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  • 1.
    Awada, Imad Alex
    et al.
    University Politehnica of Bucharest, Romania.
    Cramariuc, Oana
    IT Cenetr for Science and Technology, Romania.
    Mocanu, Irina
    University Politehnica of Bucharest.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kunnappilly, Ashalatha
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Florea, Adina Magda
    University Politehnica of Bucharest, Romania.
    An end- user perspective on the CAMI Ambient and Assisted Living Project2018In: INTED2018 Proceedings, 2018Conference paper (Refereed)
    Abstract [en]

    In this paper, we present the outcomes and conclusions obtained by involving seniors from three countries (Denmark, Poland and Romania) in an innovative project funded under the European Ambient Assisted Living (ALL) program. CAMI stands for "Companion with Autonomously Mobile Interface" in "Artificially intelligent ecosystem for self-management and sustainable quality of life in AAL". The CAMI solution enables flexible, scalable and individualised services that support elderly to self-manage their daily life and prolong their involvement in the society (sharing knowledge, continue working, etc). This also allows their informal caregivers (family and friends) to continue working and participating in society while caring for their loved ones. The solution is designed as an innovative architecture that allows for individualized, intelligent self-management which can be tailored to an individual's preferences and needs. A user-centred approach has ranked health monitoring, computer supervised physical exercises and voice based interaction among the top favoured CAMI functionalities. Respondents from three countries (Poland, Romania and Denmark) participated in a multinational survey and a conjoint analysis study.

  • 2.
    Danielsson, Jakob
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tsog, Nandinbaatar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kunnappilly, Ashalatha
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A systematic mapping study on real-Time cloud services2019In: Proceedings - 11th IEEE/ACM International Conference on Utility and Cloud Computing Companion, UCC Companion 2018, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 245-251, article id 8605787Conference paper (Refereed)
    Abstract [en]

    Cloud computing is relatively a new technique to host and use the services and applications from the internet. Although it offers a multitude of advantages like scalability, low operating cost, accessibility and maintainability, etc., they are often not utilized to the fullest due to the lack of timeliness property associated with the cloud. Cloud services are mainly designed to maximize throughput and utilization of resources and hence incorporating predictable execution time properties in to the cloud is arduous. Nevertheless, cloud still remains a highly attractive platform for hosting real-Time applications and services owing to features like elasticity, multi-Tenancy, ability to survive hardware failures, virtualization support and abstraction layer support which provides flexibility and portability. In order for real-Time safety-critical applications to exploit the potential of cloud computing, it is essential to ensure the predictable real-Time behavior of cloud services. In this paper, we perform a systematic mapping study on real-Time cloud services to identify the current research directions and potential research gaps. Our study focuses on analyzing the current architectures and software techniques that are available at present to incorporate real-Time property of the cloud services. We also aim at investigating the current challenges involved in realizing a predictable real-Time behavior of cloud services. 

  • 3.
    Kunnappilly, Ashalatha
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A formally assured intelligent ecosystem for enhanced ambient assisted living support2018In: Proceedings of the ACM Symposium on Applied Computing, 2018, p. 1581-1582Conference paper (Refereed)
    Abstract [en]

    The increasing proportion of elderly adults across the world calls for Ambient Assisted Living (AAL) solutions that can support the elderly in their daily activities, ensure timely resolution of critical scenarios, and help them live independently and without social isolation. However, most of the existing AAL solutions deliver only certain functionalities, that, if used side by side, cannot resolve potentially critical scenarios in a timely manner. A safe mitigation of such situations is possible if all relevant AAL functions are seamlessly integrated, and supported by artificially intelligent decision-making solutions. Moreover, given the safety-critical nature of such systems, evidence of their correctness and quality of service needs to also be provided via formal analysis techniques. This paper addresses such issues by presenting the ongoing Ph.D. research work of the author, aiming at developing a formally assured ecosystem for AAL systems. 

  • 4.
    Kunnappilly, Ashalatha
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Formally Assured Intelligent Systems for Enhanced Ambient Assisted Living Support2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Ambient Assisted Living (AAL) solutions are aimed to assist the elderly in their independent and safe living. During the last decade, the AAL field has witnessed a significant development due to advancements in Information and Communication Technologies, Ubiquitous Computing and Internet of Things. However, a closer look at the existing AAL solutions shows that these improvements are used mostly to deliver one or a few functions mainly of the same type (e.g. health monitoring functions). There are comparatively fewer initiatives that integrate different kinds of AAL functionalities, such as fall detection, reminders, fire alarms, etc., besides health monitoring, into a common framework, with intelligent decision-making that can thereby offer enhanced reasoning by combining multiple events. 

     

    To address this shortage, in this thesis, we propose two different categories of AAL architecture frameworks onto which different functionalities, chosen based on user preferences, can be integrated. One of them follows a centralized approach, using an intelligent Decision Support System (DSS), and the other, follows a truly distributed approach, involving multiple intelligent agents. The centralized architecture is our initial choice, due to its ease of development by combining multiple functionalities with a centralized DSS that can assess the dependency between multiple events in real time. While easy to develop, our centralized solution suffers from the well-known single point of failure, which we remove by adding a redundant DSS. Nevertheless, the scalability, flexibility, multiple user accesses, and potential self-healing capability of the centralized solution are hard to achieve, therefore we also propose a distributed, agent-based architecture as a second solution, to provide the community with two different AAL solutions that can be applied depending on needs and available resources. Both solutions are to be used in safety-critical applications, therefore their design-time assurance, that is, providing a guarantee that they meet functional requirements and deliver the needed quality-of-service, is beneficial. 

     

    Our first solution is a generic architecture that follows the design of many commercial AAL solutions with sensors, a data collector, DSS, security and privacy, database (DB) systems, user interfaces (UI), and cloud computing support. We represent this architecture in the Architecture Analysis and Design Language (AADL) via a set of component patterns that we propose. The advantage of using patterns is that they are easily re-usable when building specific AAL architectures. Our patterns describe the behavior of the components in the Behavioral Annex of AADL, and the error behavior in AADL's Error Annex. We also show various instantiations of our generic model that can be developed based on user requirements. To formally assure these solutions against functional, timing and reliability requirements, we show how we can employ exhaustive model checking using the state-of-art model checker, UPPAAL, and also statistical model-checking techniques with UPPAAL SMC, an extension of the UPPAAL model checker for stochastic systems, which can be employed in cases when exhaustive verification does not scale. The second proposed architecture is an agent-based architecture for AAL systems, where agents are intelligent entities capable of communicating with each other in order to decide on an action to take. Therefore, the decision support is now distributed among agents and can be used by multiple users distributed across multiple locations. Due to the fact that this solution requires describing agents and their interaction, the existing core AADL does not suffice as an architectural framework. Hence, we propose an extension to the core AADL language - The Agent Annex, with formal semantics as Stochastic Transition Systems, which allows us to specify probabilistic, non-deterministic and real-time AAL system behaviors. In order to formally assure our multi-agent system, we employ the state-of-art probabilistic model checker PRISM, which allows us to perform probabilistic yet exhaustive verification.

     

    As a final contribution, we also present a small-scale validation of an architecture of the first category, with end users from three countries (Romania, Poland, Denmark). This work has been carried out with partners from the mentioned countries. 

     

    Our work in this thesis paves the way towards the development of user-centered, intelligent ambient assisted living solutions with ensured quality of service.

  • 5.
    Kunnappilly, Ashalatha
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Legay, Axel
    INRIA, Rennes, France.
    Margaria, Tiziana
    Univ. Limerick and Lero, Limerick, Ireland.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Steffen, Bernhard
    TU Dortmund, Germany.
    Tranonouez, Louis-Marie
    INRIA, Rennes, France.
    Analyzing Ambient Assisted Living Solutions: A Research Perspective2017In: 12th International Conference on Design and Technology of Integrated Systems in Nanoscale Era DTIS 2017, 2017Conference paper (Refereed)
    Abstract [en]

    Typical AAL solutions rely on integrating capabilities for health monitoring, fall detection, communication and social inclusion, supervised physical exercises, vocal interfaces, robotic platforms etc. Ensuring the safe function and quality of service with respect to various extra-functional requirements like timing and security of such AAL solutions is of highest importance. To facilitate analysis, latest system development platforms provide underlying infrastructures for model-driven design (e.g., via the dime{} tool), timing and resource-usage specification (e.g., via the REMES tool), security features (e.g., by employing SECube), and statistical model-checking techniques (e.g, via Plasma). In this paper, we discuss the challenges associated with analyzing complex AAL solutions, from relevant properties to semantic interoperability issues raised by employing various frameworks for modeling and analysis, and applicability to evolving architectures. We take as examples two of the prominent existing AAL architectures and our own prior experience.

  • 6.
    Kunnappilly, Ashalatha
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Marinescu, Raluca
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Model-Checking-Based Framework For Analyzing Ambient Assisted Living Solutions2019Report (Refereed)
  • 7.
    Kunnappilly, Ashalatha
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Marinescu, Raluca
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Assuring intelligent ambient assisted living solutions by statistical model checking2018In: Lect. Notes Comput. Sci., Springer Verlag , 2018, p. 457-476Conference paper (Refereed)
    Abstract [en]

    A modern way of enhancing elderly people’s quality of life is by employing various Ambient Assisted Living solutions that facilitate an independent and safe living for their users. This is achieved by integrating computerized functions such as health and home monitoring, fall detection, reminders, etc. Such systems are safety critical, therefore ensuring at design time that they operate correctly, but also in a timely and robust manner is important. Most of the solutions are not analyzed formally at design time, especially if such Ambient Assisted Living functions are integrated within the same design. To address this concern, we propose a framework that relies on an abstract component-based description of the system’s architecture in the Architecture Analysis and Design Language. To ensure scalability of analysis, we transform the AADL models into a network of stochastic timed automata amenable to statistical analysis of various quality-of-service attributes. The architecture that we analyze is developed as part of the project CAMI, co-financed by the European Commission, and consists of a variety of health and home sensors, a data collector, local and cloud processing, as well as an artificial-intelligence-based decision support system. Our contribution paves the way towards achieving design-time assured integrated Ambient Assisted Living solutions, which in turn could reduce verification effort at later stages.

  • 8.
    Kunnappilly, Ashalatha
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Seceleanu, Cristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Do We Need an Integrated Framework for Ambient Assisted Living?2016In: UBIQUITOUS COMPUTING AND AMBIENT INTELLIGENCE, UCAMI 2016, PT II, 2016, p. 52-63Conference paper (Refereed)
    Abstract [en]

    The significant increase of ageing population calls for solutions that help the elderly to live an independent, healthy and low risk life, but also ensure their social interaction. The improvements in Information and Communication Technologies (ICT) and Ambient Assisted Living (AAL) have resulted in the development of equipment that supports ubiquitous computing, ubiquitous communication and intelligent user interfaces. The smart home technologies, assisted robotics, sensors for health monitoring and e-health solutions are some examples in this category. Despite such growth in these individualized technologies, there are only few solutions that provide integrated AAL frameworks that interconnect all of these technologies. In this paper, we discuss the necessity to opt for an integrated solution in AAL. To support the study we describe real life scenarios that help us justify the need for integrated solutions over individualized ones. Our analysis points to the clear conclusion that an integrated solution for AAL outperforms the individualized ones.

  • 9.
    Kunnappilly, Ashalatha
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Sorici, Alexandru
    University Politehnica of Bucharest, Romania.
    Awada, Imad Alex
    University Politehnica of Bucharest, Romania.
    Mocanu, Irina
    University Politehnica of Bucharest, Romania.
    Seceleanu, Cristina
    Florea, Adina Magda
    University Politehnica of Bucharest, Romania.
    A Novel Integrated Architecture for Ambient Assisted Living Systems2017In: The 41st IEEE Computer Society International Conference on Computers, Software & Applications COMPSAC 2017, 2017, Vol. 1, p. 465-472, article id 8029645Conference paper (Refereed)
    Abstract [en]

    The increase in life expectancy and the slumping birth rates across the world result in lengthening the average age of the society. This change in demography has many consequences, the major being the insufficient number of caregivers. Therefore, we are in need of techniques that will assist the elderly in their daily life, while preventing their social isolation. The recent developments in Ambient Intelligence (AmI) and Information and Communication Technologies (ICT) have facilitated a technological revolution in the field of Ambient Assisted Living (AAL). At present, there are many technologies on the market that support the independent life of older adults, requiring less assistance from family and caregivers, yet most of them offer isolated services, such as health monitoring, supervised exercises, reminders etc. There are only very few architectures that support the seamless integration of various functionalities and none of them incorporates user preferences or are formally analyzed for their functionality and quality-of-service attributes which is needed in order to ensure safe mitigations of potential critical scenarios. In this paper, we propose a novel architectural solution that seamlessly integrates necessary functions of an AAL system, based on user preferences. To enable a first level of the architecture's analysis, we model our system in Architecture Analysis and Design Language (AADL), and carry out its simulation for analyzing the end-to-end data-flow latency, resource budgets and system safety.

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