An Efficient System Model for Multicasting Measured Noise Value of Polluting Industries
01 Jan 2017-pp 377-383
TL;DR: In this paper, an air pollution monitoring system that measures the noise generated from polluting hot mix plant and multicast the acquired noise data to the Central Pollution Control Board (CPCB) and other communication media is proposed.
Abstract: In highly densely populated country like India, environmental pollution is a major problem. Specifically, the hot mix plant used for laying roadways is posing a threat to the environment by emitting heavy noise and smoke. This paper proposes an air pollution monitoring system that measures the noise generated from polluting hot mix plant and multicast the acquired noise data to the Central Pollution Control Board (CPCB) and other communication media. Initially, the pressure is acquired from sound source by microphone and then converted to electrical signals in time domain. Applying Fast Fourier Transform converts time function into the spectrum of frequency component to which A-weighting filtering technique is applied. The resulting magnitude is given as the input to the microcontroller to calculate the noise in terms of decibels. The calculated value is compared with the ambient air quality standards in respect of noise and then the appropriate outputs are displayed in LCD. The abnormalities are indicated by red, orange and green LED based on the intensity of the sound levels as heavy, medium and normal respectively. To achieve the centralized monitoring process, the results are multicast using GSM module to facilitate the authorities to take the necessary decision.
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30 Nov 2017
TL;DR: The investigation results reveals residential as well as commercial areas pollution noise level is beyond the permissible limit in evening session and there is need of action to control the Noise level in Nanded city.
Abstract: In this study we examine the level of noise present in Nanded city of Maharashtra with the help of Geographical information system and Data mining technique. The noise data is collected during the month of March and April 2017. The spatial data mining algorithm natural neighbor was applied to generate the surface model. Unsupervised data mining techniques i.e. Shapiro-Wilk normality test and supervised data mining technique Wilcoxon rank sum test were applied to identify the significant difference in day and night time noise pollution. In this study we followed the CPCB 2000 guideline. Data was collected from Residential and commercial area. The investigation results reveals residential as well as commercial areas pollution noise level is beyond the permissible limit in evening session. Furthermore, there is need of action to control the Noise level in Nanded city.
1 citations
01 Sep 2018
TL;DR: A system design is presented for cattle security that address to protect the cattle farm from intruders that involves a micro controller based security system and a GSM Module.
Abstract: The Cattle theft is one of the major reason behind decline in the population of cattle. The objective of this paper is to provide the security for the cattle farm. A micro controller based security system is designed for this system. Initially, the sensors are mounted at four sides of the farm, for which the proximity range is fixed. This helps to detect the intruders along the 360° of the cattle farm based on the principle of an echo signal generated by the ultrasonic waves bounce off an object. Then the detected information is processed by the micro controller. Based on the processed information, the respective sensors trigger a security alarm and also using the GSM Module, the location of the intruder motion is sent to the owner of the cattle farm. In this paper, a system design is presented for cattle security that address to protect the cattle farm from intruders.
Cites methods from "An Efficient System Model for Multi..."
...In this framework PIR sensor utilized to sense and after that microcontroller is utilized for controlling reason and a GSM module is utilized for SMS and calling function [4]....
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References
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TL;DR: An Environmental Air Pollution Monitoring System (EAPMS) for monitoring the concentrations of major air pollutant gases has been developed, complying with the IEEE 1451.2 standard as mentioned in this paper.
Abstract: An Environmental Air Pollution Monitoring System (EAPMS) for monitoring the concentrations of major air pollutant gases has been developed, complying with the IEEE 1451.2 standard. This system measures concentrations of gases such as CO, NO2, SO2, and O3 using semiconductor sensors. The smart transducer interface module (STIM) was implemented using the analog devices' ADuC812 microconverter. Network Capable Application Processor (NCAP) was developed using a personal computer and connected to the STIM via the transducer independent interface. Three gas sensors were calibrated using the standard calibration methods. Gas concentration levels and information regarding the STIM can be seen on the graphical user interface of the NCAP. Further, the EAPMS is capable of warning when the pollutant levels exceed predetermined maxima and the system can be developed into a low cost version for developing countries.
211 citations
17 May 2009
TL;DR: This paper enables citizens to measure their personal exposure to noise in their everyday environment by using GPS-equipped mobile phones as noise sensors and geo-localised measures and user-generated meta-data can be automatically sent and shared online with the public to contribute to the collective noise mapping of cities.
Abstract: In this paper we present a new approach to monitor noise pollution involving citizens and built upon the notions of participatory sensing and citizen science. We enable citizens to measure their personal exposure to noise in their everyday environment by using GPS-equipped mobile phones as noise sensors. The geo-localised measures and user-generated meta-data can be automatically sent and shared online with the public to contribute to the collective noise mapping of cities. Our prototype, called Noise Tube, can be found online.
193 citations
TL;DR: This paper presents a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges of constructing the high-throughput sensor Grid.
Abstract: In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.
141 citations
TL;DR: The Raspberry Pi platforms are observed to be a feasible low-cost alternative to increase the spatial-temporal resolution, whereas Tmote-Invent nodes do not confirm their suitability due to their limited memory and calibration issues.
Abstract: Noise pollution caused by vehicular traffic is a common problem in urban environments that has been shown to affect people's health and children's cognition. In the last decade, several studies have been conducted to assess this noise, by measuring the equivalent noise pressure level (called L
eq
) to acquire an accurate sound map using wireless networks with acoustic sensors. However, even with similar values of L
eq
, people can feel the noise differently according to its frequency characteristics. Thus, indexes, which can express people's feelings by subjective measures, are required. In this paper, we analyze the suitability of using the psychoacoustic metrics given by the Zwicker's model, instead of just only considering L
eq
. The goal is to evaluate the hardware limitations of a low-cost wireless acoustic sensor network that is used to measure the annoyance, using two types of commercial and off-the-shelf sensor nodes, Tmote-Invent nodes and Raspberry Pi platforms. Moreover, to calculate the parameters using these platforms, different simplifications to the Zwicker's model based on the specific features of road traffic noise are proposed. To validate the different alternatives, the aforementioned nodes are tested in a traffic congested area of Valencia City in a vertical and horizontal network deployment. Based on the results, it is observed that the Raspberry Pi platforms are a feasible low-cost alternative to increase the spatial-temporal resolution, whereas Tmote-Invent nodes do not confirm their suitability due to their limited memory and calibration issues.
95 citations
TL;DR: This study develops and evaluates several new noise metrics for more accurate assessment of exposure risks to complex and impulsive noises and identifies the most promising noise metric.
Abstract: Many noise guidelines currently use A-weighted equivalent sound pressure level LAeq as the noise metric and the equal energy hypothesis to assess the risk of occupational noises. Because of the time-averaging effect involved with the procedure, the current guidelines may significantly underestimate the risk associated with complex noises. This study develops and evaluates several new noise metrics for more accurate assessment of exposure risks to complex and impulsive noises. The analytic wavelet transform was used to obtain time-frequency characteristics of the noise. 6 basic, unique metric forms that reflect the time-frequency characteristics were developed, from which 14 noise metrics were derived. The noise metrics were evaluated utilizing existing animal test data that were obtained by exposing 23 groups of chinchillas to, respectively, different types of noise. Correlations of the metrics with the hearing losses observed in chinchillas were compared and the most promising noise metric was identified.
14 citations