Mobile Crowdsourcing for Mapping City Noise

Mobile phones carried by people are capable of capturing and sharing images, acoustics, and locations. We will be able to accomplish complex tasks if millions of people can share information and join efforts. This development is effectively leading to a new approach called mobile crowdsourcing. We have seen the applications of crowdsourcing in traffic real-time navigation (e.g., WAZE) and environmental monitoring.

Master Topic: Mobile Crowdsourcing for Mapping City Noise
Background
Mobile phones carried by people are capable of capturing and sharing images, acoustics, and locations. We will be able to accomplish complex tasks if millions of people can share information and join efforts. This development is effectively leading to a new approach called mobile crowdsourcing. We have seen the applications of crowdsourcing in traffic real-time navigation (e.g., WAZE) and environmental monitoring.

In this thesis, we will mainly focus on mobile crowdsourcing for noise measurements in Norway. In Norway, nearly 30% (about 1.4 million) are exposed to noise levels above 55 dB outside their home and the number is rapidly increasing [1]. In Fornebu, there are increasingly more constructions, people and traffic. Norway has the ambition to reduce noise annoyance 10% by 2020 [2]. However, there is no cost-effective method yet to know noise levels in order to provide strategic regulations for the government, the local communities or the residents. 

In particular, we will study mobile crowdsourcing techniques, develop an APP in the Android system (Google Nexus 6 for experiment), build a city noise map (e.g., Oslo, Fornebu) for PC or mobile phone, and test algorithms performances based on collected data. The APP will conveniently be used by end-users for crowdsourcing based noise level measurements and visualization. It is possible to extend the system to combine the noise map with other maps of a city (air pollution, property value, incidence of medical problems (psychological and physical problems can be caused by noise pollution)). 
Goal:
Study and develop mobile crowdsourcing for noise measurements in Norway
What will I do?
•    study mobile crowdsourcing techniques
•    develop an APP in Android (Google Nexus 6)
•    build a city noise map (e.g., Oslo, Fornebu) for PC or mobile phone
•    design new algorithms to improve noise level measurement accuracy (e.g., for mobile phones that are in pockets)
•    reduce mobile phone power consumption and filter faulty data
•    test algorithms performance based on collected data
•    extend the system to combine the noise map with other maps of a city (air pollution, property values, incidences of medical problems (psychological and physical problems can be caused by noise pollution)) 
Learning outcome:
•    Learn techniques for mobile crowdsourcing
•    Learn programming in Android 
•    Learn how to analyze data and visualize noise data in a map
•    Learn algorithm design and problem modeling in the context of crowdsourcing data
Qualifications:
•    Programming experience
•    Algorithm design experience
Contact supervisors
Yan Zhang, Simula Research Laboratory, and IFI, University of Oslo. Email: yanzhang@simula.no
Stein Gjessing, IFI, University of Oslo. Email: steing@ifi.uio.no 
References
[1] http://www.environment.no/Topics/Noise/
[2] "Quality of the Acoustic Environment", Oslo Community. http://www.miljo.oslo.kommune.no
 

Publisert 15. sep. 2015 10:21 - Sist endret 15. sep. 2015 10:26

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