Smart City Gnosys
Smart city article details
| Title | Noiseprobe: Assessing The Dynamics Of Urban Noise Pollution Through Participatory Sensing |
|---|---|
| ID_Doc | 39294 |
| Authors | Ghosh A.; Kumari K.; Kumar S.; Saha M.; Nandi S.; Saha S. |
| Year | 2019 |
| Published | 2019 11th International Conference on Communication Systems and Networks, COMSNETS 2019 |
| DOI | http://dx.doi.org/10.1109/COMSNETS.2019.8711473 |
| Abstract | The ambient environment conditions play a significant role in determining the actual quality of life in smart cities. Among the several pollutants that have impacted the environment compromising well being of the citizens is urban noise pollution. The prime reasons for the rise of noise pollution are imbalanced urbanization, unregulated increase in traffic and inorganic industrialization. In a bid to realize the concept of smart cities, it has become important to monitor this environment parameter for policy-making and planning for making cities livable and sustainable. The existing infrastructure for noise pollution monitoring is limited considering the coverage needed and is mostly provided by the government agencies. The advancement in mobile technology and the increasing number of mobile phone users has given an alternative in the form of participatory sensing using inbuilt microphones in mobile devices for ambient noise pollution monitoring. In these contexts, the proposed work NoiseProbe, intends to implement a participatory sensing framework by incorporating crowd-sensed data from mobile sensing to monitor city-scale noise pollution levels in real-time. It will use the aggregated information to understand the spatio-temporal characteristics of noise pollution, creating a meaningful visualization, as well as providing each user with information on their personal exposure to noise pollution. The initial outdoor experiments demonstrate that NoiseProbe can be a feasible platform for assessing the dynamics of noise pollution monitoring and providing fruitful information. © 2019 IEEE. |
| Author Keywords | Mobile sensing; Noise pollution; Participatory sensing; Smart city; Visualization |
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