Smart glasses enhance interactions with the environment by using head-mounted cameras to observe the user’s viewpoint, but lack the visual feedback used for common interactions. We introduce “Gazeify then Voiceify”, a multimodal approach allowing object selection via gaze and voice using displayless smart glasses. Users can select a physical object with their gaze, and the system generates a digital mask and a voice description of the object’s semantics. Users can further correct errors through free-form conversation. To demonstrate our approach, we develop an interactive system by integrating advanced object segmentation and detection with a visual-language model. User studies reveal that participants achieve correct gaze selection in 53% of the task trials and use voice disambiguation to correct 58% remaining errors. Participants also rated the system as likable, useful and easy to use.

Wi-Fi device-free tracking enables the inference of user behaviors without physical contact, which is crucial for intelligent indoor location-based services. Nevertheless, the practical implementation of current tracking systems is constrained by several critical limitations: 1) The low-quality sensing signals in complex scenarios lead to increased tracking errors; 2) Existing methods inadequately adjust to dynamic environments, necessitating additional data collection or retraining processes. To address these challenges, this paper introduces EOC-Tracking, a device-free Wi-Fi tracking system that dynamically incorporates environmental information. Our key innovation involves leveraging obstacles to correct illogical users' trajectories and facilitate adjustment to varying environments. This significantly improves the accuracy of the follow-up in complex and changing environments. The EOC-Tracking system is built upon three fundamental design principles: 1) A lightweight dual-branch neural network architecture that effectively fuses environmental data with Wi-Fi signal characteristics; 2) An autonomous map updating mechanism that facilitates real-time adaptation to environmental layout modifications without human intervention; 3) A sophisticated data-driven, phased training paradigm that optimizes the model's ability to learn and apply obstacle constraints. We implement EOC-Tracking using commercial Wi-Fi devices and deploy it on low-power embedded systems such as the MCU. Experimental results demonstrate that EOC-Tracking can reduce tracking errors by at most 49.48% compared to datadriven methods and 62.21% compared to model-based methods in various complex scenarios.

Whilst the vision of a robust service-oriented architecture (SOA) is very seductive it engenders many technical challenges. The main challenge is the development and support of runtime cross-standard service activation and interoperation. Such interoperation will provide a vital stepping-stone towards the integration of the emerging SOA standards and legacy services - those developed using existing middleware architectures such as DCOM, CORBA, J2EE, Web service, JXTA, and Jini. Much related works already exist including WSIF framework, which provides APIs to support design-time invocation of cross-standard Web services deployed on multiple SOAP packages. However, this paper focuses on a runtime self-regenerative mechanism related to adaptive service invocation code. The paper will present a runtime service adaptation mechanism, which supports end-users to dynamically adapt to variations in the execution environment, without altering their original design, crossing multiple standards (both synchronous and asynchronous invocation models) and middleware architectures. This paper also introduces a proposed "Polyarchical Middleware" architecture to support such self-regenerative service adaptation. An illustrative example will be used to describe the approach and the current implementation. The paper will conclude with general remarks and mention of further work.

Next generation software applications will be required to run on globally distributed heterogeneous assemblies of disparate resources including: emerging computing grids. Such application calls for seamless integration and interoperation between varieties of service standards and architectures developed and deployed using current service middleware standards and architectures. Whilst such middleware adequately provides different APIs, programming models for distributed components and services integration and interoperation at both design and runtime. There is still need for additional middleware services including the support of runtime multistandard services invocation regardless of the components/service standards and type of middleware used. Based on an ongoing research focusing on self-adaptive software for adaptive middleware, we describe a proposed on-demand (runtime) service invocation mechanism, and the associated service interoperation mechanism.