The Design and Implementation of a Location-Aware Service Bundle Manager in Smart Space Environments

현재 여러 종류의 홈 네트워크(home network) 기술들이 존재하고 있으며, 단일화된 홈 컴퓨팅(home computing) 환경을 위해서는 서로 다른 네트워크 프로토콜간의 연동이 필수적이다. 이를 위하여 여러 종류의 홈 네트워크 미들웨어(home network middleware)가 개발되었고 특히 OSGi (Open Service Gateway Initiative)는 다양한 미들웨어 환경 사이의 서비스 상호연동을 제공하기 위해 제안되었다. 그러나 OSGi의 실행환경인 프레임워크(framework)는 수동적으로 서비스 번들(service bundle), 사용자 및 장치 관리 등을 수행하는 취약점을 가지고 있다. 본 논문에서는 사용자들의 편의성을 위해 수동적으로 관리되는 부분들의 문제점을 개선하고자 한다. 이를 위하여 자동화 서비스와 효율적인 서비스 번들의 관리를 위한 SBM (Service Bundle Manager)의 구조를 제안하고, SBM을 구현하여 SBM의 실효성을 검증하였다. Since different kinds of home network technologies coexist, seamless connections between different kinds of network protocols are essential for home computing environments. Several kinds of home network middleware have been developed and OSGi(Open Service Gateway Initiative) was initiated mainly for interoperability support with service distribution between various middleware environments. Framework, OSGi service platform, has weaknesses of passive service bundle management, user management and device management. Therefore, this paper resolves passive management parts which are critical weaknesses of OSGi Specification Version 3 and proposes SBM (Service Bundle Manager) to effiently manage various service bundles. Additionally, we verify practical effects of SBM through experiments.

Since different kinds of home network technologies coexist, seamless connections between different kinds of network protocols are essential for home computing environments. Several kinds of home network middleware have been developed and OSGi (Open Service Gateway Initiative) was initiated mainly for interoperability support with service distribution between various middleware environments. In this paper, we analyze the weaknesses in the OSGi service platform, such as a non-distributed framework, passive user management, device management, and service bundle management. Moreover, we propose SBM (Service Bundle Manager) to efficiently manage various service bundles. This paper concludes with the implementation results for SBM.

The open service gateway initiative (OSGi) framework is to provide an open environment for home services, which can be deployed by different service providers. However, currently there is no total solution for the OSGi framework to diagnose and recover from unexpected faults, especially those generated by resource conflicts between services, which would require user intervention. This paper summarizes the requirements for diagnosis in the open service platform and proposes an integrated approach to detect service conflict faults, handle general exceptions, and diagnose service errors on OSGi platforms. By providing user friendly diagnosis messages, and suggestions to fix exceptions, users can operate home gateways without a heavy learning burden, and service providers can reduce the overhead associated with user requests for technical support. The implementation is packaged as a service bundle running on the service layer of the OSGi platform. This is the first attempt to diagnose and handle the service conflicts on the OSGi platform during runtime.

This paper describes LocMAC, a new location aware power saving MAC layer for target tracking applications in smart space environments. Target tracking applications focus on providing proximity based local services to mobile users within a fixed deployment of wireless nodes. Conventional wireless sensor MAC layers increase the lifespans of battery powered wireless nodes by scheduling sleep periods for the entire network, which are either of fixed length, or vary based upon current network metrics. LocMAC bases its sleep schedule on the relative physical location of network nodes and allows target tracking service to be guaranteed. It propagates user location updates, and uses this knowledge to perform 'location based sleep scheduling' (LBSS). LBSS describes the use of wireless node and network target positions to maximise the potential sleep periods. Adding knowledge of user mobility allows those nodes which will not be required by the network application to sleep for longer periods of time, waking up just in time to service network user requirements. The paper describes the operation of LocMAC and compares its performance against existing sleep scheduling MAC protocols through analysis and simulations of typical application scenarios. The results show that LocMAC performs significantly better for target tracking applications and is particularly appropriate for use in future Smart Spaces.

This paper presents the first attempt to design an interoperability platform by integrating an RDF based information sharing infrastructure named Smart-M3 within the OSGi framework, enhancing the information level interoperability of the former with the service level interoperability of the latter. Such an interoperability platform provides a generic and simple solution to develop Smart Environment Applications.

A two phase hybrid algorithm for estimating the location of a mobile node, which has the capability of measuring signal strength, azimuth, and elevation, in a smart space environment over the visible light channel is proposed. In contrast to conventional triangulation approaches which are performed in a simplified plane, the smart room architecture requires a non-planar solution due to the illumination requirement. Furthermore, conventional triangulation approaches can at times produce numerically ill-defined solutions, thereby prohibiting a notion of target location. Instead of solely relying on triangulation, the mobile node estimate their locations through a two phase approach in which they firstly exploit the signal strength observables with unique IDs to establish a coarse estimate, and secondly use the azimuth and elevation observables to establish a fine estimate. In many cases, the fine estimate will improve upon the coarse estimate; however when triangulation fails, the algorithm yield the coarse estimate rather than a localization failure. Since the environment model relies on the primary requirement of adequate illumination, the number of LED anchors and transmit power for communication functions are determined. Simulation results confirm the effectiveness of the hybrid two phase localization approach in a smart space indoor environment by having a median coarse phase accuracy of 34.88 cm and a fine phase median accuracy of 13.95 cm.

Ubiquitous computing as the integration of sensors, middleware, and networking technologies to form a "smart space" environment relies on the development of both software and hardware solutions. For over 3 years, our group has been developing a smart-space environment, involving the exploration of core technologies and attractive applications. We introduce the challenges faced and lessons learned in designing and developing a smart-space environment, including device control services, locating systems, wireless sensor nodes, and middleware services.

We introduce new type of networked robot, Ubiquitous Robotic Companion (URC), embedded with ATLAS Service-oriented architecture for enhancing the space sensing capability. URC is a network-based robotic system developed by ETRI. For years of experience in deploying service with ATLAS sensor platform for elder and people with special needs in smart houses, we need networked robots to assist elder people in their successful daily living. Recently, pervasive computing technologies reveals possibilities of networked robots in smart spaces, consist of sensors, actuators and smart devices can collaborate with the other networked robot as a mobile sensing platform, a complex and sophisticated actuator and a human interface. This paper provides our experience in designing and implementing system architecture to integrate URC robots in pervasive computing environments using the University of Florida's ATLAS service-oriented architecture. In this paper, we focus on the integrated framework architecture of URC embedded with ATLAS platform. We show how the integrated URC system is enabled to provide better services which enhance the space sensing of URC in the smart space by applying service-oriented architecture characterized as flexibility in adding or deleting service components of Ubiquitous Robotic Companion.

The experience of full automation without explicit user direction may induce anxiety among smart space users. The use of explicit mediators between users and fully automated systems may help to mitigate users’ anxiety. While robots mediators are one possible solution, several issues remain, including high complexity and limited collaboration between robots and smart space platforms, reducing overall system reliability. This paper proposes the Integrated Control Architecture for Robotic mediator in Smart environments (ICARS) as a solution to improve the integration and reliability of robot mediators within automated smart spaces. Assuming relatively thin network robots as robotic mediators to enable a wide distribution with less cost, ICARS provides a well-organized software framework consisting of three layers to integrate robots and smart spaces: a flexible communication/device model, an adaptive service model for the integrated robot control architecture, and a behavior-based high-level collaboration model. In this paper, we also present details of the design, implementation, and an application scenario conducted with ICARS. The results show that ICARS enables flexible integration of the diverse devices associated with robots and environments, adaptive service provision for collaborative services, and easier development of high-level collaborative applications with decent performance.

Life cycle management plays an essential role in context-aware systems, it needs to aware surrounding contexts and adapt to changing contexts in highly dynamic environments. Consequently, context management is different from traditional approaches due to the characteristics of contextual information are dynamic, transient, and fallible. Understanding the life cycle of a context is the key issue to maintain consistent contextual information. Accordingly, we propose an ontology-based model for representing, deducing, and managing consistent contextual information. In addition, an agent-based architecture supports the process of context life cycle management.

The expanding computer landscape leads us toward ubiquitous computing, in which smart gadgets seamlessly provide intelligent services anytime, anywhere. Smartphones and other smart devices with multiple sensors are at the vanguard of this paradigm, enabling context-aware computing. Similar setups are also known as smart spaces. Context-aware systems, primarily deployed on mobile and other resource-constrained wearable devices, use a variety of implementation approaches. Rule-based reasoning, noted for its simplicity, is based on a collection of assertions in working memory and a set of rules that regulate decision-making. However, controlling working memory capacity efficiently is a key challenge, particularly in the context of resource-constrained systems. The paper's main focus lies in addressing the dynamic working memory challenge in memory-constrained devices by introducing a systematic method for content removal. The initiative intends to improve the creation of intelligent systems for resource-constrained devices, optimize memory utilization, and enhance context-aware computing.

The objective of this paper is to demonstrate the effective deployment of a robotic assessment tool for the evaluation of mild traumatic brain injury (mTBI) patients in a busy, resource-constrained, urban emergency department (ED). Methods: Functional integration of new robotic technology for research in the ED presented several obstacles that required a multidisciplinary approach, including participation from electrical and computer engineers, emergency medicine clinicians, and clinical operations staff of the hospital. Our team addressed many challenges in deployment of this advanced technology including: 1) adapting the investigational device for the unique clinical environment; 2) acquisition and maintenance of appropriate testing space for point-of-care assessment; and 3) dedicated technical support and upkeep of the device. Upon successful placement of the robotic device in the ED, the clinical study required screening of all patients presenting to the ED with complaints of head injury. Eligible patients were enrolled and tested using a robot-assisted test battery. Three weeks after the injury, patients were contacted to complete follow-up assessments. Results: Adapting the existing technology to meet anticipated physical constraints of the ED was performed by engineering a mobile platform. Due to the large footprint of the device, it was frequently moved before ultimately being fully integrated into the ED. Over 14 months, 1423 patients were screened. Twenty-eight patients could not be enrolled because the device was unavailable due to operations limitations. Technical problems with the device resulted in failure to include 20 patients. A total of 66 mTBI patients were enrolled and 42 of them completed both robot-assisted testing and follow-up assessment. Successful completion of screening and enrollment demonstrated that the challenges associated with integration of investigational devices into the ED can be effectively addressed through a collaborative patient-oriented research model. Conclusion: Effective deployment and use of new robotic technology for research in an urban academic ED required significant planning, coordination, and collaboration with key personnel from multiple disciplines. Clinical Impact: A pilot clinical study on mTBI patients using the robotic device provided useful data without disrupting the ED workflow. Integration of this technology into the ED serves as an important step toward pursing active clinical research in an acute care setting.

Smart devices have been widely adopted in our daily life. A smart home system, e.g., Home Assistant and openHAB, can be equipped with hundreds and even thousands of smart devices. A smart home system communicates with smart devices through various device integrations, each of which is responsible for a specific kind of devices. Developing high-quality device integrations is a challenging task, in which developers have to properly handle the heterogeneity of different devices, unexpected exceptions, etc. We find that device integration bugs, i.e., iBugs, are prevalent and have caused various consequences, e.g., causing devices unavailable, unexpected device behaviors.

In recent years, the upward trend in adolescent obesity rates has become increasingly evident. The emergence of smart wearable devices has broken through the traditional technical barriers of sweat detection, enabling real-time, non-invasive, and continuous monitoring of athletic performance in adolescents. This report aims to explore the impact of smart wearable devices on enhancing the athletic performance of adolescents from the perspective of sweat analysis. Method: We employed various research methods, including literature review, logical analysis, and statistical analysis, to conduct a comprehensive search for relevant literature from the past five years in electronic databases such as PubMed, Web of Science, and CNKI. This review summarizes the latest research advancements in the field of athletic performance monitoring based on sweat analysis and the application of smart wearable devices (1). The electrolytes found in sweat can be utilized to assess the body’s hydration status and muscle fatigue levels. Detection of metabolites such as glucose and lactate can indicate physical fitness status and anaerobic metabolism levels. Furthermore, cortisol can be used to evaluate the effectiveness of fat loss in adolescents. (2) Screen printing technology allows for the integration of multiple electrochemical sensors onto a single flexible substrate, enabling non-invasive detection of sweat biomarkers through methods such as colorimetric analysis and electrochemical analysis using various sensitive elements. Microfluidic systems serve as the core technology, facilitating the absorption and accumulation of sweat, thus enhancing detection efficiency. (3) Smart wearable devices based on sweat analysis can assess various indicators, including activity intensity, energy expenditure, hydration status, and thermoregulation abilities of obese adolescents during exercise. Additionally, employing big data analytics, these devices can provide personalized exercise prescriptions tailored to the specific needs of adolescents. Smart wearable devices based on sweat detection hold great potential for a wide range of applications. However, several issues persist in their current practical use. For example, the rapid evaporation of sweat can lead to detection results that are easily influenced by environmental factors and temperature. Additionally, the sensitivity of smart sensors may decrease after repeated use. Therefore, it is essential to strengthen the interdisciplinary integration of fields such as electrochemistry, materials science, and exercise science. This collaboration can enrich the practical application scenarios of smart wearable devices and optimize the pathways for monitoring athletic performance.

Driven by the advances of information and communication technologies (ICT) as well as the increasing complexity of product and service bundles in business market, smart product-service system (Smart PSS) has become a key factor for industrial companies to meet demanding customer expectations of individual product and services. Requirement management, as the first step of Smart PSS development, significantly affects its final success. In Smart PSS, requirement management is endowed with new capabilities and opportunities due to the mature of the advances of techniques and smart devices. The manner of requirement management has transformed from a human-intensive manner to a data-driven manner. Facing this challenge, scarcely any paper discussed the foundations of managing requirements in the context of Smart PSS. In this paper, the prerequisites of managing requirements in Smart PSS are discussed, data properties, representation format and reasoning methods are analyzed based on a data-driven requirement management architecture. Two potential scenarios of requirement management are discussed as well. This work depicts the deserving manner of requirement management in Smart PSS, which points out key points of managing requirements from heterogeneous usage data in the new Smart PSS paradigm.