Improving modularity, interoperability and extensibility in Ambient Intelligence

Ambient Intelligence (AmI) and its related elds emerged some years ago with the exciting promise of pervasive intelligence, magic interaction mechanisms, and everywhere availability. This promise would be materialized in homes that knew all about our habits and preferences, proactive workplaces to support people's work or personal digital assistants to improve our daily living in all aspects possible. This somewhat utopian vision, expected by many to have already taken place, remains unaccomplished and far from it. Many challenges still lay ahead which delayed and continue to delay the expected technological unravelling. In this paper we focus on the immense technological challenges of designing and implementing AmI Systems. Speci cally, we propose a technological approach that will contribute to overcome some of these challenges by making developed AmI solutions more modular, interoperable, and extensible. This will result especially advantageous for large development teams or teams that span multiple institutions.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012)

The MASSIF platform : a modular and semantic platform for the development of flexible IoT services

In the Internet of Things (IoT), data-producing entities sense their environment and transmit these observations to a data processing platform for further analysis. Applications can have a notion of context awareness by combining this sensed data, or by processing the combined data. The processes of combining data can consist both of merging the dynamic sensed data, as well as fusing the sensed data with background and historical data. Semantics can aid in this task, as they have proven their use in data integration, knowledge exchange and reasoning. Semantic services performing reasoning on the integrated sensed data, combined with background knowledge, such as profile data, allow extracting useful information and support intelligent decision making. However, advanced reasoning on the combination of this sensed data and background knowledge is still hard to achieve. Furthermore, the collaboration between semantic services allows to reach complex decisions. The dynamic composition of such collaborative workflows that can adapt to the current context, has not received much attention yet. In this paper, we present MASSIF, a data-driven platform for the semantic annotation of and reasoning on IoT data. It allows the integration of multiple modular reasoning services that can collaborate in a flexible manner to facilitate complex decision-making processes. Data-driven workflows are enabled by letting services specify the data they would like to consume. After thorough processing, these services can decide to share their decisions with other consumers. By defining the data these services would like to consume, they can operate on a subset of data, improving reasoning efficiency. Furthermore, each of these services can integrate the consumed data with background knowledge in its own context model, for rapid intelligent decision making. To show the strengths of the platform, two use cases are detailed and thoroughly evaluated

The M3 architecture for smart spaces: Overview of semantic information broker implementations

A smart space enhances a networked computing environment by enabling information sharing for a multitude of local digital devices and global resources from the Internet. We consider the M3 architecture (multi-device, multi-vendor, multi-domain) for creating smart spaces, which integrates technologies from two innovative concepts: the Semantic Web and the Internet of Things. Our research focus is on analyses of the capabilities of Smart-M3 platform, which provides software implementations for such a central element of an M3 smart space as Semantic Information Broker (SIB). The paper presents a state-of-the-art and contributes our systematized vision on the SIB design and implementation. The analyzed open source SIB implementations include the original Smart-M3 piglet-based SIB, its optimized descendant RedSIB, OSGi SIB for Java devices, pySIB for Python devices, and CuteSIB for Qt devices. We also analyze the design of proprietary or incomplete SIB implementations: RIBS for embedded devices and ADK SIB built upon the OSGi framework with integration in the Eclipse Integrated Development Environment. The theoretical study is augmented with experimental evaluation of available SIB implementations

Inter-organization cooperation for ambient assisted living

In the last years we have witnessed to a substantial increase on the number of people in need of care services, espe-cially among the elderly, a phenomenon related to population ageing. However, this is becoming not exclusive of the elderly, as diseases like obesity, diabetes, and blood pressure have been increasing amongst young adults. This is a new reality which needs to be dealt by the healthcare sector, specifically the public one. Given these new scenarios, the importance of finding new and cost-effective ways for health care delivery are of particular relevance, especially when it is believed that these new patients should not be removed from their natural, day-to-day life, environment. The evolution of the, so called, new technolo-gies may pay here a very important role as they may become part of the solution for this new problematic. Actually, they are already been used as, in recent years, several projects have raised in this relatively new area of work. These projects, although legitimate ones, were essential for delineating a path to pursue for others to come, as they were in some case, very simple ones (e.g. panic buttons), and, especially, reactive ones. In this paper, we are going to present how we are trying to evolve these projects a step further, through the introduction of proactiveness as a key factor, taking advantage of “new”, as in applied to this areas, techniques of decision making, idea generation, argumentation and data quality, applied, not only to the in transit information, but also to the one provided by the several intervenient as well as themselves. In order to be able to pursue this delineated path, a new approach for knowledge representation, reasoning, and even for problem solving is proposed. To achieve these goals, the VirtualECare environment is presented, together with its sustaining infrastructure and architecture. Particular attention will be paidto how it may be used to simulate a virtual Assisted Living Environment in order to, later, bet-ter monitor real ones, attending to its customers’ needs

A survey and classification of software-defined storage systems

The exponential growth of digital information is imposing increasing scale and efficiency demands on modern storage infrastructures. As infrastructure complexity increases, so does the difficulty in ensuring quality of service, maintainability, and resource fairness, raising unprecedented performance, scalability, and programmability challenges. Software-Defined Storage (SDS) addresses these challenges by cleanly disentangling control and data flows, easing management, and improving control functionality of conventional storage systems. Despite its momentum in the research community, many aspects of the paradigm are still unclear, undefined, and unexplored, leading to misunderstandings that hamper the research and development of novel SDS technologies. In this article, we present an in-depth study of SDS systems, providing a thorough description and categorization of each plane of functionality. Further, we propose a taxonomy and classification of existing SDS solutions according to different criteria. Finally, we provide key insights about the paradigm and discuss potential future research directions for the field.This work was financed by the Portuguese funding agency FCT-Fundacao para a Ciencia e a Tecnologia through national funds, the PhD grant SFRH/BD/146059/2019, the project ThreatAdapt (FCT-FNR/0002/2018), the LASIGE Research Unit (UIDB/00408/2020), and cofunded by the FEDER, where applicable

QuiiQ automation foundation

Tese de mestrado. Engenharia Informática. Faculdade de Engenharia. Universidade do Porto. 200

A smart home environment to support safety and risk monitoring for the elderly living independently

The elderly prefer to live independently despite vulnerability to age-related challenges. Constant monitoring is required in cases where the elderly are living alone. The home environment can be a dangerous environment for the elderly living independently due to adverse events that can occur at any time. The potential risks for the elderly living independently can be categorised as injury in the home, home environmental risks and inactivity due to unconsciousness. The main research objective was to develop a Smart Home Environment (SHE) that can support risk and safety monitoring for the elderly living independently. An unobtrusive and low cost SHE solution that uses a Raspberry Pi 3 model B, a Microsoft Kinect Sensor and an Aeotec 4-in-1 Multisensor was implemented. The Aeotec Multisensor was used to measure temperature, motion, lighting, and humidity in the home. Data from the multisensor was collected using OpenHAB as the Smart Home Operating System. The information was processed using the Raspberry Pi 3 and push notifications were sent when risk situations were detected. An experimental evaluation was conducted to determine the accuracy with which the prototype SHE detected abnormal events. Evaluation scripts were each evaluated five times. The results show that the prototype has an average accuracy, sensitivity and specificity of 94%, 96.92% and 88.93% respectively. The sensitivity shows that the chance of the prototype missing a risk situation is 3.08%, and the specificity shows that the chance of incorrectly classifying a non-risk situation is 11.07%. The prototype does not require any interaction on the part of the elderly. Relatives and caregivers can remotely monitor the elderly person living independently via the mobile application or a web portal. The total cost of the equipment used was below R3000