Search Results (191)

This work presents the experimental and numerical investigation of a novel acoustic metamaterial based on sustainable and biodegradable components: cork membranes and honeycomb cores made from treated aramid paper. The design exploits the principle of localized resonance induced by tensioned membranes coupled with subwavelength cavities, aiming to achieve high sound absorption at low (250–500 Hz) and mid frequencies (500–1400 Hz) with minimal thickness and environmental impact. Three configurations were analyzed, varying the number of membranes (one, two, and three) while keeping a constant core structure composed of three stacked honeycomb layers. Acoustic performance was measured using an impedance tube (Kundt’s tube), focusing on the normal-incidence sound absorption coefficient in the frequency range of 250–1400 Hz. The results demonstrate that increasing the number of membranes introduces multiple resonances and broadens the effective absorption bandwidth. Numerical simulations were performed to predict pressure field distributions. The numerical model showed good agreement with the experimental data, validating the underlying physical model of coupled mass–spring resonators. The proposed metamaterial offers a low-cost, modular, and fully recyclable solution for indoor sound control, combining acoustic performance and environmental sustainability. These findings offer promising perspectives for the application of bio-based metamaterials in architecture and eco-design. Further developments will address durability, high-frequency absorption, and integration in hybrid soundproofing systems. Full article

Indoor soundscape is a relatively new and developing field compared to urban soundscape in practice. To address this gap, this study aims to identify the key influencing factors as a first step of the indoor soundscape intervention approach. The study employed a two-phase methodology. Phase one involved a Systematic Review (SR) of the literature, conducted through the PRISMA 2020 guidelines, to collate data on the influencing factors and intervention criteria of the indoor soundscape approach. Searching was conducted using two databases, Web of Science and Scopus. As a result of the search, a total of 29 studies were included in the review. The review included studies addressing the soundscape influencing factors and theoretical frameworks. Studies that did not address these criteria were excluded. Phase two comprised the application of the Grounded Theory (GT) coding process to organize, categorize, and merge the data collected in phase one. As a result of the coding process, three levels of categories were achieved; L1: key concept, L2: overarching category, L3: core category. Four core categories were identified as ‘Sound’, ‘People’, ‘Building’, and ‘Environment’ by proposing the Indoor Soundscape Intervention (ISI) criteria. The repeatable and updatable nature of the proposed method allows it to be adapted to further studies and different contexts/cases. Full article

Ensuring a sustainable and healthy human environment in university dormitories is essential for students’ learning, living, and overall health and well-being. To address this need, we carried out a series of systematic field measurements of the noise levels at 30 dormitories in three representative major urban universities in a major provincial capital city in China and designed and implemented a comprehensive questionnaire and surveyed 1005 students about their perceptions of their acoustic environment. We proposed and applied a sustainability–health-oriented, multidimensional assessment framework to assess the acoustic environment of the dormitories and student responses to natural sound, technological sounds, and human-made sounds. Using the Structural Equation Modeling (SEM) approach combined with the field measurements and student surveys, we identified three categories and six factors on student health and well-being for assessing the acoustic environment of university dormitories. The field data indicated that noise levels at most of the measurement points exceeded the recommended or regulatory thresholds. Higher noise impacts were observed in early mornings and evenings, primarily due to traffic noise and indoor activities. Natural sounds (e.g., wind, birdsong, water flow) were highly valued by students for their positive effect on the students’ pleasantness and satisfaction. Conversely, human and technological sounds (traffic noise, construction noise, and indoor noise from student activities) were deemed highly disturbing. Gender differences were evident in the assessment of the acoustic environment, with male students generally reporting higher levels of the pleasantness and preference for natural sounds compared to female students. Educational backgrounds showed no significant influence on sound perceptions. The findings highlight the need for providing actionable guidelines for dormitory ecological design, such as integrating vertical greening in dormitory design, water features, and biodiversity planting to introduce natural soundscapes, in parallel with developing campus activity standards and lifestyle during noise-sensitive periods. The multidimensional assessment framework will drive a sustainable human–ecology–sound symbiosis in university dormitories, and the category and factor scales to be employed and actions to improve the level of student health and well-being, thus, providing a reference for both research and practice for sustainable cities and communities. Full article

The COVID-19 pandemic’s rapid shift to working from home has fundamentally challenged residential acoustic design, which traditionally prioritises rest and relaxation rather than sustained concentration. However, a clear gap exists in understanding how acoustic needs and the subjective evaluation of soundscape appropriateness (SA) differ between these conflicting activities within the same domestic space. Addressing this gap, this study reveals critical differences in how people experience and evaluate home soundscapes during work versus relaxation activities in the same residential spaces. Through an online survey of 247 Chinese participants during lockdown, we assessed soundscape perception attributes, the perceived saliencies of various sound types, and soundscape appropriateness (SA) ratings while working and relaxing at home. Our findings demonstrate that working at home creates a more demanding acoustic context: participants perceived indoor soundscapes as significantly less comfortable and less full of content when working compared to relaxing (p < 0.001), with natural sounds becoming less noticeable (−13.3%) and distracting household sounds more prominent (+7.5%). Structural equation modelling revealed distinct influence mechanisms: while comfort significantly mediates SA enhancement in both activities, the effect is stronger during relaxation (R² = 0.18). Critically, outdoor man-made noise, building-service noise, and neighbour sounds all negatively impact SA during work, with neighbour sounds showing the largest detrimental effect (total effect size = −0.17), whereas only neighbour sounds and outdoor man-made noise significantly disrupt relaxation activities. Additionally, natural sounds act as a positive factor during relaxation. These results expose a fundamental mismatch: existing residential acoustic environments, designed primarily for rest, fail to support the cognitive demands of work activities. This study provides evidence-based insights for acoustic design interventions, emphasising the need for activity-specific soundscape considerations in residential spaces. As hybrid work arrangements become the norm post-pandemic, our findings highlight the urgency of reimagining residential acoustic design to accommodate both focused work and restorative relaxation within the same home. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

Sound event localization and detection (SELD) is a fundamental task in spatial audio processing that involves identifying both the type and location of sound events in acoustic scenes. Current SELD models often struggle with low signal-to-noise ratios (SNRs) and high reverberation. This article addresses SELD by reformulating direction of arrival (DOA) estimation as a multi-class classification task, leveraging deep convolutional recurrent neural networks (CRNNs). We propose and evaluate two modified architectures: M-DOAnet, an optimized version of DOAnet for localization and tracking, and M-SELDnet, a modified version of SELDnet, which has been designed for joint SELD. Both modified models were rigorously evaluated on the STARSS23 dataset, which comprises 13-class, real-world indoor scenes totaling over 7 h of audio, using spectrograms and acoustic intensity maps from first-order Ambisonics (FOA) signals. M-DOAnet achieved exceptional localization (6.00° DOA error, 72.8% F1-score) and perfect tracking (100% MOTA with zero identity switches). It also demonstrated high computational efficiency, training in 4.5 h (164 s/epoch). In contrast, M-SELDnet delivered strong overall SELD performance (0.32 rad DOA error, 0.75 F1-score, 0.38 error rate, 0.20 SELD score), but with significantly higher resource demands, training in 45 h (1620 s/epoch). Our findings underscore a clear trade-off between model specialization and multifunctionality, providing practical insights for designing SELD systems in real-time and computationally constrained environments. Full article

As a fundamental technology in environmental perception, sound source localization (SSL) plays a critical role in public safety, marine exploration, and smart home systems. However, traditional methods such as beamforming and time-delay estimation rely on manually designed physical models and idealized assumptions, which struggle to meet practical demands in dynamic and complex scenarios. Recent advancements in deep learning have revolutionized SSL by leveraging its end-to-end feature adaptability, cross-scenario generalization capabilities, and data-driven modeling, significantly enhancing localization robustness and accuracy in challenging environments. This review systematically examines the progress of deep learning-based SSL across three critical domains: marine environments, indoor reverberant spaces, and unmanned aerial vehicle (UAV) monitoring. In marine scenarios, complex-valued convolutional networks combined with adversarial transfer learning mitigate environmental mismatch and multipath interference through phase information fusion and domain adaptation strategies. For indoor high-reverberation conditions, attention mechanisms and multimodal fusion architectures achieve precise localization under low signal-to-noise ratios by adaptively weighting critical acoustic features. In UAV surveillance, lightweight models integrated with spatiotemporal Transformers address dynamic modeling of non-stationary noise spectra and edge computing efficiency constraints. Despite these advancements, current approaches face three core challenges: the insufficient integration of physical principles, prohibitive data annotation costs, and the trade-off between real-time performance and accuracy. Future research should prioritize physics-informed modeling to embed acoustic propagation mechanisms, unsupervised domain adaptation to reduce reliance on labeled data, and sensor-algorithm co-design to optimize hardware-software synergy. These directions aim to propel SSL toward intelligent systems characterized by high precision, strong robustness, and low power consumption. This work provides both theoretical foundations and technical references for algorithm selection and practical implementation in complex real-world scenarios. Full article

This study examines the short-term impact of an “eco-feedback” strategy, based on an awareness-raising information campaign and an experimental campaign, on indoor environmental quality (IEQ) parameters and sleep quality in Italian bedrooms. Forty-one participants from Cassino, Italy, monitored the IEQ in their bedroom environments during the winter and spring seasons and assessed their sleep quality using the Groningen Sleep Quality Scale before and after receiving awareness-raising information. The experimental analysis revealed that, even if the IEQ and self-reported sleep quality before receiving the information were not representative of good sleep conditions (e.g., 94% of the volunteers slept in bedrooms with a median indoor CO₂ concentration >800 ppm, the equivalent continuous sound pressure level was always >30 dB, and the self-reported sleep quality conditions were characteristic of disrupted sleep or intermediate sleep disturbance), the subjects were not able to obtain significant changes in IEQ parameters after the information campaign and that, consequently, no noticeable changes in sleep quality were obtained as well. The limited effectiveness of the eco-feedback strategy adopted in this study can be attributed to the fact that the proposed approach only led to behavioral changes characterized by a limited effect on the indoor environmental quality. This was mostly due to the period under investigation: as an example, the low nighttime outdoor temperatures did not allow for an improvement in the building ventilation during the night. Full article

Sound source localization (SSL) equips service robots with the ability to perceive sound similarly to humans, which is particularly valuable in complex, dark indoor environments where vision-based systems may not work. From a data collection perspective, increasing the number of microphones generally improves SSL performance. However, a large microphone array such as a 16-microphone array configuration may occupy significant space on a robot. To address this, we propose a novel framework that uses a structure of four planar moving microphones to emulate the performance of a 16-microphone array, thereby saving space. Because of its unique design, this structure can dynamically form various spatial patterns, enabling 3D SSL, including estimation of angle, distance, and height. For experimental comparison, we also constructed a circular 6-microphone array and a planar 4 × 4 microphone array, both capable of rotation to ensure fairness. Three SSL algorithms were applied across all configurations. Experiments were conducted in a standard classroom environment, and the results show that the proposed framework achieves approximately 80–90% accuracy in angular estimation and around 85% accuracy in distance and height estimation, comparable to the performance of the 4 × 4 planar microphone array. Full article

This study investigates the potential of thermally treated olive husk (OH)—a heterogeneous agro-industrial by-product comprising olive stones, pulp, and fibrous residues—as a multifunctional component in lightweight bio-concrete. Uniquely, this work harnesses the intrinsic dual nature of OH as both a fibrous reinforcement and a porous aggregate, without further fractionation, to evaluate its influence on the hygrothermal and mechanical behavior of cementitious composites. While prior studies have often focused selectively on thermal conductivity, this work provides a comprehensive assessment of all major thermal parameters; including diffusivity, effusivity, and specific heat capacity; offering deeper insights into the full thermal behavior of bio-based concretes. OH was incorporated at 0%, 10%, and 20% by weight, and the resulting concretes were subjected to a comprehensive characterization of their thermal, hygric, mechanical, and microstructural properties. Thermal performance metrics included conductivity, specific heat capacity, diffusivity, effusivity, time lag, and predicted energy savings. Hygric behavior was assessed through the moisture buffering value (MBV), while density, porosity, and mechanical strengths were also evaluated. At 20% OH content, thermal conductivity decreased to 0.405 W/m·K (a 72% reduction), thermal diffusivity dropped by 87%, and thermal effusivity reached 554 W·s^0.5/m²·K, collectively enhancing thermal inertia and increasing the time lag by 77% (to 2.32 h). MBVs improved to 2.18 g/m²·%RH, rated as “Excellent” for indoor moisture regulation. Despite the higher porosity, the bio-concrete maintained adequate mechanical integrity, with compressive and flexural strengths of 11.68 MPa and 3.58 MPa, respectively, attributed to the crack-bridging action of the fibrous inclusions. Microstructural analysis (SEM/XRD) revealed improved paste continuity and denser C–S–H formation, attributed to enhanced matrix compatibility following oil removal via thermal pre-treatment. These findings demonstrate the viability of OH as a new bio-based, multifunctional additive for fabricating thermally efficient, hygroscopically active, and structurally sound concretes suitable for sustainable construction. Full article

Asymmetric double-suction centrifugal fans are commonly employed in home kitchens to remove cooking pollutants, and their performance is critical to maintaining a healthy indoor environment. However, inlet condition variations significantly influence the aerodynamic efficiency and noise levels. This study utilizes a combination of performance testing and a large eddy simulation to analyze the impact of different inlet conditions on the performance curve, impeller outlet pressure pulsation, unsteady flow structures, and sound quality of an asymmetric double-suction centrifugal fan. A non-uniform air distribution at the inlet is proposed to enhance the fan’s aerodynamic and noise characteristics. The findings reveal that when the inlet area is reduced to less than 70% of its fully open state, the aerodynamic performance declines with decreasing intake area. The amplitude of the superimposed blade-passing frequency is minimized when only the left inlet is open; the pressure coefficient’s fluctuation amplitude in the time domain reaches 0.4, with sharpness peaking at 3.1. In the optimized design, the maximum deviation in total pressure efficiency is limited to 1.96%, with loudness reduced by four sones and improved sharpness and roughness. These results provide valuable insights into the design and noise reduction of asymmetric double-suction squirrel-cage fans. Full article

Based on the resource conservation requirements of GB/T 50378-2019 “Green Building Evaluation Standard”, this study constructed a BIM–Ecotect collaborative analysis model and proposed a “four-dimensional integration” green performance optimization method. Taking a high-rise office building in Wuhan as an example, a LOD 300-level Revit building information model was established, and a multidisciplinary collaborative analysis was achieved through gbXML data interaction. The lighting simulation results show that the average natural lighting coefficient of the office area facing south is 2.4 (the standard 85%), while in the meeting room area, due to the optimized design of the curtain wall, the average natural lighting coefficient has increased to 2.6 (the standard 92%). In terms of energy-saving renovation, a three-dimensional collaborative design strategy was adopted. Through the optimization of the envelope structure, the cooling load of the air conditioning system was reduced by 25.3%, and the heat load was reduced by 23.6% (the u value of the exterior wall was reduced by 56.3%, the SHGC of the exterior windows was reduced by 42.9%, and the thermal resistance of the roof was increased by 150%). The ventilation optimization adopts the CFD flow field reverse design, adjusting the window opening rate of the exterior windows from 15% to 20% to form a turbulent diffusion effect. Therefore, the air change rate in the office area reached 2.5 times per hour, and the CO₂ concentration decreased by up to 27.1% at most. The innovative adoption of the “composite sound insulation curtain wall” technology in acoustic environment control has increased the indoor noise compliance rate by 27 percentage points (from 65% to 92%). The above research data indicate that digital collaborative design can achieve an overall energy-saving rate of over 20% for buildings, providing a replicable technical path for enhancing the performance of green buildings. Full article

In response to the demand for high-precision positioning within confined or indoor environments, the application of acoustic ranging methods has been widely adopted by numerous engineers. Currently, time-of-flight (TOF)-based acoustic ranging positioning systems face challenges such as the susceptibility of sound velocity to environmental factors and the loss of acoustic signals at both short and long distances, which leads to a reduction in positioning accuracy. This paper addresses these issues by proposing a high-precision confidence interval weighting method for acoustic ranging and further introduces a method for base station deployment and self-optimization positioning within fixed indoor base station scenarios. The method is based on trilateration positioning, establishing criteria for the division of central and boundary areas. It categorizes mobile terminal nodes based on their coordinates from the previous moment, selects distance information from nearby base stations in different modes, and employs weights for decision-making and computation, ultimately yielding two-dimensional positioning coordinates. Experiments demonstrate that the proposed method can effectively enhance the positioning accuracy of acoustic positioning systems compared to traditional four-base station weighted average positioning algorithms. Full article

The indoor climate quality in classrooms at the University of Coimbra, Portugal, was investigated as part of the 3SqAir project, supported by the Interreg SUDOE program. This research focused on two equipped classrooms with different ventilation systems: natural and mechanical ventilation. Both classrooms were continuously monitored for IEQ parameters: thermal comfort, indoor air quality, noise, and lighting during heating and cooling seasons. Air temperature, relative humidity, CO₂ concentration, particulate matter, nitrogen dioxide, volatile organic compounds, formaldehyde, sound pressure level, and illuminance were measured. Outdoor weather conditions were also recorded. The primary focus was on air temperature, CO₂ concentrations, and relative humidity, while air change rates (ACH) were estimated using the Tracer Gas Method. The results showed inadequate thermal conditions in both classrooms, particularly during the heating season. Most weekly mean CO₂ concentrations were within acceptable limits, while ACH were below standard recommendations in four CO₂ decay phases. Simulations of CO₂ decay revealed further air quality gaps in each room. Corrective measures within the 3SqAir project framework were suggested for approval and implementation while monitoring continues. This work represents the first phase in an evolving study towards developing sustainable strategies for improving indoor air quality in classrooms. Full article

The global navigation satellite system (GNSS), using electromagnetic signals, enables continuous positioning throughout the entire surface of the Earth. However, underwater and underground environments significantly restrict the propagation of electromagnetic waves. The sole approach to aid positioning is the utilization of sound signals. Signal blockage in underground and indoor environments demands the accurate location of anchor points for local positioning, which requires previous deployment. Unlike radio waves, the cosmic ray muons are highly reliable natural signal sources for positioning, remaining immune to spoofing and interference. Starting from the standpoint of navigation and positioning, this paper briefly introduces the physical properties of cosmic ray muons and outlines the measurements and positioning principles of muon navigation, including trilateral localization based on the time of flight (TOF) and angular localization based on the angle of arrival (AOA). It subsequently presents the pertinent studies conducted and analyzes the findings. Finally, the challenges of muon navigation are explored from three perspectives: positioning signals, positioning models, and application scenarios. This will offer some new ideas for the domain of localization for further research on muon positioning. Full article