Data-Correlation-Based Sensor Localization for Environment Sensing with Non-Geotagged Data

Shiraki, Shino; Ohashi, Yuto; Shioda, Shigeo

doi:10.1109/vtc2020-fall49728.2020.9348657

Cited by 3 publications

(7 citation statements)

References 16 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%

“…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. Separately, we proposed a method for observing the physical world via a sensor response-based localization technology that is based solely on non-geotagged sensor data [3], [4]. However, the performance verifications conducted in that study were limited to simulations.…”

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%

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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“…In this study, we estimated sensor locations from proximity relations using the sensor response-based localization method [7]. First, we assumed that the responses of spatially proximate sensors were highly correlated when object detection-type sensor devices were installed at high density.…”

Section: B Proximity Relations Using Spatial Correlationmentioning

confidence: 99%

“…The proposed method enables location estimation from sensor response data obtained during environmental monitoring, even for sensors that are not equipped with range functions. Notably, part of the basic concepts of the proposed method was presented at the IEEE VTC-Fall 2020 [7].…”

Section: Introductionmentioning

confidence: 99%

“…In this study, our objective was to establish a highly accurate localization method for environmental monitoring. For this purpose, we expanded the proximity relation determination method from the conference paper [7] and clarified the factors that affect localization accuracy by performing several performance evaluations. The main contributions of this study are summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

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Sensor Response-Based Localization Using Spatial Correlation of Nongeotagged Data

Shiraki,

Shioda,

Matsuda

2024

IEEE Sensors J.

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Sensor devices in future wireless communication systems such as beyond fifth generation (Beyond 5G) and sixth generation (6G) require highly accurate location information. Owing to high power consumption and cost, global navigation satellite system receivers may not be installed on sensor devices, requiring the localization of sensor devices on a wireless sensor network (WSN). In many WSN applications, a spatially dense sensor installation is required to achieve satisfactory coverage. When object detectiontype sensor devices are installed at high density, the responses of spatially proximate sensors are highly correlated. In other words, these sensor responses indirectly include location information. Based on this consideration, we proposed a sensor localization method using the spatial correlation of nongeotagged sensor response data and evaluated its performance. Our method enables location estimation from the response data obtained during environmental monitoring, even for sensors that are not equipped with range functions. The simulation experiments showed that a more accurate sensor localization is possible with an error of 1 m using a wider sensor detection range, even with rough proximity pair ratio settings. In addition, we verified that there is a trade-off between localizability and observability during environmental monitoring, such as the visualization of vehicle positions from sensor responses. Our proposed method may be applied to future urban environments with a large number of sensor devices installed for environmental monitoring.

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Target Counting Using Binary Sensors Based on Disjoint Connected Subgraphs

Shiraki

Shioda

2021

2021 Wireless Days (WD)

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Data-Correlation-Based Sensor Localization for Environment Sensing with Non-Geotagged Data

Cited by 3 publications

References 16 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

Sensor Response-Based Localization Using Spatial Correlation of Nongeotagged Data

Target Counting Using Binary Sensors Based on Disjoint Connected Subgraphs

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