Abstract
The paper is aimed at developing information technology for planning safe tourist trips. The difficulty of building a tourist route is to give the user the opportunity to build it with interesting tourist attractions. This kind of problem can be classified as a combinatorial optimization problem, the solution of which will be the salesman’s problem in its open version. Solving optimization problems is performed using various algorithms, but they have the following disadvantages: – all algorithms often have limitations of local solutions; – only one solution is used as a source; – each method is quite sensitive to the choice of conditions. The key elements of this technology are the module of choice of tourist places, the module of analysis of responses of other users, the module of planning / modification of a route, the module of forecasting of occurrence of emergency situations. The last module consists of several models of machine learning. All trained models are tested for adequacy and will be used in the future to predict the likelihood of a forest fire. The initial data of the developed system provide the user with an understanding of the situation regarding the probability of a forest fire. Data are calculated as predictions based on the original data and create a forecast for this set of characteristics. As a source, the user will receive an apology visualization in the form of a graph for a specific data set, as well as a map with a prediction for a specific region for easier visual perception. The route planning and navigation system can be used for mobile devices such as PDAs and mobile phones. It includes three main functions: (1) access updated information about the place of interest; (2) plan a specific day for the user according to his / her preferences; (3) user navigation of the selected travel route and dynamic rescheduling. Service-oriented architecture (SOA) in combination with middleware methods and web services is used to design and implement system architecture. The system has a functional personal page of the user, which will display personal information of the user. The page is used to identify the user as well as his preferences. The system has two-factor authorization to log in. All personal data of users is stored in encrypted form and can be securely protected from theft. User authorization is performed at different levels: editing level, viewing level, change monitoring and analysis level.
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