Tourism planning informatization

The Tourism activity, due to its own characteristics, causes high environmental impact and its development should be influenced by the environmental characteristics of each region. The Information Systems, mainly those which represent the geographical information, will permit the development of a design, allowing the Decision-Maker the consult, the management and the presentation of decision schemes based on the defined measures of the Tourism Planning of a region. As the information associated with this design should be real and update, the Internet should be used as a means of access to the information of the region. The design presents the schemes associated to each decision, offering competitive advantages to the Decision-Makers involved in the decision process, since it is possible to evaluate, foresee and control the future environmental impacts of Tourism.

GIS on tourism planning: preventing the impacts caused by the developing tourism activity in a specific site

The environment is one of the greatest concerns of humankind. Nowadays, the activities which improve or destroy it must be assessed and controlled by efficient means which should permit the control of environmental impact caused by the development of these activities. This document presents an information system implementation, as a Decision Support system, allowing the Decision Maker to evaluate, foresee and control the future environmental impact of Tourism through consultation, the management and the presentation of decision schemes based on defined measures of a regional tourism planning.

Public transport travel planning application

Here it is presented an application that plans out travel on public transports and that chooses the best ones, according to preference criteria provided by the user. These criteria are: the time spent on the travel, the price of the tickets and the quality of the transports. The application combines different means of transport. Algorithms and heuristics were developed to draw up transport plans and to choose the best ones. The best plans are determined using the multi-attributes decision techniques. The application uses a database that was developed in a Relational Database Management System. To draw the database at the conceptual and the applicational level, it was used one of the models based on the object, the Entity-Relationship Mode

Big data warehouse framework for smart revenue management

Revenue Management’s most cited definitions is probably “to sell the right accommodation to the right customer, at the right time and the right price, with optimal satisfaction for customers and hoteliers”. Smart Revenue Management (SRM) is a project, which aims the development of smart automatic techniques for an efficient optimization of occupancy and rates of hotel accommodations, commonly referred to, as revenue management. One of the objectives of this project is to demonstrate that the collection of Big Data, followed by an appropriate assembly of functionalities, will make possible to generate a Data Warehouse necessary to produce high quality business intelligence and analytics. This will be achieved through the collection of data extracted from a variety of sources, including from the web. This paper proposes a three stage framework to develop the Big Data Warehouse for the SRM. Namely, the compilation of all available information, in the present case, it was focus only the extraction of information from the web by a web crawler – raw data. The storing of that raw data in a primary NoSQL database, and from that data the conception of a set of functionalities, rules, principles and semantics to select, combine and store in a secondary relational database the meaningful information for the Revenue Management (Big Data Warehouse). The last stage will be the principal focus of the paper. In this context, clues will also be giving how to compile information for Business Intelligence. All these functionalities contribute to a holistic framework that, in the future, will make it possible to anticipate customers and competitor’s behavior, fundamental elements to fulfill the Revenue Management