TCC - Bacharelado em Ciência da Computação (Sede)
URI permanente para esta coleçãohttps://arandu.ufrpe.br/handle/123456789/415
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Resultados da Pesquisa
Item IoT orientado a Assets: uma ferramenta para assetização de internet das coisas(2024-03-07) Alves, David Pierre; Burégio, Vanilson André de Arruda; http://lattes.cnpq.br/3518416272921878; http://lattes.cnpq.br/3465709031395966This paper discusses and demonstrates the technical doability of serving things (as in Internet of Things) as assets. While existing initiatives focus on the conversion of things into services as part of the servitization process, there are not initiatives that focus on thing conversion into assets as part of the assetization process. Assetization permits to model things from a management perspective in terms of depreciation over time, transferability across locations, disposability after use, and convertibility across platforms. Thanks to assetization, things would provide economical, informational, operational, and regulatory benefits to their owners (whether moral or juridical).Item Smart Tour PE: um aplicativo android para monitoramento remoto de pontos turísticos no estado Pernambuco(2021-07-13) Fonsêca, Eder Lucena Andrade da; Araújo, Danilo Ricardo Barbosa de; http://lattes.cnpq.br/2708354422178489; http://lattes.cnpq.br/9564226085565142The tourism sector has been growing sustainably since the 90s, and not even the period of economic downturn at the time was able to stop it. In recent years, around 2018 and 2019, the sector was breaking new records of international arrivals, with the COVID19 pandemic being the only “disaster” capable of stopping this success streak. More than a year after the beginning of the pandemic, thanks to the medical advances allowing the creation of effective vaccines and viable means to return to normality, it is expected that the search for tourist destinations will grow again very soon, with ecotourism being pointed out as the most likely niche to be sought after. Therefore, it is important that technological solutions are made available to support tourism, especially ecotourism. This undergraduate thesis is the idealization of a tool to help tourists dynamically choose their next travel destination based on the location’s real time weather. Accurate information about the climate will ensure that tourists make the most of their leisure time, being able to visit a place that most suits them, from beaches to tree lined hiking trails in preservation areas, based on climate reports. The real time weather reports from tourist attractions will be displayed through an application idealized in this undergraduate thesis, designed to work on mobile devices with internet access. This application will use information from weather stations installed in tourist attractions in the state of Pernambuco during the execution of the research project related to this undergraduate thesis, also offering the user geolocation data, video streaming from local cameras, routes to access the desired location, as well as additional information about utility telephones and a panic buttons for emergencies. According to usability tests carried out with the target audience, only 3% of them considered the application difficult to use and 97% considered it easy or extremely easy to use. In addition, the application scored 75 points in the Net Promoter Score indicator, with the average for the tourism sector in Brazil being 70 points, additionally to several other positive indicators to be explained later.Item Development of machine learning models for the prediction of dissolved oxygen in aquaculture 4.0(2021-02-24) Freitas, Fábio Alves de; Nóbrega, Obionor de Oliveira; Lins, Fernando Antonio Aires; http://lattes.cnpq.br/2475965771605110; http://lattes.cnpq.br/8576087238071129; http://lattes.cnpq.br/5725435192607619The world faces the problem of feeding a growing population, which will reach more than 9 billion people by 2050. Thus, there is a need to develop activities that promote food production, within the dimensions of sustainability (social, technicaleconomic, and environmental). In this context, IoT systems focused on aquaculture 4.0 stand out, which allows the cultivation of high productions per unit of volume, with low environmental impact. However, these systems need to be extremely controlled, requiring sensors to perform realtime readings of water metrics, with emphasis on the dissolved oxygen (DO) sensor, which plays an essential role in determining the quality and quantity of available habitat for the organisms present in the system. Even with this importance, this sensor is often not used, due to its high associated cost. As an alternative solution to this problem, machine learning models have been proposed to predict DO, using temperature and pH readings as inputs. Experiments were carried out comparing different data scaling techniques and the prediction performance in different seasons of the year and regression metrics were used to evaluate the implemented models. The results showed that the proposed LSTM model is capable of making OD predictions and being applied in IoT and aquaculture 4.0 systems.Item Uma revisão sistemática sobre avaliação do consumo de energia em nuvem das coisas(2021-12-10) Ferreira, Emerson Severino de Oliveira Ramos; Sousa, Erica Teixeira Gomes de; http://lattes.cnpq.br/9899077867723655; http://lattes.cnpq.br/9000455288391839IoT devices are used in many types of vertical industries and consumer markets. In 2020 there were around 8 billion devices connected around the world, and the forecast for 2030 is to have more than 25 billion devices connected. Furthermore, the world market for IoT devices in the government area alone will transact around $21 billion in 2022, where more than 50% of that amount will be for external surveillance equipment. Which represents a 36% increase in comparison with 2020. Nowadays, research is heading towards the integration of Cloud Computing and the Internet of Things (IoT), thus creating the concept of Cloud of Things (CoT). CoT aims to offer computational resources in a pervasive and ubiquitous way, in which IoT characteristics are available as services through Cloud Computing. In CoT, Cloud acts as a middleware that makes the interaction between objects (Things) and users/applications in a transparent way, eliminating the complexity which facilitates the development of applications that interact with smart objects, which facilitate their utilization in areas as Healthcare, Smart Cities, Smart Home, Video Surveillance, Smart Mobility, Smart Energy and others.In CoT environments, a large amount of communication and data transmission affected by IoT devices degrade the energy efficiency of these environments, affecting the quality of services. In this way, this work describes a systematic review the strategies for evaluating the energy consumption in Cloud of Things. This systematic review aims to bring together published studies related to energy consumption assessment in IoT and Cloud of Things, for an analysis of the methodologies employed in these works and proposition of future work, about cloud of things energy consumption assessment.