Design and Implementation of Location and Activity Monitoring System Based on LoRa

Lin, Shun‐Yun; Ying, Ziqiang; Zheng, Kan

doi:10.48550/arxiv.1902.01947

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Current research in the domain of LoRa predominantly revolves around harnessing its remote communication capabilities for IoT applications. For instance, Lin et al [15] utilized LoRa links to transmit human activity data monitored by sensors. Petäjäjärvi et al [16] employed LoRaMote, affixed to an individual's arm with a sensor-equipped band (including temperature and pressure sensors), for monitoring the health of human subjects.…”

Section: Related Workmentioning

confidence: 99%

A Long-Range Signal-Based Target Localization Algorithm

Ge,

Zhu,

Sun

et al. 2024

Electronics

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Indoor target localization is pivotal across various applications, encompassing security monitoring, behavioral analysis, and elderly care. This work proposes an advanced target localization algorithm that harnesses antennas endowed with sensing capabilities to capture the phase change in the signal ratio, derived from the signal amplitude. This phase change, indicative of the target’s movement direction, is analyzed alongside the front and rear arrival angle information and signal amplitude characteristics obtained from LoRa signals. The algorithm, through a comprehensive examination of the phase change patterns, amalgamated with arrival angle data and signal amplitude characteristics, effectively estimates the precise location of the target. Experimental validations underscore the algorithm’s efficacy in determining the target’s location during continuous walking activity. Conducted within a 6 m × 12 m open platform, the algorithm achieves an average localization error of 48.5 cm, underscoring its superior performance compared to existing methodologies.

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Section: Related Workmentioning

confidence: 99%

A Long-Range Signal-Based Target Localization Algorithm

Ge,

Zhu,

Sun

et al. 2024

Electronics

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show abstract

“…Initially, LoRa found its niche in enabling the transmission of real-time activity and location data from wearable devices to cloud servers via LoRa gateways [27]. This capability was especially advantageous in scenarios where monitoring devices with sensors needed to operate in remote or outdoor environments, i.e., where traditional communication technologies have struggled due to limited range [28][29][30].…”

Section: Lora Sensing In Harmentioning

confidence: 99%

Enhancing Human Activity Recognition with LoRa Wireless RF Signal Preprocessing and Deep Learning

Nie,

Zou,

Cui

et al. 2024

Electronics

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This paper introduces a novel approach for enhancing human activity recognition through the integration of LoRa wireless RF signal preprocessing and deep learning. We tackle the challenge of extracting features from intricate LoRa signals by scrutinizing the unique propagation process of linearly modulated LoRa signals—a critical aspect for effective feature extraction. Our preprocessing technique involves converting intricate data into real numbers, utilizing Short-Time Fourier Transform (STFT) to generate spectrograms, and incorporating differential signal processing (DSP) techniques to augment activity recognition accuracy. Additionally, we employ frequency-to-image conversion for the purpose of intuitive interpretation. In comprehensive experiments covering activity classification, identity recognition, room identification, and presence detection, our carefully selected deep learning models exhibit outstanding accuracy. Notably, ConvNext attains 96.7% accuracy in activity classification, 97.9% in identity recognition, and 97.3% in room identification. The Vision TF model excels with 98.5% accuracy in presence detection. Through leveraging LoRa signal characteristics and sophisticated preprocessing techniques, our transformative approach significantly enhances feature extraction, ensuring heightened accuracy and reliability in human activity recognition.

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Design and Implementation of Location and Activity Monitoring System Based on LoRa

Cited by 2 publications

References 18 publications

A Long-Range Signal-Based Target Localization Algorithm

A Long-Range Signal-Based Target Localization Algorithm

Enhancing Human Activity Recognition with LoRa Wireless RF Signal Preprocessing and Deep Learning

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