Precise localization and target tracking in coal mine tunnel is crucial for miners' safety protection. Due to the special environment of coal mine tunnel, the conventional positioning systems can not determine the...
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Precise localization and target tracking in coal mine tunnel is crucial for miners' safety protection. Due to the special environment of coal mine tunnel, the conventional positioning systems can not determine the specific location of underground personnel in real-time and with high positioning accuracy. In this paper, an improved fingerprinting algorithm based on underground Wi-Fi network is proposed to increase positioning accuracy. In our localization scheme, Received Signal Strength Indication (RSSI) from wireless Access Point (AP) and Support Vector Machine (SVM) based classifier are employed for position analysis. Specifically, the outliers were excluded by data preprocessing using k nearest neighbor (kNN) rule in the training phase, and results correction was utilized in the positioning stage. The positioning performance in coal mine tunnel environment demonstrates that the proposed improved fingerprinting algorithm can improve the positioning accuracy and the location of the miner can be computed in less time compared with traditional approach.
Precise localization and target tracking in coal mine tunnel is crucial for miners’ safety protection. Due to the special environment of coal mine tunnel, the conventional positioning systems can not determine the sp...
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Precise localization and target tracking in coal mine tunnel is crucial for miners’ safety protection. Due to the special environment of coal mine tunnel, the conventional positioning systems can not determine the specific location of underground personnel in real-time and with high positioning accuracy. In this paper, an improved fingerprinting algorithm based on underground Wi-Fi network is proposed to increase positioning accuracy. In our localization scheme, Received Signal Strength Indication (RSSI) from wireless Access Point (AP) and Support Vector Machine (SVM) based classifier are employed for position analysis. Specifically, the outliers were excluded by data preprocessing using k nearest neighbor (kNN) rule in the training phase, and results correction was utilized in the positioning stage. The positioning performance in coal mine tunnel environment demonstrates that the proposed improved fingerprinting algorithm can improve the positioning accuracy and the location of the miner can be computed in less time compared with traditional approach.
Positioning based on received signal strength (RSS) is regarded as a promising candidate for localization purposes in wireless networks due to its feasibility and deployability. In general, multilateration and fingerp...
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Positioning based on received signal strength (RSS) is regarded as a promising candidate for localization purposes in wireless networks due to its feasibility and deployability. In general, multilateration and fingerprinting algorithms are the primary localization methods in RSS-based localization systems, which are assessed by the Cramer-Rao lower bound (CRLB), given fixed node locations, including the target and participating anchors. However, this methodology produces only definite values for the CRLB specific to the scenario of interest while does not provide insights into the fundamental limits of localization performance. Thus, we are motivated to analyze the RSS-based localization performance using stochastic geometry to allow for randomly distributed nodes and investigate how the nodes' locations influence this performance. To characterize the localization performance of the multilateration method, a tractable expression of localizability is provided to indicate the probability that a target is localizable. Then, conditioned on the number of participating anchors L, we provide an accurate approximation of the CRLB using the [L/4]th value of ordered distances to quantify the localization accuracy on a random network setting and examine how its performance is influenced under different propagation channels by utilizing kappa-mu shadowed fading. Next, the fingerprinting localization problem is regarded as a hypothesis testing problem, and thus, its performance can be evaluated based on the similarity analysis of the observed RSS fingerprints. A comprehensive analysis of these two methods is performed, and the derived calculations are compared with the experimental results to demonstrate that our unified framework can precisely reflect localization performance in real-world scenarios. Based on the analysis, we can develop an insight to optimally design an RSS-based localization system that achieves the specified localization requirements.
The fast increase in the percentage of elderly people over the past few years has prompted a major interest in developing monitoring systems to help in the well being of the elderly. More importantly, we are also witn...
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ISBN:
(纸本)9781665414937
The fast increase in the percentage of elderly people over the past few years has prompted a major interest in developing monitoring systems to help in the well being of the elderly. More importantly, we are also witnessing an increase in the number of elderly needing assistance because of diverse chronic diseases. The elderly related dementia is among the most disabling diseases with dangerous consequences such as wandering into hazardous or insecure areas. This wandering, particularly in urban areas can be life threatening. Recently, with the rapid emergence of disruptive technologies like Internet of Things (IoT) and Radio Frequency Identification (RFID), it has become possible to build systems that combine IoT and the cloud for monitoring the elderly suffering from dementia or depression. This paper introduces an RFID-based novel cost-effective tracking system for a multi-person home. The proposed system can accurately track up to three elderly people within the room they are in. The proposed prototype solution is based on wearable anklets or bracelets with batteryless tags for localizing elderly wandering within the home using passive RFID. An Android Applet was developed for localizing the elderly and alerting caregivers of at-risk inhabitants of smart homes within and outside (at exit level) the residence area.
It is well known that Wi-Fi indoor positioning accuracy is vulnerable to environmental fluctuations. In this paper, we propose a novel Wi-Fi indoor positioning method which applies signal strength order invariance (SS...
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ISBN:
(纸本)9781479962396
It is well known that Wi-Fi indoor positioning accuracy is vulnerable to environmental fluctuations. In this paper, we propose a novel Wi-Fi indoor positioning method which applies signal strength order invariance (SSOI) to overcome the problem of environment influence and hence improve the positioning accuracy. In the off-line phase we save not only the signal strength of reference points but also the corresponding signal strength order. Then in the online phase, the measured signal strength and the associated order are used jointly to estimate the unknown point's coordinate. Simulation and experimental results both demonstrate that our proposed algorithm can achieve better positioning accuracy than the methods using the traditional nearest neighbor (NN) or K-nearest-neighbors (KNN) fingerprinting algorithm only.
Design smells in software models reduce the software quality. Smells identification supports the refractoring, which is a way to improve the quality of models and subsequently increasing software readability, maintain...
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ISBN:
(纸本)9780769544182
Design smells in software models reduce the software quality. Smells identification supports the refractoring, which is a way to improve the quality of models and subsequently increasing software readability, maintainability and extensibility. We propose a preliminary study of using Similarity Scoring algorithm and fingerprinting algorithm for design smells detection. In the future, we plan to do extensive verification on several large projects, integrate these methods to the smells detection framework and compare effectiveness with other approaches.
Coal mine industry, which produces the most abundant and widely-distributed fossil fuel, is the deadliest in casualties. A recent report shows that the casualty rates of coal production per million tones are 4.36 in C...
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