Monitoring Of Noise Levels Research Articles

A Nanoparticle-Based Artificial Ear for Personalized Classification of Emotions in the Human Voice Using Deep Learning.

Artificial intelligence and human-computer interaction advances demand bioinspired sensing modalities capable of comprehending human affective states and speech. However, endowing skin-like interfaces with such intricate perception abilities remains challenging. Here, we have developed a flexible piezoresistive artificial ear (AE) sensor based on gold nanoparticles, which can convert sound signals into electrical signals through changes in resistance. By testing the sensor's performance at both frequency and sound pressure level (SPL), the AE has a frequency response range of 20 Hz to 12 kHz and can sense sound signals from up to 5 m away at a frequency of 1 kHz and an SPL of 126 dB. Furthermore, through deep learning, the device achieves up to 96.9% and 95.0% accuracy in classification and recognition applications for seven emotional and eight urban environmental noises, respectively. Hence, on one hand, our device can monitor the patient's emotional state by their speech, such as sudden yelling and screaming, which can help healthcare workers understand patients' condition in time. On the other hand, the device could also be used for real-time monitoring of noise levels in aircraft, ships, factories, and other high-decibel equipment and environments.

Studying the factors that affect urban road noise-case study: El-Tahrir Street, Al-Dokki Cairo, Egypt.

Expanding road networks to accommodate various activities has significantly increased urban noise pollution, adversely affecting human health and quality of life. Numerous factors influence the noise level in urban areas, including road characteristics, traffic characteristics, surrounding buildings, and weather conditions. While previous studies have considered many of these factors individually, this study aims to integrate all relevant variables to comprehensively monitor and analyze their combined effects on noise levels. The objective is to determine the most influential factors that could be incorporated into effective noise reduction strategies. This research focuses on Cairo, one of the most densely populated cities in the world, where high noise levels are a persistent issue. A detailed case study of Tahrir Street in Dokki, Cairo, provides the basis for this investigation. One of the most crowded areas is El-Tahrir Street in Al-Dokki, which was selected as a case study in this research. This area experiences high traffic volume, with up to 1700 vehicles passing through within a 15-min interval. This significant traffic volume is the primary driver of the elevated noise levels in the area. Traffic and noise level monitoring was conducted using a field survey using the sound level meter.Consequently, a statistical analysis was conducted to investigate the correlation between different factors and the noise level and determine the most influential factors. The study revealed that traffic volume and congestion are the most significant factors influencing noise levels on Tahrir Street, exhibiting strong positive correlations (R = 0.38). Additionally, the study found an inverse relationship between vehicle speed and noise level due to high traffic volumes and identified that building characteristics and wind direction also play roles, albeit to a lesser extent.

Design of a Website-Based Realtime Noise Monitoring System in the Work Environment as a Support for Occupational Health and Safety (OHS) Data

The level of noise in the work environment is one of the factors that affect workers' performance. Research on noise level monitoring tools has been realized using a GY Max 4466 sound sensor with a website-based ESP Wroom 32 microcontroller. This study aims to determine the noise level in the work environment and to monitor noise levels based on a website to support occupational health and safety data. Data was collected by sound detection in the PDAM Way Rilau Bandar Lampung pump room from 08.00-12.00 WIB. The results showed that the system functioned well, indicated by the average accuracy of the four sensors of 97.07% and the average error value of 2.93%. The noise level data generated from the PDAM Way Rilau pump room is classified as high or dangerous because it has exceeded the noise threshold (NAV) value of 70 dB. The system used on the website is localhost access on a computer that can be monitored in the work environment as supporting data for occupational health and safety (K3).

Impact of occupational noise exposure on the hearing level in hospital staffs: a longitudinal study.

The study aimed to evaluate the impact of occupational noise on hearing loss among healthcare workers using audiometry. A longitudinal study was conducted with a six-month follow-up period in a hospital with 21 participants, divided into high-noise-exposure (HNE) and low-noise-exposure (LNE) groups. Mean noise levels were higher in the HNE group (70.4 ± 4.5 dBA), and hearing loss was measured using pure-tone audiometry at baseline and follow-up. The HNE group had significantly higher mean threshold levels at frequencies of 0.25kHz, 0.5kHz, 4.0kHz, and an average of 0.5, 1, 2, and 4kHz (all p-values < 0.05) after the follow-up period. After adjusting for confounding factors, the HNE group had significantly higher hearing loss levels at 0.25kHz, 0.5kHz, and average frequencies of 0.5, 1, 2, and 4kHz compared to the LNE group at the second measurement. Occupational noise levels above 65 dBA over six months were found to cause significant threshold changes at frequencies of 0.25kHz, 0.5kHz, and an average of 0.5-4.0kHz. This study highlights the risk of noise-induced hearing loss among healthcare workers and emphasizes the importance of implementing effective hearing conservation programs in the workplace. Regular monitoring and assessment of noise levels and hearing ability, along with proper use of personal protective equipment, are crucial steps in mitigating the impact of occupational noise exposure on the hearing health of healthcare workers.

Modelling of Animal Activity, Illuminance, and Noise on a Weaned Piglet Farm.

Measuring animal activity and its evolution in real time is useful for animal welfare assessment. In addition, illuminance and noise level are two factors that can improve our understanding of animal activity. This study aims to establish relationships between animal activity as measured by passive infrared sensors, and both illuminance and noise level on a conventional weaned piglet farm. First, regression models were applied, and then cosine models with three harmonics were developed using least squares with a Generalized Reduced Gradient Nonlinear method. Finally, all the models were validated. Linear models showed positive correlations, with values between 0.40 and 0.56. Cosine models drew clear patterns of daily animal activity, illuminance and noise level with two peaks, one in the morning and one in the afternoon, coinciding with human activity inside the building, with a preference for inactivity at night-time and around midday. Cosine model fitting revealed strong correlations, both in the measurement and validation periods, for animal activity (R = 0.97 and 0.92), illuminance (R = 0.95 and 0.91) and noise level (R = 0.99 and 0.92). The developed models could be easily implemented in animal welfare monitoring systems and could provide useful information about animal activity through continuous monitoring of illuminance or noise levels.

Remote Binaural System (RBS) for Noise Acoustic Monitoring

The recent emergence of advanced information technologies such as cloud computing, artificial intelligence, and data science has improved and optimized various processes in acoustics with potential real-world applications. Noise monitoring tasks on large terrains can be captured using an array of sound level meters. However, current monitoring systems only rely on the knowledge of a singular measured value related to the acoustic energy of the captured signal, leaving aside spatial aspects that complement the perception of noise by the human being. This project presents a system that performs binaural measurements according to subjective human perception. The acoustic characterization in an anechoic chamber is presented, as well as acoustic indicators obtained in the field initially for a short period of time. The main contribution of this work is the construction of a binaural prototype that resembles the human head and which transmits and processes acoustical data on the cloud. The above allows noise level monitoring via binaural hearing rather than a singular capturing device. Likewise, it can be highlighted that the system allows for obtaining spatial acoustic indicators based on the interaural cross-correlation function (IACF), as well as detecting the location of the source on the azimuthal plane.

Noise Pollution Control using Internet of Things (IoT) solutions

At present, noise is one of the main environmental pollutants that even government agencies are paying attention to find solutions for its control. Noise pollution traditional methods are based on expensive electronic devices—limited to constant monitoring in real-time. In recent years, (IoT), the internet of things diverse strategies, has been proposed to tackle this issue by offering low-cost sensors, capturing and storing real-time data for better decision-making processes. This article presents the results from an exploratory literature revision regarding Noise Pollution solution proposals based on IoT. in 17 articles indexed in a high-impact database with four research questions about the proposed layers, cover for the control of environmental noise, technological elements, and current limitations and gaps in the problem of environmental noise, defining an OiT system of four layers to define the functionalities of monitoring and analysis of noise levels, the review process established stages such as the identification of critical terms, location of literature, evaluating and selecting literature, organizing and finally summarizing the literature review.

ASSESSMENT OF ROAD TRAFFIC NOISE IN SELECTED URBAN RESIDENTIAL AND CONSTRUCTION AREAS

The work presented in this paper includes a field investigation of road traffic noise between residential and construction areas in a selected urban area. The aim of this study was to assess the level of noise pollution from road traffic noise in Seri Kembangan, Selangor. Therefore, this study included measurements of traffic noise level, evaluation of the percentage traffic volume between residential and construction areas; and identification of the correlation between traffic volume and traffic noise level. An EXTECH 407764 sound level meter was used to take noise level measurements for 1 hour and 30 minutes in one-minute intervals at both study sites. The parameter collected in the noise level monitoring was average noise level (LAeq). The traffic volume study was conducted using manual counts for 30 minutes. Four types of vehicles were counted, namely cars, vans, motorcycles, and heavy vehicles. Based on statistical analysis, it can be concluded that both sites had high traffic noise levels which exceeded the maximum permissible limit of 60 dBA during daytime, according to Malaysian guidelines, due to several factors. The findings show that road infrastructure such as noise barriers need to be further implemented, especially in residential areas. Mitigation of noise pollution must be further carried out by contractors. Additionally, further investigations need to be conducted by the relevant authorities to reduce the level of noise which may affect the quality of life for the communities in the area.

A Smartphone-Enabled IoT System for Vibration and Noise Monitoring of Rail Transit

With the development of the urban rail transit system, the ride comfort of trains in operation has been emphasized by passengers and railroad operators alike. The monitoring of interior vibration and noise levels of trains provides an efficient way to guarantee ride comfort. Traditional monitoring equipment has numerous disadvantages, such as high cost, poor mobility, and lack of real-time evaluation functions. To solve these problems, this study explored the utilization of smartphones to measure vibration and noise and diagnose human comfort levels. A smartphone application has been developed based on the Internet of Things (IoT) concept. The smartphone device not only realizes data sensing, visualization, and transmission, but also fulfills edge-computing functions to process sensing data and evaluate vibration and noise impact in real time. The design principle and major components of the developed application are elaborated. In situ experiments were conducted on the Hong Kong Mass Transit Railway, which provides valuable experiences for applying IoT monitoring technology in the rail transit systems and enables the realization of citizen sensing in the future.

Objective and subjective analysis of the acoustic performance of a ZEB test-building

The paper describes an experimentation campaign, including both objective and subjective analysis, carried out in a Zero-Energy full-scale test building and aiming at analysing the acoustic performance of the construction and the acoustic comfort of the rooms. The objective analysis consists of sound insulation measurements of facades and partitions, noise level measurements of service equipment and environmental noise level monitoring. The subjective analysis is based on a survey carried out on 100 participants to collect the answers about their evaluation of the acoustic quality in two different test rooms. The outcomes of the questionnaire were compared to the outcomes of the measurements in order to find a relationship between the subjective and objective data.

A comprehensive experimental study of the influence of temperature on urban road traffic noise under real-world conditions

The effect of road traffic noise in urban environments is an issue of social and scientific interest, due to its public health and economic impacts. Scientific literature showed a decrease in the level of tyre/road noise generated as temperature increases, but usually under standardised traffic conditions in non-urban environments. Based on a wide network for the hourly monitoring of road traffic flow, air temperature and noise levels across the city of Madrid (Spain), this work proposes and applies a new experimental methodology for studying the dependence of urban road traffic noise on temperature. This study was conducted under real-world traffic conditions involving a wide variability in urban configurations and in the type and state of preservation of vehicles, tires and pavements. From the analysis of data for a whole year, a time interval was identified (from Tuesday to Thursday and between 8 a.m. and 8 p.m.) in which the variability in road traffic flow for the whole city of Madrid was stable enough to allow for a linear regression study between temperature and noise levels from urban road traffic. The relationships found were highly significant (p ≤ 0.001) for data from all the noise monitoring stations, with values of higher than 20% and up to 42% for the explanation of the variability in the measured noise levels by temperature at most of the measurement points. The values of the slope coefficients at the noise monitoring stations ranged from −0.036 to −0.125 dB/°C, with an average value of −0.090 ± 0.011 dB/°C. These results are within the range of values reported in the scientific literature for experimental tests conducted under conditions of controlled or free-flowing traffic.

A proposed method for measuring noise from wind farms for the purpose of determining compliance with applicable limits and the comparison of results to ISO 9613-2 predictions

This paper describes methods for the measurement of noise emissions from utility-scale wind farms and the analysis of the resulting data for determining compliance with noise level limits and standards. The methods call for primarily unattended monitoring of noise levels, wind speeds, and turbine operating conditions over many weeks, in some cases months, in order to capture the recurring maximum turbine-only noise level at a receptor (e.g., residence). This condition occurs when the nearest turbines are producing full acoustic output, while noise from background sources is very low (particularly that from wind). This paper will present the results of noise compliance measurement studies applying these methods conducted by Hankard Environmental, encompassing over 13 projects and over 50 measurement locations in the Northeast, Midwest, and Plains regions of the United States (U.S.) The results of these measurements are used to assess the accuracy of the ISO 9613-2:1996 method in predicting wind turbine noise levels on both an overall A-weighted and octave band basis. These results can be used by wind energy developers to accurately design projects to meet applicable limits and standards and gives all parties in the permitting process a greater degree of confidence in predictions and compliance measurement results.

Effects of Intraoperative Auditory Stimulation on Pain and Agitation on Awakening After Pediatric Adenotonsillectomy

Severe pain on awakening (POA) and emergence delirium (ED) are common following pediatric adenotonsillectomy. Effective preventive interventions are lacking. To determine the effects of intraoperative auditory stimulation on reduction of POA and ED after pediatric adenotonsillectomy. Single-center, double-blinded, 4-armed, randomized clinical trial of children undergoing adenotonsillectomy from March 2018 to May 2019 at a tertiary care pediatric referral center. Children were randomized to 1 of the following groups: auditory stimulation with music, auditory stimulation with noise, ambient noise insulation with masking earplugs, and a control group receiving no intervention. Ear inserts were placed in the operating room once general anesthesia was administered. Stimulation parameters were based on the preoperative audiological evaluation and the appropriate fitting of the transduction system, including ambient noise level monitoring. The primary outcome was POA levels measured on 10-point scales according to age-appropriate validated tools. The secondary outcome was ED levels assessed according to the Pediatric Anesthesia Emergence Delirium 20-point scale. A total of 104 consecutive healthy children (median [interquartile range] age at surgery, 5.0 [3.8-6.4] years) were included in the analysis. Music had a large effect size on POA (0.63; 98% CI, 0.43-0.84) and a medium effect size on ED (0.47; 98% CI, 0.21-0.75), while noise had a medium effect size on POA (0.47; 98% CI, 0.22-0.73) and a large effect size on ED (0.63; 98% CI, 0.44-0.85) compared with controls. The earplugs group showed a small effect size on POA and ED. Considering a clinically meaningful threshold of greater than 4 for POA and 10 or greater for ED at dichotomized analysis, a large effect size was achieved by music (1.39; odds ratio [OR], 0.08; 98% CI, 0.02-0.29; and 0.84; OR, 0.22; 98% CI, 0.06-0.75, respectively) and noise (0.97; OR, 0.17; 98% CI, 0.05-0.6; and 1.48; OR, 0.07; 98% CI, 0.02-0.26, respectively), while earplugs resulted in a small effect size. In this randomized clinical trial, children undergoing adenotonsillectomy who received intraoperative auditory stimulation demonstrated a clinically meaningful decrease in POA and ED in the immediate postoperative period. Further research is needed to assess whether intraoperative auditory stimulation may decrease POA and ED in children undergoing other types of surgical procedures. ClinicalTrials.gov Identifier: NCT04112979.

Design of low-cost wireless noise monitoring sensor unit based on IoT concept

The recent expansion of wireless sensor networks (WSN) in urban cities has led to possibility of generation of large amounts of information data from the environmental monitoring systems among which one of the most concerning is the excessive urban noise pollution. As opposed to the conventional noise mapping procedures that involve costly and time-consuming measurement process with a traditional high-priced noise level meter, the low-cost wireless sensor networks provide a method for achieving data collection and analysis with a higher level of granularity. Тhis paper presents a wireless noise sensor unit design for continuous environmental noise level monitoring as a framework for the realization of the Internet of Things (IoT) and „Smart city” concept. The concept involves the complete noise data information system, from sensor structure to data visualization and data analysis. The overall design, characteristics and performance of the sensing system for continuous measuring urban noise pollution is discussed.

The sound of the future: listening as data and the politics of soundscape assessment

ABSTRACT This sonic ecology of cities has been highlighted recently by the effects of the global pandemic: fewer cars and people on the road are letting quieter layers of the soundscape to come forward, signalling unequivocally that the urban soundscape is a direct result of anthropocenic activity. This is a time, then, to listen and reflect, and perhaps heed new models for thinking of urban sound. One barrier to such a process is the persistent and entrenched disconnect between soundscape literature, public engagement with sound, and urban planning. By critically surveying literature on soundscape assessment as it intersects with cultural sound studies and acoustic ecology, this paper traces a number of important disciplinary ontologies of everyday listening in cities, ranging from attempts to standardise evaluation metrics and classification of soundscapes, to the emergence of subjective listening studies. More recently a ‘digital commons’ approach to civic engagement has led to crowdsourcing sonic experiences, soundmapping, and, at the infrastructural level – networked monitoring of noise levels. These rhetorical and practical developments fit within important contemporary conversations in critical data and algorithm studies and as such require a critical excavation of underlying values and conceptions of listening.

Noise Exposure Levels in Basic School Environments in a City in Ghana

Basic schools that are located in heavily populated residential and commercial areas in Ghana are exposed to environmental noise that can have detrimental effects on the academic attainments of children. Limited studies have been conducted on noise level in basic schools to date in Ghana. The objective of the study was to assess noise levels in and around learning spaces in basic schools in Ghana with a focus on Kumasi. A survey employing the use of interviews and an empirical monitoring of noise levels in and around learning spaces in four selected basic schools were adopted. The study revealed that mean outdoor and indoor noise levels exceed the World Health Organisation permissible limits by 30 - 40 percent and 90 - 107 percent respectively for schools in the commercial zones and schools that are located near highways. The school that is sited in an educational environment with a setback from the highway attained mean noise levels ranging from 1.2 percent below to 3.7 percent above the permissible limits for outdoor and between 64 - 105 percent for indoor. The outcome of the study is expected to engender the design of environmental noise resilient buildings to facilitate teaching and learning in basic schools in Ghana.

Comparison of wind turbine-only noise levels measured at operating wind farms in the United States to noise levels predicted using ISO 9613-2:1996

This paper describes robust and effective methods for the measurement of noise emissions from utility-scale wind farms and the analysis of the resulting data for determining compliance with noise level limits and standards. The methods call for primarily unattended monitoring of noise levels, wind speeds, and turbine operating conditions over many weeks, in some cases months, in order to capture the recurring maximum wind turbine-only noise level at a receptor (i.e., residence). This condition occurs when the nearest turbines are producing full acoustic output while noise from background sources is very low (particularly that from wind). Presented are the results of noise compliance measurement studies applying these methods conducted by Hankard Environmental, encompassing eight projects and 35 measurement locations in the Northeast, Midwest, and Plains regions of the United States (U.S.) The results of these measurements are used to assess the accuracy of the ISO 9613-2:1996 method in predicting wind turbine noise levels at residences. These results can be used by wind energy developers to accurately design projects to meet applicable limits and standards and give all parties involved in the permitting process a greater degree of confidence in predictions and greater clarity during compliance measurements.

COLLABORATIVE NOISE MAPPING USING SMARTPHONE

Abstract. Noise pollution is considered to be one of the most prevalent environmental challenges affecting human health. Noise pollution is increasing in cities needing techniques to monitor and predict the noise. The monitoring of traffic noise levels in different parts of the cities at different times has become very difficult due to logistic constraints. It is thus required to measure the noise levels at certain strategic locations, such as, near the noise sources (e.g., roads), and then to utilize it to predict the noise levels at surrounding locations. The challenge of monitoring the noise near several road crossings in a city can be reduced using a smartphone-based noise monitoring technique. However, the prediction of noise levels and showcase it as maps require terrain data, noise data, and noise prediction models. The requirement of terrain data can be met using open-source terrain data, from which various terrain parameters can be extracted and integrated with a standard prediction model on the web platform to predict the noise map for an area. Smartphone-based noise monitoring and its subsequent mapping can be a very popular and effective option, which uses a crowdsourcing approach. The entire methodology is tried to be applied over Lucknow city in India. Noise levels are monitored at three different slots, daily, over 14 road crossings using the smartphone-based app. Further, collected noise levels were calibrated against standard noise meter to ascertain accurate noise levels for these locations. Thereafter, three categories of noise environments are chosen from it and mapped using open-source satellite images and standard noise models, over the web on the GIS platform. The predicted noise levels on the maps were verified with the recorded noise data from similar locations using standard noise meter. For these three crossings at different times the predictions are found to be accurate within ±4.5 dB.

SpaceMaze: incentivizing correct mobile crowdsourced sensing behaviour with a sensified minigame

ABSTRACT Modern mobile phones are equipped with many sensors, which can increasingly be used to sense various environmental phenomena. In particular, mobile sensing has enabled crowdsourced data collection at an unprecedented scale. However, as laypersons are involved in this, concerns regarding the data quality arise. This work explores the gamification of smartphone-based measurement processes in practice by embedding a sensing task into a mobile minigame. The underlying idea is – rather than to educate the user on how to correctly perform a measurement task – to opportunistically execute the measurement in the background once the smartphone is in a suitable context. To this end, this paper presents the design and evaluation of SpaceMaze, a smartphone game with the goal of minimising user error by introducing appropriate game mechanics to influence the phone context, using the example of mobile noise level monitoring. A large user study that compares SpaceMaze to two non-gamified apps for noise level monitoring (N = 360 in total) shows that SpaceMaze can successfully reduce user errors when compared to simple non-gamified ambient noise level monitoring applications and that the minigame is generally perceived as being enjoyable. Solutions for remaining problems, such as noise generated by the players, are discussed.

LEVELS, TRENDS AND EXPOSURE DOSES OF NOISE EMITTED BY SMALL SCALE ENTERPRISES IN ABEOKUTA, SOUTH-WESTERN NIGERIA

Monitoring of noise levels and their impact are common in large scale and corporate industrial establishments while the small scale industries have not received sufficient attention. Consequently, the present study examined the levels and pattern of noise emission from small-scale enterprises that are generally ignored from compliance monitoring of the relevant agencies. The study utilises the results of noise emission quantification, determination of safe distance to the selected small-scale enterprises and impact on human as input for noise policy formulation. Three types of small-scale enterprises sampled from seventy-five (75) sites in Abeokuta were selected for noise measurement using a portable noise meter. Questionnaire and field observation were employed to assess the impact of noise on machine operators and their apprentices. Mean noise emission from the aluminum slitting machines ranged from 103.9 – 118.4 d(BA), iron welding machines; 97.0 – 108.8 d(BA) and food grinding machines; 91.6 to 108.2 d(BA). Daily Noise Dose (DND) from these three types of machine workshops were 800 – 19230% (aluminum slitter), 200 – 2400% (iron welder), and 100 – 3305% (food grinder). Time Weighted Average (TWA) for 8 hours noise exposure values were 94.0 – 107.8, 88.0 – 98.8 and 85.0 – 100.2 respectively. The spatial dimension of noise emission from the studied machines showed that acceptable levels were obtained at 20 meters from the machines sites. As predictors of variations in noise emission, the age of the machines explained 8.3 – 13.6%, 17.2 – 17.8% and 29.1 – 55.4% of noise emitted by food grinders, aluminum slitters and iron welders. The capacities of the studied machines predicted 7.9 – 13.5%, 18.4 – 30.5 and 43.9 – 56.3% of the noise emitted by iron welders, aluminum slitter and food grinders respectively. While the noise levels at the sites of the machines were significantly higher than the permissible limit, 25% of the workers were exposed for upwards of 10 hours daily and 30% for more than five years. The array of health problems; stress, dizziness, tinnitus, sleep disturbance and speech interference, experienced by the machines operators may not be unconnected to their non-use of Personal Protective Equipment (PPE) to minimize noise hazard. Policy formulation for public protection from noise pollution should prescribe limit for small scale enterprises, enforce noise level compliance, monitor wearing of appropriate PPE by machine operators and maintained a minimum of 20 meters between the sites of these machines and other human activities. &#x0D; &#x0D; &#x0D;