119 resultados para context-aware computing
em Instituto Politécnico do Porto, Portugal
Resumo:
Human Computer Interaction (HCl) is to interaction between computers and each person. And context-aware (CA) is very important one of HCI composition. In particular, if there are sequential or continuous tasks between users and devices, among users, and among devices etc, it is important to decide the next action using right CA. And to take perfect decision we have to get together all CA into a structure. We define that structure is Context-Aware Matrix (CAM) in this article. However to make exact decision is too hard for some problems like low accuracy, overhead and bad context by attacker etc. Many researcher has been studying to solve these problems. Moreover, still it has weak point HCI using in safety. In this Article, we propose CAM making include best selecting Server in each area. As a result, moving users could be taken the best way.
Resumo:
Involving groups in important management processes such as decision making has several advantages. By discussing and combining ideas, counter ideas, critical opinions, identified constraints, and alternatives, a group of individuals can test potentially better solutions, sometimes in the form of new products, services, and plans. In the past few decades, operations research, AI, and computer science have had tremendous success creating software systems that can achieve optimal solutions, even for complex problems. The only drawback is that people don’t always agree with these solutions. Sometimes this dissatisfaction is due to an incorrect parameterization of the problem. Nevertheless, the reasons people don’t like a solution might not be quantifiable, because those reasons are often based on aspects such as emotion, mood, and personality. At the same time, monolithic individual decisionsupport systems centered on optimizing solutions are being replaced by collaborative systems and group decision-support systems (GDSSs) that focus more on establishing connections between people in organizations. These systems follow a kind of social paradigm. Combining both optimization- and socialcentered approaches is a topic of current research. However, even if such a hybrid approach can be developed, it will still miss an essential point: the emotional nature of group participants in decision-making tasks. We’ve developed a context-aware emotion based model to design intelligent agents for group decision-making processes. To evaluate this model, we’ve incorporated it in an agent-based simulator called ABS4GD (Agent-Based Simulation for Group Decision), which we developed. This multiagent simulator considers emotion- and argument based factors while supporting group decision-making processes. Experiments show that agents endowed with emotional awareness achieve agreements more quickly than those without such awareness. Hence, participant agents that integrate emotional factors in their judgments can be more successful because, in exchanging arguments with other agents, they consider the emotional nature of group decision making.
Resumo:
The exhibition of information does not always attend to the preferences and characteristics of the users, nor the context that involves the user. With the aim of overcoming this gap, we propose an emotional context-aware model for adapting information contents to users and groups. The proposed model is based on OCC and Big Five models to handle emotion and personality respectively. The idea is to adapt the representation of the information in order to maximize the positive emotional valences and minimize the negatives. To evaluate the proposed model it was developed a prototype for adapting RSS news to users and group of users.
Resumo:
Multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the benefits gained from multiple interfaces come at an expense—that being higher energy consumption in an era where mobile devices need to be energy compliant. One promising solution is the usage of short-range cooperative communication as an overlay for infrastructure-based networks taking advantage of its context information. However, the node discovery mechanism, which is pivotal to the bearer establishment process, still represents a major burden in terms of the total energy budget. In this paper, we propose a technology agnostic approach towards enhancing the MAC energy ratings by presenting a context-aware node discovery (CANDi) algorithm, which provides a priori knowledge towards the node discovery mechanism by allowing it to search nodes in the near vicinity at the ‘right time and at the right place’. We describe the different beacons required for establishing the cooperation, as well as the context information required, including battery level, modes, location and so on. CANDi uses the long-range network (WiMAX and WiFi) to distribute the context information about cooperative clusters (Ultra-wideband-based) in the vicinity. The searching nodes can use this context in locating the cooperative clusters/nodes, which facilitates the establishing of short-range connections. Analytical and simulation results are obtained, and the energy saving gains are further demonstrated in the laboratory using a customised testbed. CANDi saves up to 50% energy during the node discovery process, while the demonstrative testbed shows up to 75% savings in the total energy budget, thus validating the algorithm, as well as providing viable evidence to support the usage of short-range cooperative communications for energy savings.
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Mestrado em Engenharia Informática
Resumo:
In this paper we present a mobile recommendation and planning system, named PSiS Mobile. It is designed to provide effective support during a tourist visit through context-aware information and recommendations about points of interest, exploiting tourist preferences and context. Designing a tool like this brings several challenges that must be addressed. We discuss how these challenges have been overcame, present the overall system architecture, since this mobile application extends the PSiS project website, and the mobile application architecture.
Resumo:
IEEE International Conference on Pervasive Computing and Communications (PerCom). 23 to 26, Mar, 2015, PhD Forum. Saint Louis, U.S.A..
Resumo:
To select each node by devices and by contexts in urban computing, users have to put their plan information and their requests into a computing environment (ex. PDA, Smart Devices, Laptops, etc.) in advance and they will try to keep the optimized states between users and the computing environment. However, because of bad contexts, users may get the wrong decision, so, one of the users’ demands may be requesting the good server which has higher security. To take this issue, we define the structure of Dynamic State Information (DSI) which takes a process about security including the relevant factors in sending/receiving contexts, which select the best during user movement with server quality and security states from DSI. Finally, whenever some information changes, users and devices get the notices including security factors, then an automatic reaction can be possible; therefore all users can safely use all devices in urban computing.
Resumo:
In this paper a new free flight instrument is presented. The instrument named FlyMaster distinguishes from others not only at hardware level, since it is the first one based on a PDA and with an RF interface for wireless sensors, but also at software level once its structure was developed following some guidelines from Ambient Intelligence and ubiquitous and context aware mobile computing. In this sense the software has several features which avoid pilot intervention during flight. Basically, the FlyMaster adequate the displayed information to each flight situation. Furthermore, the FlyMaster has its one way of show information.
Resumo:
Tourist recommendation systems have been growing over the last years, mainly because of the use of mobile devices to get user context. This work discuss some of the most relevant systems on the field and presents PSiS Mobile, which is a mobile recommendation and planning application designed to support a tourist during his vacations. It provides recommendations about points of interest to visit based on tourist preferences and on user and sight context. Also, it suggests a visit planning which can be dynamically adapted based on current user and sight context. This tool works like a journey dairy since it records the tourist moves and tasks to help him remember how the trip was like. To conclude, some field experiences will be presented.
Resumo:
Context-aware recommendation of personalised tourism resources is possible because of personal mobile devices and powerful data filtering algorithms. The devices contribute with computing capabilities, on board sensors, ubiquitous Internet access and continuous user monitoring, whereas the filtering algorithms provide the ability to match the profile (interests and the context) of the tourist against a large knowledge bases of tourism resources. While, in terms of technology, personal mobile devices can gather user-related information, including the user context and access multiple data sources, the creation and maintenance of an updated knowledge base of tourism-related resources requires a collaborative approach due to the heterogeneity, volume and dynamic nature of the resources. The current PhD thesis aims to contribute to the solution of this problem by adopting a Crowdsourcing approach for the collaborative maintenance of the knowledge base of resources, Trust and Reputation for the validation of uploaded resources as well as publishers, Big Data for user profiling and context-aware filtering algorithms for the personalised recommendation of tourism resources.
Resumo:
In this paper, we present PSiS (Personalized Sightseeing Tours Recommendation System) Mobile. PSiS Mobile is our proposal to a mobile recommendation and planning support system, which is designed to provide effective support during the tourist visit with context-aware information and recommendations about places of interest (POI), exploiting tourist preferences and context.
Resumo:
In this paper, we present a state of the art on applications of mobile devices to support decision of a tourist running on a trip. We focus on two types of applications, tourism recommendation and tourism guide, making a brief description of the main characteristics of each one of them. We also refer the main problems encountered on the development of applications for mobile devices, and present PSiS (Personalized Sightseeing Tours Recommendation System) Mobile, our proposal to a mobile recommendation and planning support system, which is designed to provide an effective support during the tourist visit, providing contextaware information and recommendations about places of interest (POI) to visit, based on tourist preferences and his current context.
Resumo:
Os sistemas de recomendação têm vindo a ser cada vez mais utilizados nos últimos anos. Por isso, é imprescindível que estes sistemas se adaptem à evolução da sociedade incluindo cada vez mais novas funcionalidades, tais como a adaptação do sistema ao contexto da pessoa. Esta adaptação pode ser feita através de, por exemplo, dispositivos móveis, que têm vindo a apresentar uma taxa de crescimento de vendas muito grande. Dada a crescente integração dos sistemas de recomendação com os sistemas móveis, foi elaborado um estudo sobre o estado da arte dos sistemas de auxílio ao turista que utilizam dispositivos móveis, sendo apresentadas as suas vantagens e desvantagens. Estes sistemas móveis de auxílio a turistas foram divididos em dois grupos: os que apresentam apenas a informação sobre pontos de interesse e os sistemas que são capazes de efectuar recomendações, com base no perfil do turista. Um breve estudo sobre os sistemas operativos para dispositivos móveis é apresentado, sendo especialmente focado o sistema operativo Android que foi o escolhido para esta implementação. Como os dispositivos móveis, actualmente, ainda possuem várias limitações, estas foram descritas e apresentadas as boas práticas no desenvolvimento de aplicações para este tipo de sistemas. É também apresentado um estudo que visa descobrir qual é o método mais leve e mais rápido para trocar dados entre a parte servidora e a parte móvel. Com a parte introdutória apresentada, é exposto o projecto desenvolvido nesta tese, o PSiS Mobile. Este sistema é um módulo que faz parte do projecto PSiS e pretende trazer todas as vantagens dos sistemas móveis para o sistema base já implementado. O projecto PSiS foca-se no estabelecimento de planos de visita personalizados com indicação de percursos para turistas com tempo limitado. Apoiando a definição de planos de visitas de acordo com o perfil do turista (interesses, valores pessoais, desejos, restrições, deficiências, etc.) combinando os produtos de turismo mais adequados (locais de interesse, eventos, restaurantes, etc.) em itinerários eficientes. A utilização de dispositivos móveis para acompanhamento da visita permite uma rápida interacção entre o turista e o sistema. Assim, o PSiS poderá recolher informação contextual do utilizador para que o perfil do mesmo seja enriquecido. O sistema apresentado é composto por duas partes: a parte cliente e a parte servidora. Toda a informação, como por exemplo o perfil do turista, histórico de viagens e valores de similaridade entre utilizadores está presente na parte servidora. O processo de recomendação também é efectuado pela aplicação servidora, sendo esta a responsável pela atribuição de uma classificação aos pontos de interesse tendo em conta o perfil do utilizador em causa. A base de dados do PSiS possui toda a informação relativa aos pontos de interesse numa determinada cidade ou região e o portfólio completo do histórico de visitas de cada utilizador. A componente móvel é uma parte muito importante para o sistema, pois interage com o utilizador no terreno. Um dispositivo móvel como o PDA, não só permite a apresentação de informação relevante ao utilizador, como também permite a recolha automática de informação contextual (por exemplo, a localização). Toda esta informação contribui para a definição de um perfil completo e para uma melhor adaptação do sistema às necessidades do utilizador. De forma a nem sempre estar dependente do servidor, a aplicação móvel possui rotinas para a realização de recomendações básicas. Ou seja, a aplicação móvel não realiza a classificação dos pontos de interesse, mas apenas mostra os principais resultados já formados pela parte servidora. Por exemplo, se um utilizador gostar de comida Chinesa, um restaurante Chinês nas imediações irá ter uma boa classificação e, por isso, ser recomendado. A aplicação móvel mostra ao turista o percurso definido para o dia em que o mesmo se encontra, sendo feito o rastreio do trajecto que o mesmo efectua. Assim, o sistema consegue saber se o horário do planeamento está a ser cumprido ou não. Caso não esteja, é invocado um algoritmo de planeamento que irá tentar corrigir o atraso ou o adiantamento perante o horário inicial. Depois de visitar um ponto de interesse, é pedido ao utilizador para fornecer feedback sobre o mesmo. Se desejado também é possível mostrar os pontos de interesse existentes perto do turista (usando as coordenadas GPS obtidas pelo dispositivo móvel) organizados por categorias, raio de distância, etc. Apesar dos dispositivos móveis possuírem várias restrições, pretendeu-se proporcionar ao utilizador uma boa experiência, através de uma aplicação rápida, de fácil utilização e adaptável, incluindo funcionalidades de planeamento, realidade aumentada e integração com a rede social do sistema. Todos estes factores contribuem para a disponibilização de informação detalhada ao turista.
Resumo:
This paper reports on the design and development of an Android-based context-aware system to support Erasmus students during their mobility in Porto. It enables: (i) guest users to create, rate and store personal points of interest (POI) in a private, local on board database; and (ii) authenticated users to upload and share POI as well as get and rate recommended POI from the shared central database. The system is a distributed client / server application. The server interacts with a central database that maintains the user profiles and the shared POI organized by category and rating. The Android GUI application works both as a standalone application and as a client module. In standalone mode, guest users have access to generic info, a map-based interface and a local database to store and retrieve personal POI. Upon successful authentication, users can, additionally, share POI as well as get and rate recommendations sorted by category, rating and distance-to-user.