The global mobile application market is booming in all directions and business giants, viz. Google and Apple, have acknowledged the huge expansion in their Application Market and App Store. There is a demand though for a system that can elevate the momentum of context-aware mobile applications, where an application’s behavior is customized according to context information. This thesis proposes a context-aware system that provides mobile Applications as a Service (AppaaS). AppaaS handles various context information including location information, user profile, device profile, user ratings, and current time to provision the best relevant mobile application to such a context. AppaaS also supports state preservation, where application-specific data that is relevant to a user is stored for future reference. Our prototype demonstrates a seamless system performance with respect to finding relevant applications to a specific context and controlling the applications functions according the users requirements and access privileges. We also demonstrate how AppaaS can preserve an applications state when a user is to reuse the same application again. / Thesis (Master, Computing) -- Queen's University, 2013-01-31 20:23:11.063

Submitted by Marcio Filho (marcio.kleber@ufba.br) on 2017-06-06T13:37:20Z No. of bitstreams: 1 dissertacao_marcelo_mendonca.pdf: 29068279 bytes, checksum: 80fb8fb6ea4e3852373e2a42c4467ea6 (MD5) / Approved for entry into archive by Vanessa Reis (vanessa.jamile@ufba.br) on 2017-06-16T15:11:16Z (GMT) No. of bitstreams: 1 dissertacao_marcelo_mendonca.pdf: 29068279 bytes, checksum: 80fb8fb6ea4e3852373e2a42c4467ea6 (MD5) / Made available in DSpace on 2017-06-16T15:11:16Z (GMT). No. of bitstreams: 1 dissertacao_marcelo_mendonca.pdf: 29068279 bytes, checksum: 80fb8fb6ea4e3852373e2a42c4467ea6 (MD5) / Correctly identifying the road area on an image is a crucial task for many traffic analyses based on surveillance cameras and computer vision. Despite that, most of the systems do not provide this functionality in an automatic fashion; instead, the road area needs to be annotated by tedious and inefficient manual processes. This situation results in further inconveniences when one deals with a lot of cameras, demanding considerable effort to setup the system. Besides, since traffic analysis is an outdoor activity, cameras are exposed to disturbances due to natural events (e.g., wind, rain and bird strikes), which may require recurrent system reconfiguration. Although there are some solutions intended to provide automatic road detection, they are not capable of dealing with common situations in urban context, such as poorly-structured roads or occlusions due to objects stopped in the scene. Moreover in many cases they are restricted to straight-shaped roads (commonly freeways or highways), so that automatic road detection cannot be provided in most of the traffic scenarios. In order to cope with this problem, we propose a new approach for road detection. Our method is based on a set of innovative solutions, each of them intended to address specific problems related to the detection task. In this sense, a context-aware background modeling method has been developed, which extracts contextual information from the scene in order to produce background models more robust to occlusions. From this point, segmentation is performed to extract the shape of each object in the image; this is accomplished by means of a superpixel method specially designed for road segmentation, which allows for detection of roads with any shape. For each extracted segment we then compute a set of features, the goal of which is supporting a decision tree-based classifier in the task of assigning the objects as being road or non-road. The formulation of our method — a road detection carried out by a combination of multiple features — makes it able to deal with situations where the road is not easily distinguishable from other objects in the image, as when the road is poorly-structured. A thorough evaluation has indicated promising results in favour of this method. Quantitatively, the results point to 75% of accuracy, 90% of precision and 82% of recall over challenging traffic videos caught in non-controlled conditions. Qualitatively, resulting images demonstrate the potential of the method to perform road detection in different situations, in many cases obtaining quasi-perfect results.

<p>As the development of context aware applications has evolved, there has been a corresponding increase in need for more sophisticated system. The aim for this thesis is the development of a dynamical P2P network system which is based on locations. The P2P network is self organizing and in a lightweight format. Modern technical solutions including   AGPS have facilitated the work associated with the ability to position users and modern mathematical solutions such as spherical trigonometry provides the P2P system with the necessary accuracy even for short distances. The P2P system works on different Java platforms including JSE, JME and Android. Unfortunately the 3G network distributor has not yet solved a NAT traversal problem, which means that the P2P network self organization and architecture has only been proved by means of simulations. Another problem is that certain mathematical formulas are required for the spherical trigonometry and the limitation for JME is that it is unable to handle inverse trigonometry. However, the Android and JSE versions can form a correct P2P network, under the condition that the Android device uses a WIFI connection point outside the 3G distributor network system. This thesis reports the successful testing of the locations-based P2P network.</p> / MediaSense

As the development of context aware applications has evolved, there has been a corresponding increase in need for more sophisticated system. The aim for this thesis is the development of a dynamical P2P network system which is based on locations. The P2P network is self organizing and in a lightweight format. Modern technical solutions including   AGPS have facilitated the work associated with the ability to position users and modern mathematical solutions such as spherical trigonometry provides the P2P system with the necessary accuracy even for short distances. The P2P system works on different Java platforms including JSE, JME and Android. Unfortunately the 3G network distributor has not yet solved a NAT traversal problem, which means that the P2P network self organization and architecture has only been proved by means of simulations. Another problem is that certain mathematical formulas are required for the spherical trigonometry and the limitation for JME is that it is unable to handle inverse trigonometry. However, the Android and JSE versions can form a correct P2P network, under the condition that the Android device uses a WIFI connection point outside the 3G distributor network system. This thesis reports the successful testing of the locations-based P2P network. / MediaSense

This study explores the subject of providing personalized services to mobile users, by exploiting relevant domain knowledge (i.e. contextual information). Although the process of gathering, modelling and processing of context has been extensively researched, there are only a few studies in the literature showing how such context can be effectively utilized to provide services valuable to the general public. Instead, there exist a multitude of examples of services targeted towards specialized audiences, either because the scope of each service is not of broad interest, or because of custom software and/or hardware requirements. Part of the reason why the scope of such services is so narrow can also be attributed to short service life cycle. While all such services offer relative value to interested audiences, we support that contemporary mainstream mobile devices are now more than ever capable of running large-scale context-aware applications as the required combination of hardware and software is available. This licentiate thesis challenges the current state-of-the art in context aware services by proposing an alternative perspective, driven from the appreciation of the user rather than from the ideas of a system designer. The potential impact of this work lies in the set of diverse applications which have been implemented using existing mainstream technology, targeting large and diverse sets of audiences. In order to realize the vision, we have implemented a context-aware system featuring a flexible architecture that is able to scale to the requirements of different services. In order to demonstrate the flexibility of this architecture as well as to prove the aforementioned claims, we have implemented support for two context aware services which have demonstratively had a large appeal to users. These scenarios not only include full implementation and exposure to public use, but they also differ from each other in terms of their functionality: A printing service where the printing resources are scattered within a workspace environment. The system selects the most appropriate printer for a mobile user to print his or her document on, based on the user's location and nature of the document relative to the capabilities of each of the printers. A recommender system service where mobile users are forwarded Web feeds of related interest, based on each user's social signature on the web (i.e. social context). The reader should note the tangible nature of context used in the services above, as context is not only associated - by tradition - with knowledge relative to physical stimuli (e.g. location), but is also related to information present on contemporary media such as the World Wide Web. / QC 20110516

Information is useless unless it is used whilst still applicable. Having a system that notifies the user of important messages using the most appropriate medium and device will benefit users that rely on time critical information. There are several existing systems and models for mobile notification as well as for adaptive mobile notification using context awareness. Current models and systems are typically designed for a specific set of mobile devices, modes and services. Communication however, can take place in many different modes, across many different devices and may originate from many different sources. The aim of this research was to develop a model for adaptive mobile notification using context awareness. An extensive literature study was performed into existing models for adaptive mobile notification systems using context awareness. The literature study identified several potential models but no way to evaluate and compare the models. A set of requirements to evaluate these models was developed and the models were evaluated against these criteria. The model satisfying the most requirements was adapted so as to satisfy the remaining criteria. The proposed model is extensible in terms of the modes, devices and notification sources supported. The proposed model determines the importance of a message, the appropriate device and mode (or modes) of communication based on the user‘s context, and alerts the user of the message using these modes. A prototype was developed as a proof-of-concept of the proposed model and evaluated by conducting an extensive field study. The field study highlighted the fact that most users did not choose the most suitable mode for the context during their initial subscription to the service. The field study also showed that more research needs to be done on an appropriate filtering mechanism for notifications. Users found that the notifications became intrusive and less useful the longer they used them.

This thesis presents the development and evaluation of an enhanced turn-key indoor positioning system (IPS) for tracking the mobility patterns of older adults in residential settings. The design of the IPS hardware and software focused on usability in the context of aging-in-place, while maintaining high data quality, reduced incidences of missing data, and elevated room detection accuracy, with the highest accuracy reaching 99.47%. By integrating positional data with IMU sensors, this system not only captures precise locations but also identifies activity states and contextual information, establishing a detailed profile of mobility patterns. A 'floor filter' in the data processing models was developed to address vertical alignment challenges commonly encountered in multi-story dwellings. This adjustment improved prediction accuracies, with an average accuracy increase of 3.33% to 6.28% across various models. Among these, the Multi-Layer Perceptron Neural Network (MLP NN) and Shallow Neural Network (SNN) exhibited the highest accuracies for user room location predictions. Furthermore, we demonstrated the practical application of these technologies in a real-world setting through pilot clinical studies involving older adults. This study not only validated the integration of IPS and IMU data but also facilitated the establishment of behavioral trends that are crucial for context-aware analysis. The system's ability to adapt to different indoor environments without extensive setup, alongside its proven accuracy and reliability in capturing detailed mobility and activity information, underscores its potential to enhance elderly care and support aging in place. By leveraging advanced machine learning models and innovative data processing techniques, this work contributes to the field by offering a robust, scalable solution for monitoring the mobility patterns of the elderly, thus paving the way for future healthcare applications designed to accommodate the complexities of aging populations. / Thesis / Master of Applied Science (MASc) / This project develops a system that helps track the location and movement of older adults in their homes to support their independence and reduce stress on healthcare services. It improves on current technology by providing more accurate tracking inside the home. The system uses sensors to monitor how active someone is and understands the context of their movements—like whether they are resting or moving around—which helps in assessing both their physical and mental well-being. The results show that this technology is effective in tracking daily activities and can help in providing better care for older adults.

<p>This research concerns exploiting knowledge of the user's environment (i.e., context information) to enrich a user's communication making it more personal, by ensuring that the user receives only relevant messages and calls in his/her current context, and to facilitate more opportunities for communication interactions with people that are in the same context and that share the same interests as this user. We describe in this licentiate thesis the concepts of context-addressed messaging and context-aware session control that enable users to: (1) send messages to others based on their context, rather than their network address and (2) to initiate, adapt, and terminate user's communication sessions based on this user's current context, respectively. These concepts address questions such as: how to discover, select, and switch to an optimal communication means to meet varying user, contextual, communication, and device resource requirements and preferences. A key to solving these problems is to create a representation of the user's context-dependent preferences and to process the user's context-dependent preferences which are part of context triggers. These context triggers can initiate a communication event upon a particular context update. Additionally, in order to provide the described context-aware communication functions, these mechanisms need timely access to the acquired (desired) context information. This in turn raises a plethora of other questions, such as how to discover sensors that provide the desired context information; how to acquire raw context data from these sensors; how to abstract, process, and model this data to become "understandable" to applications and system components; and how to distribute this context to applications that are running on different nodes.</p><p> </p><p>This research is split into three different parts. The first part concerns investigating and implementing context management functions. As part of this research we propose a novel approach for context synthesis using context operators. We also propose a design architecture for context-aware middleware that mediates between the sensors and applications, and that is able to share and retrieve context from other nodes in the network. The second part of our research concerns our proposed mechanism for context-addressed messaging. To implement this mechanism we designed our own message format, called the Common Profile for Context-Addressed Messaging (CPCAM) that is able to use any high level context to compose a context-based address. Additionally, we proposed to use context-based filtering to find the correct message recipients and determine if this message is relevant to these potential message recipients in their current context, as well as to deliver this message to the recipients' preferred device that is adapted using their preferred communication means. At the end of this second part we design context-addressed messaging system operations on top of a SIP and SIMPLE-based network infrastructure. The third part of our research describes context-aware session control mechanisms using context switch and context trigger constructs. A context-switch selects an action from a set of context-dependent actions upon an incoming communication event based on the receiver's current context. In contrast, a context trigger initiates an action based on a context update and the user's preferences that are specified in this updated context. This part illustrates in several examples the context-aware session control mechanisms, i.e. the initiation of a communication session based on the match of a user's preferences and current context, as well as adaptation and (if necessary) termination of an ongoing communication session based upon the user's context-dependent preferences.</p><p> </p><p>The research leading to this licentiate has created network and system level models necessary for implementation of a context-addressed communication system that would enable users to easily design their own personalized, context-aware communication services. The necessary constructs and properties of these models are designed and analyzed in the thesis, as well as in conference papers and other documents published in the process of doing the research for this thesis. A number of remaining open issues and challenges have been outlined as part of the future work.</p><p> </p> / EU FP6 MIDAS (Middleware Platform for Developing and Deploying Advanced Mobile Services) / EU FP6 MUSIC (Self-adapting Applications for Mobile Users In Ubiquitous Computing Environments)

This research concerns exploiting knowledge of the user's environment (i.e., context information) to enrich a user's communication making it more personal, by ensuring that the user receives only relevant messages and calls in his/her current context, and to facilitate more opportunities for communication interactions with people that are in the same context and that share the same interests as this user. We describe in this licentiate thesis the concepts of context-addressed messaging and context-aware session control that enable users to: (1) send messages to others based on their context, rather than their network address and (2) to initiate, adapt, and terminate user's communication sessions based on this user's current context, respectively. These concepts address questions such as: how to discover, select, and switch to an optimal communication means to meet varying user, contextual, communication, and device resource requirements and preferences. A key to solving these problems is to create a representation of the user's context-dependent preferences and to process the user's context-dependent preferences which are part of context triggers. These context triggers can initiate a communication event upon a particular context update. Additionally, in order to provide the described context-aware communication functions, these mechanisms need timely access to the acquired (desired) context information. This in turn raises a plethora of other questions, such as how to discover sensors that provide the desired context information; how to acquire raw context data from these sensors; how to abstract, process, and model this data to become "understandable" to applications and system components; and how to distribute this context to applications that are running on different nodes.   This research is split into three different parts. The first part concerns investigating and implementing context management functions. As part of this research we propose a novel approach for context synthesis using context operators. We also propose a design architecture for context-aware middleware that mediates between the sensors and applications, and that is able to share and retrieve context from other nodes in the network. The second part of our research concerns our proposed mechanism for context-addressed messaging. To implement this mechanism we designed our own message format, called the Common Profile for Context-Addressed Messaging (CPCAM) that is able to use any high level context to compose a context-based address. Additionally, we proposed to use context-based filtering to find the correct message recipients and determine if this message is relevant to these potential message recipients in their current context, as well as to deliver this message to the recipients' preferred device that is adapted using their preferred communication means. At the end of this second part we design context-addressed messaging system operations on top of a SIP and SIMPLE-based network infrastructure. The third part of our research describes context-aware session control mechanisms using context switch and context trigger constructs. A context-switch selects an action from a set of context-dependent actions upon an incoming communication event based on the receiver's current context. In contrast, a context trigger initiates an action based on a context update and the user's preferences that are specified in this updated context. This part illustrates in several examples the context-aware session control mechanisms, i.e. the initiation of a communication session based on the match of a user's preferences and current context, as well as adaptation and (if necessary) termination of an ongoing communication session based upon the user's context-dependent preferences.   The research leading to this licentiate has created network and system level models necessary for implementation of a context-addressed communication system that would enable users to easily design their own personalized, context-aware communication services. The necessary constructs and properties of these models are designed and analyzed in the thesis, as well as in conference papers and other documents published in the process of doing the research for this thesis. A number of remaining open issues and challenges have been outlined as part of the future work. / EU FP6 MIDAS (Middleware Platform for Developing and Deploying Advanced Mobile Services) / EU FP6 MUSIC (Self-adapting Applications for Mobile Users In Ubiquitous Computing Environments)

Vehicular Ad-hoc Network (VANET) is a special application of the Mobile Ad-hoc Network (MANET) for managing road traffic and substantially contributes to the development of Intelligent Transportation Systems (ITS). VANET was introduced as a standard for data communication between moving vehicles with and without fixed infrastructure. It aims to support drivers by improving safety and driving comfort as a step towards constructing a safer, cleaner and a more intelligent environment. Nowadays, vehicles are manufactured equipped with a number of sensors and devices called On Board Units (OBU) assisting the vehicle to sense the surrounding environment and then process the context information to effectively manage communication with the surrounding vehicles and the associated infrastructure. A number of challenges have emerged in VANET that have encouraged researchers to investigate this concept further. Many of the recent studies have applied different technologies for intelligent parking management. However, despite all the technological advances, researchers are no closer to developing a system that enables drivers to easily locate and reserve a parking space. Limited resources such as energy, storage space, availability and reliability are factors which could have contributed to the lack success and progress in this area. The task then is to close these gaps and present a novel solution for parking. This research intends to address this need by developing a novel architecture for locating and reserving a parking space that best matches the driver's preferences and vehicle profile without distracting the driver. The simple and easy-to-use mechanism focuses on the domain of an intelligent parking system that exploits the concept of InfoStation (IS) and context-aware system creating a single framework to locate and reserve a parking space. A three tier network topology comprising of vehicles, IS and the InfoStation Centre (ISC) has been proposed as the foundation of the on-street parking system architecture. The thesis attempts to develop the architecture of a parking management solution as a comfort-enhancing application that offers to reduce congestion related stress and improve the driver experience by reducing the time it takes to identify and utilise a parking space that is available.