Analyzing Correlation Between Air and Noise Pollution with Influence on Air Quality Prediction

Ghosh, Arindam; Pramanik, Prithviraj; Banerjee, Kartick Das; Roy, Ashutosh; Nandi, S.; Saha, Sujoy

doi:10.1109/icdmw.2018.00133

Cited by 12 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Cost Effective Ubiquitous Air Quality Sensingmentioning

confidence: 99%

“…While the works discussed above are all related to primary sensing of the pollutants, other works indirectly measure air quality through various modalities like sound, social media, images, and other spatio-temporal factors [18,33,39,40,43]. In [18], the authors have shown that acoustic signatures correlate well with the air quality. Accordingly, they have developed a prediction model to estimate the air quality from the auditory noise information, especially for areas with a high density of traffic.…”

Section: Cost Effective Ubiquitous Air Quality Sensingmentioning

confidence: 99%

See 1 more Smart Citation

AQuaMoHo: Localized Low-Cost Outdoor Air Quality Sensing over a Thermo-Hygrometer

Pramanik¹,

Karmakar²,

Kumar³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Efficient air quality sensing serves as one of the essential services provided in any recent smart city. Mostly facilitated by sparsely deployed Air Quality Monitoring Stations (AQMSs) that are difficult to install and maintain, the overall spatial variation heavily impacts air quality monitoring for locations far enough from these pre-deployed public infrastructures. To mitigate this, we in this paper propose a framework named AQuaMoHo that can annotate data obtained from a low-cost thermo-hygrometer (as the sole physical sensing device) with the AQI labels, with the help of additional publicly crawled Spatio-temporal information of that locality. At its core, AQuaMoHo exploits the temporal patterns from a set of readily available spatial features using an LSTM-based model and further enhances the overall quality of the annotation using temporal attention. From a thorough study of two different cities, we observe that AQuaMoHo can significantly help annotate the air quality data on a personal scale.CCS Concepts: • Human-centered computing → Human computer interaction (HCI); • Information systems → Location based services.

show abstract

Section: Cost Effective Ubiquitous Air Quality Sensingmentioning

confidence: 99%

Section: Cost Effective Ubiquitous Air Quality Sensingmentioning

confidence: 99%

AQuaMoHo: Localized Low-Cost Outdoor Air Quality Sensing over a Thermo-Hygrometer

Pramanik¹,

Karmakar²,

Kumar³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…1. In addition to contributing to the reduction of atmospheric and acoustic emissions (environmental), electric buses are generally associated with greater comfort and information (social) for users [5] as well as a better use of available energy, just to mention a few of the challenges.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Electric Buses Within an Urban Smart City Environment

et al. 2022

View full text Add to dashboard Cite

A practical experience on monitoring the data generated by electric buses is presented, focusing on energy consumption, charge and state of the batteries. The work is carried out in the framework of a global smart city strategy developed by the H2020 Smart City Lighthouse STARDUST project. The crucial role of the data collection and transmission from electric buses has become evident in this work, so the adopted solutions are covered in detail. A practical electric bus charging station configuration is considered, operating within the city of Pamplona, Spain, with an urban route setting in which electric charging is performed. Various key factors for the practical implementation of the necessary communication infrastructure, including wireless Low Power Wide Area connectivity challenges within the urban scenario settings, based in LoRa/LoRaWAN communication system nodes. The monitoring system architecture is also presented, in which specific machine learning modules in order to collect patterns and visualization of data to enhance planning, operation and maintenance procedures.

show abstract

“…Particularly, the electrification of the urban public transportation is critical to improve, among others, air quality and noise pollution in cities. In addition, electric buses are associated to improved comfort and more comprehensive information for users [2].…”

Section: Introductionmentioning

confidence: 99%

Smart Charging Station with Photovoltaic and Energy Storage for Supplying Electric Buses

Berrueta

Astráin

Puy

et al. 2022

2022 37th Conference on Design of Circuits and Integrated Circuits (DCIS)

View full text Add to dashboard Cite

A Smart Charging Station (SCS) has been installed in the Public University of Navarre, Spain, in the framework of the H2020 Smart City Lighthouse STARDUST project. The SCS consists of a high-power electric bus charging point (300 kW), a 100 kW photovoltaic system, a 84 kWh support energy storage system based on a second-life lithiumion battery, and a monitoring and control system that allows the safe storage and convenient access to operation data. This SCS operates as a Smart Grid, being able to provide the power peaks required by the electric bus charger, reducing and smoothing the power demanded from the distribution grid and increasing the renewable energy self-consumption rate. This contribution presents a novel monitoring and control system, which is a key tool to integrate this SCS in the data infrastructure of a Smart City, as well as an energy management system able to operate the SCS to achieve the above-mentioned technical requirements. The crucial role of the monitoring and control system and the energy management system becomes evident in this work.

show abstract

Analyzing Correlation Between Air and Noise Pollution with Influence on Air Quality Prediction

Cited by 12 publications

References 25 publications

AQuaMoHo: Localized Low-Cost Outdoor Air Quality Sensing over a Thermo-Hygrometer

AQuaMoHo: Localized Low-Cost Outdoor Air Quality Sensing over a Thermo-Hygrometer

Monitoring of Electric Buses Within an Urban Smart City Environment

Smart Charging Station with Photovoltaic and Energy Storage for Supplying Electric Buses

Contact Info

Product

Resources

About