Localizing Sensors from Their Responses to Targets

Shioda, Shigeo

doi:10.1587/transcom.e98.b.145

Cited by 9 publications

(10 citation statements)

References 18 publications

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“…The sensor response-based localization technology proposed in this paper and our previous studies [2]- [4] also uses connectivity-based localization. However, unlike existing methods, our method estimates proximity relationships between sensors from the "closeness of the sensor response time" [2], [3] or the "collected data similarity (correlation coefficient)" [4]. A novel feature of our method is that it allows sensor response-based localization technology to be applied to inexpensive sensors that cannot send or receive radio signals to or from each other.…”

Section: Related Workmentioning

confidence: 99%

“…Based on the assumption that Sensor 1 is located at the coordinate origin, we set 1 = (0, 0) in (2). Function ( 2 , .…”

Section: Relative Sensor Location Mapmentioning

confidence: 99%

“…( 3 ). Note that inverting the matrix is only required once because the same matrix is used for all iteration steps [2]. Once the inverse of the matrix is obtained, the amount of calculation required for obtained {ˆ( ) } =2 is ( 2 ).…”

Section: F Computational Complexity Of the Proposed Localizationmentioning

confidence: 99%

“…where the inequality follows from the Cauchy-Schwartz inequality 1) and =ˆ( 2) , the inequality (13) yields 2) .…”

Section: Appendixmentioning

confidence: 99%

“…In a previous study, we proposed a sensor response-based localization method that can produce location estimates from non-geotagged sensor responses [2]. This technology obtains proximity relationships among sensors in real-world environments from the closeness of the sensor response time or collected data similarities and then estimates relative and absolute sensor locations from their proximity relationships.…”

Section: Introductionmentioning

confidence: 99%

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Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

et al. 2021

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A sensor response-based localization technology that uses the non-geotagged responses of environmental object detection sensors to estimate the positions of sensors in a defined observation area was proposed in a previous study. That method is based on the concept that the proximity relationships among sensors obtained from the closeness of the sensor response times or collected data similarities. However, since that study was limited to simulation-based experiments, this study extends the scheme to experiments involving real devices, simulated environments, and ideal environments to ascertain the accuracy of localization estimates produced using real devices. We also aimed at extracting the problems that must be resolved before the proposed technology can be put into practical use. Even if clock synchronization between the sensors was impossible, the proximity relationships among them could be estimated using before-after detection time relationships, thus confirming that sensor locations could be estimated based on these proximity relationships. In a real device experiment using 20 sensors indoors at 20.25 2 , we confirmed that the average localization error was 0.84 m. Based on those results and other findings resulting from this study, we determined that the primary factor related to increased sensor localization errors was the number of incorrectly constructed sensor pairs. The results of this study are expected to facilitate the realization of physical world sensing using sensor response-based localization technology.

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Section: Related Workmentioning

confidence: 99%

“…Based on the assumption that Sensor 1 is located at the coordinate origin, we set 1 = (0, 0) in (2). Function ( 2 , .…”

Section: Relative Sensor Location Mapmentioning

confidence: 99%

Section: F Computational Complexity Of the Proposed Localizationmentioning

confidence: 99%

“…where the inequality follows from the Cauchy-Schwartz inequality 1) and =ˆ( 2) , the inequality (13) yields 2) .…”

Section: Appendixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

et al. 2021

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Contact Information-Based Indoor Pedestrian Localization Using Bluetooth Low Energy Beacons

Shiraki

Shioda

2022

IEEE Access

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Indoor localization technologies are actively investigated to realize location-based applications in various environments, and indoor localization methods based on whether the received signal strength indicator (RSSI) is less than a threshold have been proposed previously. Such a proximity/nonproximity binary value is used in digital contact tracing applications to reduce the coronavirus disease effects. We proposed two indoor pedestrian localization methods based on contact information using bluetooth low energy (BLE) beacons, namely multilateration and cooperative localization. This study attempts to demonstrate the effectiveness of the proposed methods using only contact information. Through simulation experiments, we found that the proposed methods can achieve comparable accuracy to existing methods when the attenuation model is accurate. The difference in average localization error was 0.1 m between the proposed method 1 and range-based method, and 0.2 m between the proposed method 2 and fingerprinting method. We confirmed that the proposed methods using only contact information are robust against environmental changes even when the attenuation model is inaccurate. We consider that these contributions have added a new perspective on the use of contact information in the field of indoor localization, which aims to realize power-saving and cost reduction.

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Environment Sensing Based on Non-Geotagged Sensor Data

Shioda

Ohashi

2020

2020 International Conference on Computing, Networking and Communications (ICNC)

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Localizing Sensors from Their Responses to Targets

Cited by 9 publications

References 18 publications

Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

Verification of Error-Increasing Factors by Sensor Response-Based Localization Technology Through Real Device Experiments

Contact Information-Based Indoor Pedestrian Localization Using Bluetooth Low Energy Beacons

Environment Sensing Based on Non-Geotagged Sensor Data

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