Indoor Positioning Based on Bluetooth RSSI Mean Estimator for the Evacuation Supervision System Application

Janczak, Dariusz; Walendziuk, Wojciech; Sadowski, Maciej; Zankiewicz, Andrzej; Konopko, Krzysztof; Slowik, Maciej; Gulewicz, Malgorzata

doi:10.1109/access.2024.3389986

Cited by 2 publications

(1 citation statement)

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“…Bluetooth devices have been widely applied in electronic devices, such as smart phones, laptops, wristbands and so on. Most commercial solutions calculated the target's location with measured angles and signal strengths [45,46]. Among them, the Spotlight algorithm was proposed [47], which utilized both the AoA and elevation of angle (EoA) of the signals to solve more accurate angle estimates.…”

Section: Basic Localization Technologiesmentioning

confidence: 99%

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments

He,

Huang

2024

Sensors

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With the rapid development of fully automatic operation (FAO) and location-based services, the evaluation criteria of average localization accuracy can no longer meet our demands, in favor of deterministic localization. However, most localization researches modeled localization performance function and enhanced it by minimizing average localization root mean square error (RMSE). The performance degradation in a small region was not considered. In this paper, we present a survey of deterministic localization and analyze the relationship between accuracy and certainty. In this paper, two common solutions of localization enhancement are presented and their localization certainties are discussed. Furthermore, we carry out related localization enhancement experiments in rail transit line and analyze their improvement on deterministic localization. The experimental results show that the overall localization performance is improved, while the deterministic localization requires the stricter solution to promote.

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Section: Basic Localization Technologiesmentioning

confidence: 99%

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments

He,

Huang

2024

Sensors

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Hybrid neural network for personnel recognition and tracking in remote bidding evaluation monitoring

Zhou,

Wang,

Meng

et al. 2024

Preprint

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Unauthorized access to the bidding evaluation office and the departure of experts can significantly compromise the quality of on-site assessment work and introduce substantial integrity risks. To address these concerns, this paper presents the development of a hybrid neural network, integrating Yolov5s, Deepsort, and Dlib to ascertain the status of person within the bidding evaluation office. Our approach is bifurcated into two primary components. Firstly, Deepsort is integrated with Yolov5s to develop a model for the detection and tracking of personnel within the evaluation office. The model detects, counts, and tracks the flow of personnel on site and assesses the presence or absence of experts. Subsequently, Yolov5s, enhanced by the Swin Transformer architecture, refines the Dlib facial recognition model, augmenting its capacity to detect and swiftly identify small faces, thereby discerning potential intruders. The experimental results demonstrate that the model is capable of effectively detecting and tracking personnel on site, recognizing novel micro-scale targets, verifying individual identities, and evaluating the status of on-site personnel. Throughout the testing phase, when juxtaposed with conventional methodologies, our model has exhibited a marked enhancement in the accuracy of detecting unauthorized entry and the absence of designated experts, enabling real-time analysis of the evaluation office's status.

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Indoor Positioning Based on Bluetooth RSSI Mean Estimator for the Evacuation Supervision System Application

Abstract: and Moose sp. z O. O., while the part related to the research on the development of auxiliary devices used for the construction of system components were covered by a Bialystok University of Technology internal grants.

Cited by 2 publications

References 66 publications

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments

Deterministic Localization for Fully Automatic Operation: A Survey and Experiments

Hybrid neural network for personnel recognition and tracking in remote bidding evaluation monitoring

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