A tracking service like asset management is essential in a dynamic hospital environment consisting of numerous mobile assets (e.g., wheelchairs or infusion pumps) that are continuously relocated throughout a hospital. The tracking service is accomplished based on the key technologies of an indoor location-based service (LBS), such as locating and monitoring multiple mobile targets inside a building in real time. An indoor LBS such as a tracking service entails numerous resource lookups being requested concurrently and frequently from several locations, as well as a network infrastructure requiring support for high scalability in indoor environments. A traditional centralized architecture needs to maintain a geographic map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor mobile asset management (MAM) platform, and proposes an architecture for multiple trackees (such as mobile assets) and trackers based on the proposed distributed platform in real time. In order to verify the suggested platform, scalability performance according to increases in the number of concurrent lookups was evaluated in a real test bed. Tracking latency and traffic load ratio in the proposed tracking architecture was also evaluated.

Obstructive sleep apnea (OSA), although it is a common symptom for ordinary people, is a serious issue in that it can lead to chronic and degenerative brain disease. However, these sleep disorders and apnea symptoms are difficult to diagnose at home or to recognize and cope with severe apnea situations. In response to this, we developed a Sleepcare Kit, an integrated wearable device. The Sleepcare Kit is a wearable distributed system in which the PAAR band and the bio-cradle are combined in the form of a hot plug-in without pre-setting. The PAAR band serves as a gateway for wireless communication with external devices and adjusts initial setting values for various sensors of the bio-cradle. Bio-cradle continuously measures/stores multiple bio-signals (PPG/SPO2, respiration, 3axis-acc, and body temperature) and analyzes the signal data to determine sleep quality and emergency situation in real-time. Although it is a set of small wearable devices, the kit itself diagnoses sleep quality on a real-time base without any external computing assistance while he/she is asleep. Simultaneously, it analyzes the gathered hypopnea and apnea data in real time and calculates the apnea risk phase. Moreover, according to the apnea risk phase, it can inform the wearer or guardian about the danger through the smartphone or smart-speaker. In this paper, we will discuss the algorithm that is used for the detection of sleep apnea in Sleepcare Kit, as well as the software platform for continuous measurement and synchronization of various bio-signals in real time. Moreover, we evaluated the accuracy of the system by comparing the obtained results with the polysomnography equipment used in hospitals.INDEX TERMS Wearable device, healthcare, sleep apnea, hypopnea, body-area network.

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Most older persons would prefer “aging in my place,” that is, to remain in good health and live independently in their own home as long as possible. For assisting the independent living of older people, the ability to gather and analyze a user’s daily activity data would constitute a significant technical advance, enhancing their quality of life. However, the general approach based on centralized server has several problems such as the usage complexity, the high price of deployment and expansion, and the difficulty in identifying an individual person. To address these problems, we propose a wearable device platform for the life assistance of older persons that automatically records and analyzes their daily activity without intentional human intervention or a centralized server (i.e., cloud server). The proposed platform contains self-organizing protocols, Delay-Tolerant Messaging system, knowledge-based analysis and alerting for daily activities, and a hardware platform that provides low power consumption. We implemented a prototype smart watch, called Personal Activity Assisting and Reminding (PAAR), as a testbed for the proposed platform, and evaluated the power consumption and the service time of example scenarios.

The tracking of multiple wireless mobile nodes is not easy with current legacy WSN technologies, due to their inherent technical complexity, especially when heavy traffic and frequent movement of mobile nodes are encountered. To enable mobile asset tracking under these legacy WSN systems, it is necessary to design a specific system architecture that can manage numerous mobile nodes attached to mobile assets. In this paper, we present a practical system architecture including a communication protocol, a three-tier network, and server-side middleware for mobile asset tracking in legacy WSNs consisting of mobile-stationary co-existing infrastructures, and we prove the functionality of this architecture through careful evaluation in a test bed. Evaluation was carried out in a microwave anechoic chamber as well as on a straight road near our office. We evaluated communication mobility performance between mobile and stationary nodes, location-awareness performance, system stability under numerous mobile node conditions, and the successful packet transfer rate according to the speed of the mobile nodes. The results indicate that the proposed architecture is sufficiently robust for application in realistic mobile asset tracking services that require a large number of mobile nodes.