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The past few years have seen an exponential growth in data collection capabilities. Unfortunately, the ability to process this vast amount of data has not kept pace with this growth. Taking full advantage of these increased capabilities requires scalable, computationally efficient algorithms to timely and robustly extract actionable information from the very large data sets generated by the sensors...
Software engineering has been historically topdown. From a fully specified problem, a software engineer needs to detail each step of the resolution to get a solution. The resulting program will be functionally adequate as long as its execution environment complies with the original specifications. With their large amount of data, their ever changing multi-level dynamics, smart cities are too complex...
In normal conversation, the meanings of data, information and knowledge can often be used interchangeably. At some level of approximation, these three terms are near enough the same. In the domain of computing and in particular the topic known as artificial intelligence, to accept this generalisation is to lose some resolution in a plausible model of the origin of thought. This paper offers an interpretation...
For improving e-health services, we propose a context-aware framework to monitor the activities of daily living of dependent persons. We define a strategy for generating long-term realistic scenarios and a framework containing an adaptive monitoring algorithm based on three approaches for optimizing resource usage. The used approaches provide a deep knowledge about the person's context by considering:...
The advance of sensor and networking technologies led to the development of many WSN-based context-aware applications. Especially, WSN-based indoor location-based services (LBS) have been studied recently. To understand the sensing data in those context-aware applications, we need to abstract the low-level sensor data into high-level context information to understand the data and transmit/process/store...
The "Internet of Things" (IoT) represents an em- bodiment of the continuous convergence between the physical facet of human activities and its reflection on the informa- tion world. In the context of “Industrial Internet”, where the operation of complex physical machinery is integrated with networked sensors and software applications, IoT is under- stood as a technological enabler of significant...
As miniaturized and high functional sensor devices like smartphones have spread, we can utilize large amounts of sensing data gathered from these devices. Participatory sensing is one of modern sensor-based application models in which users provide their sensing data including their personal data as well as get services. Current models, however, have limitations on flexible data flow based on provider's...
Service Creation Environments facilitate the creation of complex services and play a major role in the software industry. In this context, we aim at developing a domain-specific framework (networking domain) that uses a chain of existing "off-the-shelf" tools that are integrated together from the design phase to the verification activities. In this paper, we propose a new meta-model that...
Smart systems are defined as miniaturized devices that incorporate functions of sensing, actuation, control, and adaptation. They are capable of describing and analyzing a situation, and taking decisions based on the available data in a predictive or adaptive manner, thereby performing smart (intelligent) actions. In order to effectively manage any situation confronted by it, the system components...
This paper provides an overview of CyMRisk, an experimental architecture for computing mission risk due to cyber attack. In its current form, the approach employs a simulation of key aspects of a target business/mission process as well as attacker behavior to estimate mission impact due to cyber attacks. In addition, CyMRisk estimates worst case attacker level of effort associated with carrying out...
Recent studies recognize that health is influenced broadly by a multitude of factors of different types, including medical, genetic, environmental, social and behavioral factors. Developing successful health interventions therefore requires taking into account all these factors as well as the interactions between them. However, intervention designers have traditionally had access only to a very limited...
This paper addresses a major issue with patient's homecare systems which aim at improving the quality of care and the assistance services. To ensure effectiveness and efficiency, these systems have to provide physiological and environmental data acquired by sensors in a continual basis and transferred them to central middleware to be processed. This process has for consequence to generate a large...
The penetration of mobile devices equipped with various embedded sensors also make it possible to capture the physical and virtual context of the user and surrounding environment. Further, the modeling of human behaviors based on those data becomes very important due to the increasing popularity of context-aware computing and people-centric applications, which utilize users' behavior pattern to improve...
As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a substantial acceleration of the growth rate in the future. It is also evident that the increasing number of IoT middleware solutions are developed in both research...
One of the main challenges in the development of traffic systems is to assure safety for all road users. Hence, especially expensive vehicles are equipped with advanced driver assistance systems (ADAS) that use data about the vehicle and information about objects in the proximity of the vehicle to execute the assistance function. These objects have to be detected by sensors and they have to be tracked...
Context-aware systems are concerned with identifying the context of a user and then to either provide that information based on queries or to automatically decide on appropriate actions to be taken. Some context aspects (such as location) are easy to sense through hardware, while the activity of a user has shown to be somewhat elusive to being sensed with hardware sensors. As users use web services...
One of the banes of modern software development is needing to make design decisions before enough information is available to do so with adequate justification. In this paper, we describe a novel system engineering technique that helps alleviate the problem by allowing many such decisions to be delayed until they can be made with sufficient supporting information. We expect this approach will substantially...
This paper presents a light inference system for context management, ready to perform reasoning tasks in resource-constrained devices. The inference system is part of a service-oriented mobile software framework which runs on Javaenabled handheld devices. This framework serves to facilitate the creation of context-aware applications, as it decouples sensor's data acquisition and context processing...
Mobility and distribution are the key characteristics of pervasive computing environment. It is an inevitable problem for mobile applications how to find available context in a distributed context-aware system. This paper proposes a context-aware mechanism to enable mobile applications to be bound up with different agents adapting to the changing location of mobile applications. The mechanism relies...
Interest in Context Awareness is gaining ground in both Academic and Industrial communities. Most context information is provided by sensor networks. However, there is always a delay between the collection of the data and the usage of the information. In this paper, we developed a generic decay model for sensor information. The model contains an information-specific function and several parameters...
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