14 research outputs found

    SAT based Enforcement of Domotic Effects in Smart Environments

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    The emergence of economically viable and efficient sensor technology provided impetus to the development of smart devices (or appliances). Modern smart environments are equipped with a multitude of smart devices and sensors, aimed at delivering intelligent services to the users of smart environments. The presence of these diverse smart devices has raised a major problem of managing environments. A rising solution to the problem is the modeling of user goals and intentions, and then interacting with the environments using user defined goals. `Domotic Effects' is a user goal modeling framework, which provides Ambient Intelligence (AmI) designers and integrators with an abstract layer that enables the definition of generic goals in a smart environment, in a declarative way, which can be used to design and develop intelligent applications. The high-level nature of domotic effects also allows the residents to program their personal space as they see fit: they can define different achievement criteria for a particular generic goal, e.g., by defining a combination of devices having some particular states, by using domain-specific custom operators. This paper describes an approach for the automatic enforcement of domotic effects in case of the Boolean application domain, suitable for intelligent monitoring and control in domotic environments. Effect enforcement is the ability to determine device configurations that can achieve a set of generic goals (domotic effects). The paper also presents an architecture to implement the enforcement of Boolean domotic effects, and results obtained from carried out experiments prove the feasibility of the proposed approach and highlight the responsiveness of the implemented effect enforcement architectur

    Holografsko kodiranje akcija i interakcija procesa

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    Digital holographic transformations. Holographic surface. Objects, actions and events on the holographic surface. Coding of the actions. Process state follow-up: short- and long-term memory. HOLA – holographic analytical machine. Data flow in the holographic machine. Process state interactions.Digitalne holografske pretvorbe. Holografska površina. Objekti, akcije i događaji na holografskoj površini. Kodiranje akcija. Slijeđenje procesnog stanja: kratkotrajna i dugotrajna memorija. HOLA – holografski analitički stroj. Tok podataka u holografskom stroju. Međudjelovanja procesnih stanja

    Ambient Intelligence in Healthcare: A State-of-the-Art

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    Information technology advancement leads to an innovative paradigm called Ambient Intelligence (AmI). A digital environment is employed along with AmI to enable individuals to be aware to their behaviors, needs, emotions and gestures. Several applications of the AmI systems in healthcare environment attract several researchers. AmI is considered one of the recent technologies that support hospitals, patients, and specialists for personal healthcare with the aid of artificial intelligence techniques and wireless sensor networks. The improvement in the wearable devices, mobile devices, embedded software and wireless technologies open the doors to advanced applications in the AmI paradigm. The WSN and the BAN collect medical data to be used for the progress of the intelligent systems adapted inevitably. The current study outlines the AmI role in healthcare concerning with its relational and technological nature. Health

    Deliberative Context-Aware Ambient Intelligence System for Assisted Living Homes

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    Monitoring wellbeing and stress is one of the problems covered by ambient intelligence, as stress is a significant cause of human illnesses directly affecting our emotional state. The primary aim was to propose a deliberation architecture for an ambient intelligence healthcare application. The architecture provides a plan for comforting stressed seniors suffering from negative emotions in an assisted living home and executes the plan considering the environment's dynamic nature. Literature was reviewed to identify the convergence between deliberation and ambient intelligence and the latter's latest healthcare trends. A deliberation function was designed to achieve context-aware dynamic human-robot interaction, perception, planning capabilities, reactivity, and context-awareness with regard to the environment. A number of experimental case studies in a simulated assisted living home scenario were conducted to demonstrate the approach's behavior and validity. The proposed methods were validated to show classification accuracy. The validation showed that the deliberation function has effectively achieved its deliberative objectives

    Deliberative Context-Aware Ambient Intelligence System for Assisted Living Homes

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    [EN] Monitoring wellbeing and stress is one of the problems covered by ambient intelligence, as stress is a significant cause of human illnesses directly affecting our emotional state. The primary aim was to propose a deliberation architecture for an ambient intelligence healthcare application. The architecture provides a plan for comforting stressed seniors suffering from negative emotions in an assisted living home and executes the plan considering the environment¿s dynamic nature. Literature was reviewed to identify the convergence between deliberation and ambient intelligence and the latter¿s latest healthcare trends. A deliberation function was designed to achieve context-aware dynamic human-robot interaction, perception, planning capabilities, reactivity, and context-awareness with regard to the environment. A number of experimental case studies in a simulated assisted living home scenario were conducted to demonstrate the approach¿s behavior and validity. The proposed methods were validated to show classification accuracy. The validation showed that the deliberation function has effectively achieved its deliberative objectives.This work is supported by the Spanish MINECO Project (No. TIN2017-88476-C2-1-R) and the Universitat Politecnica de Valencia Research (Grant No. PAID-10-19).Babli, M.; Rincón-Arango, JA.; Onaindia De La Rivaherrera, E.; Carrascosa Casamayor, C.; Julian, V. (2021). Deliberative Context-Aware Ambient Intelligence System for Assisted Living Homes. Human-Centric Computing and Information Sciences. 11:1-18. https://doi.org/10.22967/HCIS.2021.11.0191181

    A Methodology for Trustworthy IoT in Healthcare-Related Environments

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    The transition to the so-called retirement years, comes with the freedom to pursue old passions and hobbies that were not possible to do in the past busy life. Unfortunately, that freedom does not come alone, as the previous young years are gone, and the body starts to feel the time that passed. The necessity to adapt elder way of living, grows as they become more prone to health problems. Often, the solution for the attention required by the elders is nursing homes, or similar, that take away their so cherished independence. IoT has the great potential to help elder citizens stay healthier at home, since it has the possibility to connect and create non-intrusive systems capable of interpreting data and act accordingly. With that capability, comes the responsibility to ensure that the collected data is reliable and trustworthy, as human wellbeing may rely on it. Addressing this uncertainty is the motivation for the presented work. The proposed methodology to reduce this uncertainty and increase confidence relies on a data fusion and a redundancy approach, using a sensor set. Since the scope of wellbeing environment is wide, this thesis focuses its proof of concept on the detection of falls inside home environments, through an android app using an accelerometer sensor and a micro- phone. The experimental results demonstrates that the implemented system has more than 80% of reliable performance and can provide trustworthy results. Currently the app is being tested also in the frame of the European Union projects Smart4Health and Smart Bear.A transição para os chamados anos de reforma, vem com a liberdade de perseguir velhas pai- xões e passatempos que na passada vida ocupada não eram possíveis de realizar. Infelizmente, essa liberdade não vem sozinha, uma vez que os anos jovens anteriores terminaram, e o corpo começa a sentir o tempo que passou. A necessidade de adaptar o modo de vida dos menos jovens, cresce à medida que estes se tornam mais propensos a problemas de saúde. Muitas vezes, a solução para a atenção que os mais idosos necessitam são os lares de idosos, ou similares, que lhes tiram a tão querida independência. IoT tem o grande potencial de ajudar os cidadãos idosos a permanecerem mais saudá- veis em casa, uma vez que tem a possibilidade de se ligar e criar sistemas não intrusivos capa- zes de interpretar dados e agir em conformidade. Com essa capacidade, vem a responsabili- dade de assegurar que os dados recolhidos são fiáveis e de confiança, uma vez que o bem- estar humano possa depender dos mesmos. Abordar esta incerteza é a motivação para o tra- balho apresentado. A metodologia proposta para reduzir esta incerteza e aumentar a confiança no sistema baseia-se numa fusão de dados e numa abordagem de redundância, utilizando um conjunto de sensores. Uma vez que o assunto de bem-estar e saúde é vasto, esta tese concentra a sua prova de conceito na deteção de quedas dentro de ambientes domésticos, através de uma aplicação android, utilizando um sensor de acelerómetro e um microfone. Os resultados expe- rimentais demonstram que o sistema implementado tem um desempenho superior a 80% e pode fornecer dados fiáveis. Atualmente a aplicação está a ser testada também no âmbito dos projetos da União Europeia Smart4Health e Smart Bear

    HTN planning: Overview, comparison, and beyond

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    Hierarchies are one of the most common structures used to understand and conceptualise the world. Within the field of Artificial Intelligence (AI) planning, which deals with the automation of world-relevant problems, Hierarchical Task Network (HTN) planning is the branch that represents and handles hierarchies. In particular, the requirement for rich domain knowledge to characterise the world enables HTN planning to be very useful, and also to perform well. However, the history of almost 40 years obfuscates the current understanding of HTN planning in terms of accomplishments, planning models, similarities and differences among hierarchical planners, and its current and objective image. On top of these issues, the ability of hierarchical planning to truly cope with the requirements of real-world applications has been often questioned. As a remedy, we propose a framework-based approach where we first provide a basis for defining different formal models of hierarchical planning, and define two models that comprise a large portion of HTN planners. Second, we provide a set of concepts that helps in interpreting HTN planners from the aspect of their search space. Then, we analyse and compare the planners based on a variety of properties organised in five segments, namely domain authoring, expressiveness, competence, computation and applicability. Furthermore, we select Web service composition as a real-world and current application, and classify and compare the approaches that employ HTN planning to solve the problem of service composition. Finally, we conclude with our findings and present directions for future work. In summary, we provide a novel and comprehensive viewpoint on a core AI planning technique.<br/

    Distributed coordination in unstructured intelligent agent societies

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    Current research on multi-agent coordination and distributed problem solving is still not robust or scalable enough to build large real-world collaborative agent societies because it relies on either centralised components with full knowledge of the domain or pre-defined social structures. Our approach allows overcoming these limitations by using a generic coordination framework for distributed problem solving on totally unstructured environments that enables each agent to decompose problems into sub-problems, identify those which it can solve and search for other agents to delegate the sub-problems for which it does not have the necessary knowledge or resources. Regarding the problem decomposition process, we have developed two distributed versions of the Graphplan planning algorithm. To allow an agent to discover other agents with the necessary skills for dealing with unsolved sub-problems, we have created two peer-to-peer search algorithms that build and maintain a semantic overlay network that connects agents relying on dependency relationships, which improves future searches. Our approach was evaluated using two different scenarios, which allowed us to conclude that it is efficient, scalable and robust, allowing the coordinated distributed solving of complex problems in unstructured environments without the unacceptable assumptions of alternative approaches developed thus far.As abordagens actuais de coordenação multi-agente e resolução distribuída de problemas não são suficientemente robustas ou escaláveis para criar sociedades de agentes colaborativos uma vez que assentam ou em componentes centralizados com total conhecimento do domínio ou em estruturas sociais pré-definidas. A nossa abordagem permite superar estas limitações através da utilização de um algoritmo genérico de coordenação de resolução distribuída de problemas em ambientes totalmente não estruturados, o qual permite a cada agente decompor problemas em sub-problemas, identificar aqueles que consegue resolver e procurar outros agentes a quem delegar os subproblemas para os quais não tem conhecimento suficiente. Para a decomposição de problemas, criámos duas versões distribuídas do algoritmo de planeamento Graphplan. Para procurar os agentes com as capacidades necessárias à resolução das partes não resolvidas do problema, criámos dois algoritmos de procura que constroem e mantêm uma camada de rede semântica que relaciona agentes dependentes com o fim de facilitar as procuras. A nossa abordagem foi avaliada em dois cenários diferentes, o que nos permitiu concluir que ´e uma abordagem eficiente, escalável e robusta, possibilitando a resolução distribuída e coordenada de problemas complexos em ambientes não estruturados sem os pressupostos inaceitáveis em que assentava o trabalho feito até agora
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