Kimberly Garcia

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Garcia
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Kimberly
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kimberly.garcia@unisg.ch

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    Item type:Publication,
    A Digital Companion Architecture for Ambient Intelligence
    (Association for Computing Machinery (ACM), 2024-05-13)
    Garcia, Kimberly  
    ;
    Vontobel, Jonathan
    ;
    Mayer, Simon  
    Ambient Intelligence (AmI) focuses on creating environments capable of proactively and transparently adapting to users and their activities. Traditionally, AmI focused on the availability of computational devices, the pervasiveness of networked environments, and means to interact with users. In this paper, we propose a renewed AmI architecture that takes into account current technological advancements while focusing on proactive adaptation for assisting and protecting users. This architecture consist of four phases: Perceive, Interpret, Decide, and Interact. The AmI systems we propose, called Digital Companions (DC), can be embodied in a variety of ways (e.g., through physical robots or virtual agents) and are structured according to these phases to assist and protect their users. We further categorize DCs into Expert DCs and Personal DCs, and show that this induces a favorable separation of concerns in AmI systems, where user concerns (including personal user data and preferences) are handled by Personal DCs and environment concerns (including interfacing with environmental artifacts) are assigned to Expert DCs; this separation has favorable privacy implications as well. Herein, we introduce this architecture and validate it through a prototype in an industrial scenario where robots and humans collaborate to perform a task.
    Type:journal article
    Journal:Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
    Volume:8
    Issue:2
    DOI:10.1145/3659610
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/121378
    Scopus© Citations 5
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    Item type:Publication,
    MR Object Identification and Interaction: Fusing Object Situation Information from Heterogeneous Sources
    (ACM, 2023-09-28)
    Jannis Rene Strecker  
    ;
    Khakim Akhunov
    ;
    Federico Carbone
    ;
    Kimberly Garcia  
    ;
    Kenan Bektas  
    The increasing number of objects in ubiquitous computing environments creates a need for effective object detection and identification mechanisms that permit users to intuitively initiate interactions with these objects. While multiple approaches to such object detection-including through visual object detection, fiducial markers, relative localization, or absolute spatial referencing-are available, each of these suffers from drawbacks that limit their applicability. In this paper, we propose ODIF, an architecture that permits the fusion of object situation information from such heterogeneous sources and that remains vertically and horizontally modular to allow extending and upgrading systems that are constructed accordingly. We furthermore present BLEARVIS, a prototype system that builds on the proposed architecture and integrates computer-vision (CV) based object detection with radio-frequency (RF) angle of arrival (AoA) estimation to identify BLE-tagged objects. In our system, the front camera of a Mixed Reality (MR) head-mounted display (HMD) provides a live image stream to a vision-based object detection module, while an antenna array that is mounted on the HMD collects AoA information from ambient devices. In this way, BLEARVIS is able to differentiate between visually identical objects in the same environment and can provide an MR overlay of information (data and controls) that relates to them. We include experimental evaluations of both, the CV-based object detection and the RF-based AoA estimation, and discuss the applicability of the combined RF and CV pipelines in different ubiquitous computing scenarios. This research can form a starting point to spawn the integration of diverse object detection, identification, and interaction approaches that function across the electromagnetic spectrum, and beyond.
    Type:journal article
    Journal:Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)
    Volume:7
    Issue:3
    URL:https://dl.acm.org/doi/10.1145/3610879
    DOI:10.1145/3610879
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/117879
    Scopus© Citations 14