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This paper presents a magnetic matching-aided indoor localization system based on a waist-mounted self-contained sensor array. Our purpose is to localize and track the elderly in nursing homes through the proposed wearable device to ensure their safety. The device consists of a low-cost 9-axis self-contained sensor array, a microcontroller, and a WiFi transmission module. This system uses the step length and heading-based pedestrian dead reckoning (PDR) framework as the backbone to estimate the user’s position using the averaged inertial data from the sensor array. A magnetic fingerprint matching (MFM) algorithm is introduced to constrain the drift of the PDR system. Meanwhile, we construct a single-step-based hybrid magnetic fingerprint model to improve the low discernibility of the magnetic field. Finally, we propose an augmented particle filter to fuse the PDR and the MFM algorithms to enhance the system performance further. Experimental results show that 95% of the positioning error after fusion is about 1.47 m, which is 99.3% higher than that of PDR, and the average positioning error after fusion is 0.55 m, which is 61.3% higher than that of PDR. Experimental results have successfully validated the effectiveness and high performance of the proposed magnetic matching-aided wearable indoor localization system.

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Monotone noises at high decibels have been identified as a main cause of degradation in people’s mental health. This paper proposes a directional monotone noise reduction method to suppress spatially localized single-frequency noises. The system is designed based on a feedforward active noise control (ANC) structure by implementing filtered-x least mean square (FxLMS) algorithms. Compared with traditional ANC methods, our system employs a parametric array loudspeaker (PAL) as the active noise-canceling source with high audio directivity for directional noise suppression. The system monitors the ambient monotone noise and implements the ANC algorithm in real-time through a software-based platform operating on a generic personal computer (PC). Experimental measurements demonstrate an 8dB reduction of different monotone noises at a 260cm distance from the active source. Compared with traditional ANC methods with a voice coil loudspeaker (VCL) as the noise-canceling source, our PAL-based system achieves similar noise suppression performance with a 5.8 times improvement in the source-to-target distance and 64% reduction in the −3dB audio main lobe beam width. The results prove the advantage of introducing PALs as active-noise-canceling sources for monotone noise suppression with a cost-effective enhancement in operating distances and noise control directivities.