not only the accumulated statistics in real time, but also the previously collected, stored and produced by machine learning tools.

Advances of the Internet of Things (IoT) technology resulted in appearance of digital connection and computation boxes, personal mobile devices, and ubiquitous wireless networks. The dependability in such IoT environments suffers due to taking the computation control away from remote servers to local surroundings (Internet edge) and intermediary devices (on network data transfer paths to the servers). In this paper, we consider the two emerging IoT-enabled paradigms: Edge-centric Computing and Fog Computing. We elaborate their potential for development of smart applications with focus on the dependability and using a mobile assistant for e-tourism as a reference application. We analyze possible concept elements for smart application development and provide recommendations in respect to the dependability.

This paper describes approach and methods used for the development of navigation services for people with disabilities. Our previous papers contained the description of informational environment development for disabled people. The environment includes several applications utilizing unified database and providing the information support to disabled people. The service “Accessibility Passports” was developed to collect information about accessibility of the objects. “Accessibility map” service visualizes the information on the geographical map. This paper is focused on the development of the key service of environment - “Social navigator”. Recently we have presented the service only conceptually without detailed description of navigation approach and methods with adaptation to personal mobility restriction. The paper describes developed methods of navigation for disabled people and elaborated algorithms. Also the practical opportunities of the service to support disabled people are presented. The results of approach study and development work are also presented in the paper.

Trip planning is among important and complex problems in tourism industry. Trip plan preparation requires data analyzing from a substantial number of services. Usually, service or standalone application provides limited functionality, which can be used only in trip preparation and for basic scenarios. This paper provides an approach to creating Smart Space-based Trip planning service. The Smart Space technology allows to create proactive services with context-based scenarios and multi-service usage. The paper describes trip planning problem as a list of possible tasks and presents mathematical model for common task. The presented approach includes high-level architecture of Smart Spacebased service, scenarios usage and possible data sources from existing third party services and used algorithms for data transformation.

This paper describes an approach to the optimal planning of wood harvesting and timber supply for forest companies of Russia. Software and tools successfully used in other countries (e.g., Finland, Sweden, Canada, etc.) are not as effective in Russian conditions for a number of reasons. This calls for the development of an original approach to solve this problem with respect to Russia’s specific conditions. The main factors affecting the operation of wood harvesting companies in Russia were determined. The optimization problem was formulated taking into account all important features of wood harvesting specific to the country. The mathematical model of the problem was formulated and analyzed. An important requirement is that the solution algorithm should find high-quality plans within short computation times. The original problem was reduced to a block linear programming problem of large dimension, for which an effective numerical solution method was proposed. It is based on the multiplicative simplex method with column generation within Dantzig–Wolfe decomposition and uses heuristics to determine feasible solutions based on the branch and bound method. We tested the solution approach on real production data from a forest company in southern Karelia with a planning horizon up to a year. This case study involved 198 sites and 14 machines harvesting up to 200,000 cubic meters from an available stock volume of about 300,000 cubic meters. An increase in profit by 5% to 10% was observed, measured as revenue from the sale of products, net of harvesting and transportation costs.