In the last decade, with the extensive use of mobile electronic and wireless communication devices, there is a growing need for context aware applications and many pervasive computing applications have become integral parts of our daily lives. Context aware recommender systems are one of the popular ones in this area. Such systems surround the users and integrate with the environment / hence, they are aware of the users&#039 / context and use that information to deliver personalized recommendations about everyday tasks. In this manner, predicting user&rsquo / s next activity preferences with high accuracy improves the personalized service quality of context aware recommender systems and naturally provides user satisfaction. Predicting activities of people is useful and the studies on this issue in ubiquitous environment are considerably insufficient. Thus, this thesis proposes an activity prediction model to forecast a user&rsquo / s next activity preference using past preferences of the user in certain contexts and current contexts of user in ubiquitous environment. The proposed model presents a new approach for activity prediction by taking advantage of ontology. A prototype application is implemented to demonstrate the applicability of this proposed model and the obtained outputs of a sample case on this application revealed that the proposed model can reasonably predict the next activities of the users.

In this thesis work, a certificate based authentication model supported by mobile devices is provided for ubiquitous computing environments. The model primarily aims to create an infrastructure for controlling and regulating access requests through mobile devices to local resources and services. The model also allows users from different domains to use local resources and services within the scope of agreements between domains. In addition to conceptual description of the model, a real prototype implementation is developed and successful application of the model is demonstrated. Within the prototype implementation, a mobile application is developed for access requests and sensors are used as representative local resources. Sample cases applied on the prototype demonstrate applicability and feasibility of the model.

Recent advances in technology are changing the way how everyday activities are performed. Technologies in the traffic domain provide diverse instruments of gathering and analysing data for more fuel-efficient, safe, and convenient travelling for both drivers and passengers. In this article, we propose a reference architecture for a context-aware driving assistant system. Moreover, we exemplify this architecture with a real prototype of a driving assistance system called Driving coach. This prototype collects, fuses and analyses diverse information, like digital map, weather, traffic situation, as well as vehicle information to provide drivers in-depth information regarding their previous trip along with personalised hints to improve their fuel-efficient driving in the future. The Driving coach system monitors its own performance, as well as driver feedback to correct itself to serve the driver more appropriately.

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-31T13:25:42Z No. of bitstreams: 1 Claudio Manoel.pdf: 2235875 bytes, checksum: 09f2ae854210974f87252bad3c5b1df9 (MD5) / Made available in DSpace on 2017-08-31T13:27:28Z (GMT). No. of bitstreams: 1 Claudio Manoel.pdf: 2235875 bytes, checksum: 09f2ae854210974f87252bad3c5b1df9 (MD5) Previous issue date: 2015-05-27 / The use and popularity of mobile devices has been growing vertiginously, as well an the cloud computing as instrument to store data and services, making feasible the combination of these two technologies. One of the biggest obstacles is the mobile device’s security and ergonomics to provide security for transporting its data without performance degradation. This work proposes a context-aware security mechanism for mobile devices in cloud computing. In addition, it is used the TLS technology to create a secure channel of data sent between mobile device’s client and the cloud server, authenticating them via public key cryptography. At the same time, it provides an appropriate level of security, and analyses the context of the mobile device from the Fuzzy logic. The impact of the mechanism on the mobile device’s performance were measured through experiments. / O uso e a popularidade dos dispositivos móveis vem crescendo vertiginosamente, bem como a computação em nuvem como instrumento para armazenar dados e serviços, tornando-se viável a união dessas duas tecnologias. Um dos maiores obstáculos é a questão da segurança e ergonomia do dispositivo móvel que necessita provê-lo ao trafegar dados sem haver degradação de seu desempenho. Este trabalho propõe então um mecanismo de segurança ciente do contexto para Computação em Nuvem Móvel. Em adição, utiliza-se a tecnologia Transport Layer Security (TLS) para criar um canal seguro de envio de dados entre o cliente do dispositivo móvel e o servidor da Nuvem, autenticando-o por meio de criptografia de chave pública. Paralelamente, para prover um nível de segurança apropriado, analisase o contexto do dispositivo móvel a partir da lógica Fuzzy. O impacto do mecanismo no desempenho do dispositivo móvel foi medido por meio de experimentos.

A certificate based approach is proposed for access control operations of context aware systems for multi domain environments. New model deals with the removal of inter-domain communication requirement in access request evaluation process. The study is applied on a prototype implementation with configuration for two dierent cases to show the applicability of the proposed certificate based, context aware access control model for multi domain environments. The outputs for the cases show that proposed access control model can satisfy the requirements of a context aware access control model while removing inter domain communication needs which may cause some latency in access request evaluation phase.

Weighted granular best matching algorithm is proposed for the operation of context matching in context-aware computing systems. New algorithm deals with the subjective, fuzzy and multidimensional characteristics of contextual information by using weights and a granular structure for contextual information. The proposal is applied on a case: CAPRA &ndash / Context-Aware Personal Reminder Agent tool to show the applicability of the new context matching algorithm. The obtained outputs showed that proposed algorithm produces the results which are more sensitive to the user&rsquo / s intention, more adaptive to the characteristics of the contextual information and applicable to a current Context-aware system.

Context-aware computing aims at making mobile devices sensitive to the social and physical settings in which they are used. A necessary requirement to achieve this goal is to enable those devices to establish a shared understanding of the desired settings. Establishing a shared understanding entails the need to manipulate sensed data in order to capture a real world situation wholly, conceptually, and meaningfully. Quite often, however, the data acquired from sensors can be inexact, incomplete, and/or uncertain. Inexact sensing arises mostly due to the inherent limitation of sensors to capture a real world phenomenon precisely. Incompleteness is caused by the absence of a mechanism to capture certain real-world aspects; and uncertainty stems from the lack of knowledge about the reliability of the sensing sources, such as their sensing range, accuracy, and resolution. The thesis identifies a set of criteria for a context-aware system to capture dynamic real-world situations. On the basis of these criteria, a distributed architecture is designed, implemented and tested. The architecture consists of Primitive Context Servers, which abstract the acquisition of primitive contexts from physical sensors; Aggregators, to minimise error caused by inconsistent sensing, and to gather correlated primitive contexts pertaining to a particular entity or situation; a Knowledge Base and an Empirical Ambient Knowledge Component, to model dynamic properties of entities with facts and beliefs; and a Composer, to reason about dynamic real-world situations on the basis of sensed data. Two additional components, namely, the Event Handler and the Rule Organiser, are responsible for dynamically generating context rules by associating decision events ? signifying a user?s activity ? with the context in which those decision events are produced. Context-rules are essential elements with which the behaviour of mobile devices can be controlled and useful services can be provided. Four estimation and recognition schemes, namely, Fuzzy Logic, Hidden Markov Models, Dempster-Schafer Theory of Evidence, and Bayesian Networks, are investigated, and their suitability for the implementation of the components of the architecture of the thesis is studied. Subsequently, fuzzy sets are chosen to model dynamic properties of entities. Dempster-Schafer?s combination theory is chosen for aggregating primitive contexts; and Bayesian Networks are chosen to reason about a higher-level context, which is an abstraction of a real-world situation. A Bayesian Composer is implemented to demonstrate the capability of the architecture in dealing with uncertainty, in revising the belief of the Empirical Ambient Knowledge Component, in dealing with the dynamics of primitive contexts and in dynamically defining contextual states. The Composer could be able to reason about the whereabouts of a person in the absence of any localisation sensor. Thermal, relative humidity, light intensity properties of a place as well as time information were employed to model and reason about a place. Consequently, depending on the variety and reliability of the sensors employed, the Composer could be able to discriminate between rooms, corridors, a building, or an outdoor place with different degrees of uncertainty. The Context-Aware E-Pad (CAEP) application is designed and implemented to demonstrate how applications can employ a higher-level context without the need to directly deal with its composition, and how a context rule can be generated by associating the activities (decision events) of a mobile user with the context in which the decision events are produced.

The improvement of throughput rates is a crucial factor at higher education institutions; hence, university departments focus on improving pass rates per module. This study investigated how lecturers in the School of Computing (SoC) at the University of South Africa, use technology for improving throughput rates in an Open Distance Learning (ODL) context. The study sought answers to the main research question on how lecturers in the SoC use technology for improving throughput rates in an ODL institution. A mixed research methods approach was used, where quantitative data was extracted from the university systems and integrated with the qualitative data collected from interviews. Thirteen lecturers for the thirty modules under investigation were interviewed. A thematic analysis was used on the qualitative data, and quantitative data was analysed using rankings and correlation coefficients, leading to the interpretation that the use of myUnisa technology assisted to improve throughput on the modules. / Mathematics Education / M. Sc. (Computing Education)