Development of an adaptive device-free human detection system for residential lighting load control

Santiprapan, Phonsit; Sengchuai, Kiattisak; Jindapetch, Nattha; Saitō, Hiroshi; Booranawong, Apidet

doi:10.1016/j.compeleceng.2021.107233

Cited by 7 publications

(6 citation statements)

References 15 publications

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“…Such factors can affect radio signal propagation and RSSI measurement. [33][34][35] Zolertia Z1 motes as low-power wireless sensor nodes 36,37 are used to operate the wireless network. The Z1 mote is equipped with a MSP430F2617 microcontroller and a CC2420RF module.…”

Section: Methodsmentioning

confidence: 99%

Development of an indoor corridor localization system based on a WCL method with corridor area selection and distance compensation

Wattananavin,

Booranawong,

Saito

2024

Int J Communication

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SummaryIn this paper, a received signal strength indicator (RSSI)‐based weighted centroid localization (WCL) method for indoor corridor scenarios is developed and tested. The contribution of the proposed system is that, to scope the area of an unknown target position, the possible corridor area where the target node should be located is automatically selected, and only reference nodes deployed in such an area are applied for position estimation. Additionally, to improve the estimation precision, distance values converted from measured RSSIs and used for the WCL are also compensated to alleviate the RSSI variation problem caused by physical environments. Therefore, our methods can save a number of reference nodes to be used, while localization accuracy can also be achieved. Experiments in the corridor environment using a 2.4 GHz IEEE 802.15.4 wireless sensor network with four reference nodes deployed in the test field dimension of 22 m × 9.3 m have been performed. Experimental results demonstrate that the proposed method, which requires only two reference nodes, outperforms the original WCL method with four reference nodes by 53.053%, as indicated by average localization errors. The results also reveal that the proposed method provides error distances lower than the WCL method for all test target positions, while all estimated positions fall within the corridor areas by 100%.

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Section: Methodsmentioning

confidence: 99%

Development of an indoor corridor localization system based on a WCL method with corridor area selection and distance compensation

Wattananavin,

Booranawong,

Saito

2024

Int J Communication

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“…EWMA, a time series filtering method based on weighted averaging, assigns a larger weight to the most recent data points and a smaller weight to the historical data points, thus effectively eliminating noise and random variations. EWMA has found wide application in the filtering of data (Roberts, 2000;Santiprapan et al, 2021). The formula for EWMA is as follows:…”

Section: Ewma Filteringmentioning

confidence: 99%

“…EWMA, a time series filtering method based on weighted averaging, assigns a larger weight to the most recent data points and a smaller weight to the historical data points, thus effectively eliminating noise and random variations. EWMA has found wide application in the filtering of data (Roberts, 2000; Santiprapan et al., 2021). The formula for EWMA is as follows:

{\text{EWMA}}_{t}={\alpha X}_{t}+(1-\alpha ){\text{EWMA}}_{t-1}

In the formula, X t denotes the t th data point, EWMA t ‐1 denotes the EWMA value at the previous time point, α , called the smoothing coefficient, usually takes a value ranging from 0 to 1 (Lin et al., 2013).…”

Section: Calibration Model Based On Machine Learningmentioning

confidence: 99%

Measurement and Calibration of EMF: A Study Using Phone and GBDT for Mobile Communication Signals

Zeng,

Chen,

et al. 2024

Radio Science

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Electromagnetic exposure caused by mobile communication signals has always been a cause of concern. Due to the cost and inconvenience of professional measurement equipment, researchers have turned to smartphone APPs to study and assess the electric field strength caused by mobile communication signals. However, existing cell phone‐based measurements have two weaknesses. First, no system architecture suitable for large‐scale crowdsourced testing has been proposed. Second, since smartphone sensors cannot measure electric field strength directly, existing methods for converting the received signal power of the phone and electric field strength have errors of more than 5 dB. This paper proposes a measurement and calibration method for electric field strength of mobile communication signals based on a smartphone app and gradient boosting decision tree (GBDT). This method consists of a downlink signal acquisition system based on an APP and a calibration model based on GBDT to convert received signal power into electric field strength. The experimental results show that the proposed model achieves a R2 score of 0.93 and a MAE of 0.97 dB. Compared with the existing methods, our method improves the calibration accuracy by 4 dB, enabling large‐scale, low‐cost, and high‐precision direct measurement of the electric field strength of mobile communication signals.

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“…The achieved accuracy exceeded 90%. With the help of special Zigbee modules (used for low-consumption wireless communication) and an algorithm based on moving averages [8], it was possible to achieve 100% accuracy in laboratory conditions. The probabilistic algorithm based on MRF (Markov Random Fields) [9] achieved an accuracy of 86% in a large room with an area of 150 m 2 .…”

Section: Rssi-based Approachesmentioning

confidence: 99%

Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks

Shibaev¹,

Chupakhin²

2022

Proceedings of ISP RAS

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Using Received Signal Strength Indicator (RSSI) values to detect human presence is a well-known Wi-Fi sensing technique. In this paper, an overview of existing algorithms solving the problem is considered. Two new techniques based on the discrete Kolmogorov-Wiener filter and the gated recurrent unit neural network are proposed. Human detection experiment results are presented along with algorithms' accuracy analysis.

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Development of an adaptive device-free human detection system for residential lighting load control

Cited by 7 publications

References 15 publications

Development of an indoor corridor localization system based on a WCL method with corridor area selection and distance compensation

Development of an indoor corridor localization system based on a WCL method with corridor area selection and distance compensation

Measurement and Calibration of EMF: A Study Using Phone and GBDT for Mobile Communication Signals

Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks

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