Published papers

In the event of a large-scale disaster, the dissemination of audible disaster warning information via sirens is effective in ensuring a rapid response. Sirens can be installed not only on fixed towers, but also on public transport and other vehicles passing through residential areas, and at spots where residents congregate, to increase area coverage. Although models to calculate the spatial coverage of audible information delivered from fixed sirens have been constructed, no general-purpose model has been developed to assess the delivery from vehicles. In this study, we focused on the General Transit Feed Specification (GTFS), which is an open format for geospatial information on public transport. We conducted a spatial analysis using a geographic information system (GIS) on the basis of the acquired bus location information. We developed a model to calculate the spatial coverage of the audible information delivery for overlapping hazard maps and population. Assuming a flood occurred in the vicinity of Brisbane Central Station, Queensland, Australia, we confirmed that the developed model was capable of characterizing the time-series changes in the exposed population in the target area. Since the GTFS format is currently distributed across various countries, this assessment model is considered to be highly versatile and widely applicable.

There is a growing need to introduce warning dissemination systems in disaster-prone regions to improve the coverage of information distribution. In this study, a warning dissemination system was designed in which disaster information transmitted by a global navigation satellite system (GNSS) is received by terrestrial infrastructure, such as sirens and public transportation, converted into audio messages, and delivered automatically. The originality of the designed system lies in its appropriate integration of existing satellite systems and terrestrial infrastructure, making the system potentially applicable in many regions. First, we evaluated the effectiveness of the designed system in distributing audio messages using public buses in Brisbane, Australia, where large floods occur frequently. Real-time location information for public buses was acquired in the format of General Transit Feed Specification (GTFS), which is currently used in many countries. Time-series changes in the coverage rate relative to both the flood inundation zone and population were calculated using a geographic information system (GIS). The simulation results showed that the system could reach 60% of the flood inundation zone and 70% of the population on a holiday, indicating that the designed system could be effec-tively adapted to the target area. The coverage rate was found to peak during 15:00–16:00, with minimum rates observed late at night and early in the morning. These results will allow the development of an effective disaster management plan. In the future, this system will be evaluated in other regions using the same cal-culation process.

With the widespread use of indoor positioning technology, various services based on this technology are beginning to be offered to consumers and industrial applications. In the case of logistics facilities, in addition to indoor and outdoor spaces, there are top-bounded spaces (TBSs): elongated areas that are covered with roofs or eaves on the upper parts of buildings. The sides of such spaces are open, and workers and forklifts work in these areas. Only a few studies have been conducted on positioning methods for this unusual environment, and the way by which Signal-to-Noise Ratio (SNR) of Global Positioning System (GPS) changes with the stay in TBSs is unclear. Therefore, we conducted preliminary experiments and confirmed that TBS dwellings are difficult to stably detect with existing methods due to the combination of satellites with variable and unchanged SNRs. In this study, we designed a simple processing flow for selecting satellites with high probabilities of changing SNRs by using the spatial characteristics of TBSs as parameters (height, depth, and side opening orientation). We propose a method to detect the stay in TBSs using the SNR change rates of the selected satellites. As a result of evaluation experiments with three TBSs, we successfully detected the stay in TBSs with about 30% higher probability than those of an existing method.

Numerous studies have been conducted on indoor and outdoor seamless positioning and indoor–outdoor detection methods. However, the classification of real space into two types, outdoor space and indoor space, is difficult. One type of space that is difficult to classify is top-bounded space, which can be observed in commercial facilities, logistics facilities, and street-facing sidewalks. In this study, we designed a method for detecting stays in three spatial contexts: Outdoor, top-bounded space, and indoor. This method considers elongated top-bounded spaces covered with a roof and open on one of the sides. Specifically, we selected Global Positioning System (GPS) satellites for stay detection based on the simple extraction of the spatial characteristics of a top-bounded space and designed a decision flow using fuzzy inference based on the signal-to-noise ratio (SNR) of the selected GPS satellites. Moreover, we conducted an evaluation experiment to verify the effectiveness of the proposed method and confirmed that it could correctly detect the stay in three spatial contexts, outdoor, top-bounded space, and indoor, with a high probability of 93.1%.

© 2019 IEEE. The installation process of numerous Bluetooth Low Energy (BLE) beacons in the indoor positioning environment usually requires the manual measurement of the beacon's physical coordinates which tends to be a labor-intensive process. In this work, we aim to create a BLE beacon map by obtaining their coordinates from in situ Received Signal Strength (RSS) observations on a smartphone in a short period of time. This paper proposes a method of automatic localization for twin BLE beacons based on Range-Only Simultaneous Localization and Mapping (RO-SLAM) approach and multi-hypothesis Extended Kalman Filter (EKF), on the condition that only the relative distance of twin beacons is known. In this method, a person holding a smartphone collects RSS of BLE beacons by walking around with no requirement of predefined trajectory. Normally, the lack of angular information on the sensor involves the difficulty of finding a good initial value of the state vector in the EKF, that requires substantial time to evolve the estimation enough. In our proposed method, tracking the multiple hypotheses which represent the probability distribution of possible locations of the BLE beacon and smartphone makes the results obtainable in a brief RSS survey. The hypotheses generation process employs the interval information of twin BLE beacons to reduce the number of hypotheses and consequently the computational load. The experimental evaluation using commercial off-the-shelf devices show that the proposed method offers a significant improvement in the time required to evolve the location estimation, while the use of twin BLE beacons can suppress the total number of hypotheses.