01. Universidade Federal Rural de Pernambuco - UFRPE (Sede)
URI permanente desta comunidadehttps://arandu.ufrpe.br/handle/123456789/1
Navegar
12 resultados
Resultados da Pesquisa
Item Predição do consumo energético de dispositivos LoRa usando aprendizagem de máquina(2024-12-10) Pimentel, Henrique Pablo Pinheiro dos Santos; Araújo, Danilo Ricardo Barbosa de; http://lattes.cnpq.br/2708354422178489; http://lattes.cnpq.br/0078523045227122A Internet das Coisas (IoT) é um conceito em constante evolução que tem conquistado destaque tanto na comunidade acadêmica quanto na indústria. Dentro dela, o consumo energético é um fator fundamental para determinar o tempo de funcionamento dos dispositivos e a frequência necessária para realizar a manutenção deles. Este artigo investiga a aplicação de algoritmos de aprendizado de máquina para predição do consumo energético de dispositivos IoT-LoRa, permitindo estimar a duração da bateria dos dispositivos e sua autonomia. A metodologia considerou a criação de um conjunto de dados a partir de experimentos com placas de desenvolvimento Event stream processing (ESP32), capturando métricas como tempo de hibernação, tipo de conexão e consumo energético. Técnicas de Inteligência Artificial (IA) são então aplicadas para prever o consumo energético com base nessas variáveis. De acordo com os resultados obtidos, a melhor técnica para prever o consumo energético é a Decision Tree, com um coeficiente de determinação superior a 96%. O estudo contribui para processos decisórios que visam selecionar dispositivos IoT considerando a autonomia projetada para as baterias de tais dispositivos.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 Desenvolvimento de uma infraestrutura em nuvem para monitoramento de ninhos de tartarugas marinhas(2024-03-08) Silva, Wanderson Moura da; Medeiros, Victor Wanderley Costa de; http://lattes.cnpq.br/7159595141911505This Course Completion Work proposes a monitoring system for sea turtle nesting, using the ThingsBoard platform to create a monitoring dashboard. The study seeks to integrate Internet of Things (IoT) technologies and community involvement strategies to improve the conservation of these species, whose existence has long been threatened by various predatory factors. The application on the ThingsBoard platform makes it possible to obtain essential data in real time, such as movement and temperature from devices installed inside the nest. The implemented dashboard will provide a clear visual representation of the status of each monitored nest, automatically generating an alert when critical events occur, such as an excessive increase in temperature or movements that cause the incubated eggs to hatch. The dashboard, in addition to providing crucial information for researchers and environmentalists, will be accessible to the local community through an exclusive mobile application. The project review encompasses ongoing improvement strategies, emphasizing collaboration with local experts and active community participation to optimize the effectiveness of the monitoring application. The central role of the dashboard developed on the ThingsBoard platform is to receive and present data from devices installed in turtle nests, to monitor temperature and movement. This system facilitates understanding and analysis of data, providing insights into the possibility of egg hatching, and contributing to the effective conservation of sea turtles.Item Desenvolvimento de um dispositivo sensor para monitoramento de ninhos de tartarugas marinhas(2024-03-10) Arruda, André Luiz Ribeiro; Medeiros, Victor Wanderley Costa de; http://lattes.cnpq.br/7159595141911505; http://lattes.cnpq.br/7895899500265397The preservation of sea turtles is crucial for marine ecology and global biodiversity, as they play important roles in maintaining coastal and marine ecosystems. Currently, some non-governmental organizations dedicated to this cause monitor nests on beaches along the brazilian coast manually, which requires time and human resources. To streamline this process, this study proposes the implementation of an IoT device equipped with sensors for monitoring sea turtle nests. Utilizing Long-Range, Low-Power (LoRa) communication technology, the device aims to enhance monitoring efficiency and accuracy, thereby contributing to the conservation of these vulnerable species.Item Prototipação de um sistema de localização utilizando Redes LoRaWAN(2024-03-05) Maia, Pedro Lopes; Medeiros, Victor Wanderley Costa de; http://lattes.cnpq.br/7159595141911505; http://lattes.cnpq.br/2161981667043569With the proliferation of the use of IoT technologies, efficient solutions in terms of battery usage and applicability for device positioning have become increasingly necessary due to the demand for location-based services. In this context, signal-based localization techniques, such as fingerprinting, represent a very appropriate solution as they meet the requirements of these applications. In this study, a public dataset containing RSSI values from a LoRaWAN network was used to create machine learning models to evaluate their effectiveness in positioning LoRa devices, offering an alternative to GPS, which due to the high power consumption of device batteries, in many cases, is not viable for IoT systems. After evaluating hyperparameters and applying appropriate methodologies for each algorithm studied, a model was obtained capable of making predictions with an average error of 301.34 meters and a median of 164.26 meters.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.Item Desenvolvimento de software para dimensionamento automático de painéis fotovoltaicos aplicados a sistemas IoT com restrição energética(2022-10-17) Maia, Bruno Lins; Medeiros, Victor Wanderley Costa de; http://lattes.cnpq.br/7159595141911505; http://lattes.cnpq.br/4677794271430249The growth of the IoT (Internet of Things) systems market has generated a growing demand for resources to power these devices. Many of them are used in applications and regions where access to electrical energy is restricted. One alternative to this challenge is using solar energy, which is widely available, especially in Brazil, due to its favorable geographic location. Given this scenario, this work proposes the study and implementation of a software tool capable of providing technical specifications of a photovoltaic system aimed at embedded devices with energy restrictions.Item Desenvolvimento de um sistema integrado baseado em IoT para automação de um Clinostato 3D(2022-08-23) D’Amorim, João José Antonio Souza; Albuquerque, Jones Oliveira de; http://lattes.cnpq.br/1220553574304474The integrated system based on IoT for automation, is a set of technological devices aiming at microgravity in an Internet control and microgravity simulator. Terrestrial gravity is capable of masking scientific and technological experiments, in view, the 3D Clinostat is able to promote a microgravity environment offering a more accurate result in various types of experiments. The extra axis speed per minute, temperature of the two axis stepper motors and the environment, the values of the three axes x,y and z of the accelerometer and the values of the x,y and z axes of the gyroscope, speed sensors, three, temperature, accelerometer and gyroscopes to the equipment. Aiming at a simple and intuitive user cloud in a simple way and values of the data obtained, with the purpose of informing and controlling, simultaneously, the equipment, the values in a spreadsheet in the intuitive display in an IoT dashboard platform in realtime and sends alerts about the operation through a Bot on an instant messaging communication platform. The proposed integrated is capable of extracting the aforementioned data from the precision sensors, through a simple and objective measurement system, in the form of a real system and auxiliary measurement for measuring the tested equipment.