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NoiseSPY: a real-time mobile phone platform for urban noise monitoring and mapping
In this paper we present the design, implementation, evaluation, and user experiences of the NoiseSpy application, our sound sensing system that turns the mobile phone into a low-cost data logger for monitoring environmental noise. It allows users to explore a city area while collaboratively visualizing noise levels in real-time. The software combines the sound levels with GPS data in order to generate a map of sound levels that were encountered during a journey. We report early findings from the trials which have been carried out by cycling couriers who were given Nokia mobile phones equipped with the NoiseSpy software to collect noise data around Cambridge city. Indications are that, not only is the functionality of this personal environmental sensing tool engaging for users, but aspects such as personalization of data, contextual information, and reflection upon both the data and its collection, are important factors in obtaining and retaining their interest
The Programmable City
AbstractThe worldwide proliferation of mobile connected devices has brought about a revolution in the way we live, and will inevitably guide the way in which we design the cities of the future. However, designing city-wide systems poses a new set of challenges in terms of scale, manageability and citizen involvement. Solving these challenges is crucial to making sure that the vision of a programmable Internet of Things (IoT) becomes reality. In this article we will analyse these issues and present a novel programming approach to designing scalable systems for the Internet of Things, with an emphasis on smart city applications, that addresses these issues
Urban Air Pollution Monitoring Using Wireless Sensor Networks: A Comprehensive Review
Air pollution is evolving as a severe environmental concern due to its enormous impact on the well being of the people, universal environment and also on the global economy. Conventional air pollution systems are not able to provide air pollution data of high spatiotemporal resolution due to non-scalability and limited data availability. With the advances in the areas of Micro Electro Mechanical Sensor (MEMS) and Wireless Sensor Network (WSN), the researchers had implemented various state-of-the-art air pollution monitoring systems with better and efficient results. A comprehensive review of continuous air pollution surveillance of both indoor and outdoor pollution by employing WSN was presented. In the proposed paper attempts to provide the details related to the existing methods for measuring major air pollutants like CO2, CO, O3, SO2, VOC and Particulate Matter (PM). It presents the various methods, algorithms and dedicated network designs in air pollution monitoring which are useful for generating new solutions to improve the performance through WSN. A comprehensive and detailed review of the existing methods of Air Quality Monitoring systems using WSN was done along with their comparison
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
An airborne remote sensing system for urban air quality
Several NASA sponsored remote sensors and possible airborne platforms were evaluated. Outputs of dispersion models for SO2 and CO pollution in the Washington, D.C. area were used with ground station data to establish the expected performance and limitations of the remote sensors. Aircraft/sensor support requirements are discussed. A method of optimum flight plan determination was made. Cost trade offs were performed. Conclusions about the implementation of various instrument packages as parts of a comprehensive air quality monitoring system in Washington are presented
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