Awareness and learning in participatory noise sensing

Informing about the invisible: communicating en route air pollution and noise exposure to cyclists and pedestrians using focus groups

Active mobility and public transport are considered beneficial for health and wellbeing and valuable for climate change mitigation. However, cyclists and pedestrians have high air pollution and noise exposure alongside traffic, which adversely impact health and wellbeing. The measured exposure can differ from the perceived exposure, hence, communicating en route exposure is crucial. Therefore, this study investigates how to communicate route-based exposure to cyclists and pedestrians and explores if exposure communication, e.g. via smartphones, is worthwhile for healthy and pleasant commute. It is investigated how exposure feedback influences the motivation to protect oneself and how exposure information should be designed. Three focus groups with 20 cyclists/pedestrians living in Berlin, Germany, were conducted. Based on Protection Motivation Theory and Environmental Health Literacy concept, (1) experiences and practices after recognizing exposure were discussed and (2) information needs and communication strategies were developed. The results reveal a feeling of helplessness regarding the ubiquity and uncertainty of pollution and a heightened threat appraisal. Anger, anxiety and rejection were stated. Making sense of pollution levels and protective alternatives were central. A healthy routing app, including also pleasant route factors, was desired. However, information provision was also denied. Participants argued the responsibility should not be left to the commuters and planning for exposed road users would be crucial. Information provision may not be worthwhile if planning authorities do not provide healthy alternatives. People-centered approaches for tackling air pollution and noise exposure en route should be investigated further.

Indoor noise level measurements and subjective comfort: Feasibility of smartphone-based participatory experiments

We designed and performed a participatory sensing initiative to explore the reliability and effectiveness of a distributed network of citizen-operated smartphones in evaluating the impact of environmental noise in residential areas. We asked participants to evaluate the comfort of their home environment in different situations and at different times, to select the most and least comfortable states and to measure noise levels with their smartphones. We then correlated comfort ratings with noise measurements and additional contextual information provided by participants. We discuss how to strengthen methods and procedures, particularly regarding the calibration of the devices, in order to make similar citizen-science efforts effective at monitoring environmental noise and planning long-term solutions to human well-being.

Finding successful strategies in a complex urban sustainability game

The adverse effects of unsustainable behaviors on human society are leading to an increasingly urgent and critical need to change policies and practices worldwide. This requires that citizens become informed and engaged in participatory governance and measures leading to sustainable futures. Citizens’ understanding of the inherent complexity of sustainable systems is a necessary (though generally not sufficient) ingredient for them to understand controversial public policies and maintain the core principles of democratic societies. In this work, we present a novel, open-ended experiment where individuals had the opportunity to solve model urban sustainability problems in a purposeful game. Participants were challenged to interact with familiar LEGO blocks representing elements in a complex generative urban economic indicators model. Players seeks to find a specific urban configuration satisfying particular sustainability requirements. We show that, despite the intrinsic complexity and non-linearity of the problems, participants’ ability to make counter-intuitive actions helps them find suitable solutions. Moreover, we show that through successive iterations of the experiment, participants can overcome the difficulties linked to non-linearity and increase the probability of finding the correct solution to the problem. We contend that this kind of what-if platforms could have a crucial role in future approaches to sustainable developments goals.

Geo-Crowdsourced Sound Level Data in Support of the Community Facilities Planning. A Methodological Proposal

To reduce environmental noise pollution and to safeguard people’s well-being, it is urgently necessary to move towards sustainable urban development and reconcile demographic and economic growth with the protection and restoration of the environment and the improvement of the quality of human lives. This challenge should be a concern to policymakers, who must issue regulations and define the appropriate actions for noise monitoring and management, and citizens, who must be sensitive to the problem and act accordingly. Starting from an analysis of several crowdsourcing noise data collection tools, this paper focuses on the definition of a methodology for data analysis and mapping. The sound sensing system, indeed, enables mobile devices, such as smartphones and tablets, to become a low-cost data collection for monitoring environmental noise. For this study, the “NoiseCapture” application developed in France by CNRS and IFSTTAR has been utilized. The measurements acquired in 2018 and 2019 at the Fisciano Campus at the University of Salerno were integrated with the kernel density estimation. This is a spatial analysis technique that allows for the elaboration of sound level density maps, defined spatially and temporally. These maps, overlaid on a campus facilities map, can become tools to support the appropriate mitigation actions.

Sustainable Urban Air Mobility Supported with Participatory Noise Sensing

In about 15 years, there is likely to be urban air mobility (UAM) in larger cities across the globe. Air taxis will provide on-demand transportation for individual needs. They will also connect important transportation nodes, such as airports and city centers, as well as providing quick transfers between train stations or a convenient option for crossing rivers and lakes. It is hoped that UAM will help meet today’s political targets of sustainability and decarbonization. However, there are certain threats that could impede the sustainable and thus successful introduction of UAM to our cities, with noise being a prominent limitation. This paper argues that citizens have to be viewed as stakeholders in urban air transportation, regardless of whether they or not intend to use it, and that a concept of resident participatory noise sensing (PNS) will be beneficial to the implementation of UAM. Web-based services and smartphones facilitate the access and updating of current information about local noise distributions, thus enabling them to be used to foster UAM in smart cities.

Teachers' and Children's Experiences after an Acoustic Intervention and a Noise-Controlling Workshop in Two Elementary Classrooms

INTRODUCTION

Treating sources of noise is a novel aspect of voice ergonomics intended to enhance the preconditions for good voice production and easy listening.

OBJECTIVE

To improve experiences of listening and voice ergonomics in classrooms.

METHODS

Participants were two female elementary school teachers with voice symptoms and their pupils (n = 50). Two interventions were performed: the acoustic intervention and then the workshop intervention where the teachers and pupils were active. Teachers' voice symptoms and pupils' and teachers' experiences of the interventions were elicited by questionnaire.

RESULTS

The teacher with many voice symptoms experienced more annoyance from sounds and benefitted more from the interventions. After the interventions both teachers suffered fewer voice breaks and voice symptoms such as lump and mucus in the throat. The pupils reported improvement in the teachers' voice clarity and audibility (p = 0.001). Pupils aged 12-13 years were more annoyed by sounds than those aged 8-9 years (p = 0.003). The older pupils experienced less sound annoyance after both interventions and the younger ones after the workshop intervention.

CONCLUSIONS

The importance of good acoustics and individuals' ability to improve voice ergonomics and listening conditions was demonstrated.

A Citizen-Sensing-Based Digital Service for the Analysis of On-Site Post-Earthquake Messages

The effectiveness of disaster response depends on the correctness and timeliness of data regarding the location and the impact of the event. These two issues are critical when the data come from citizens’ tweets, since the automatic classification of disaster-related tweets suffers from many shortcomings. In this paper, we explore an approach based on participatory sensing (i.e., a subset of mobile crowdsourcing that emphasizes the active and intentional participation of citizens to collect data from the place where they live or work). We operate with the hypothesis of a “friendly world”, that is by assuming that after a calamitous event, in the survivors prevails the feeling of helping those who suffer. The extraction, from the Twitter repository, of the few tweets relevant to the event of interest has a long processing time. With the aggravating circumstance in the phase that follows a severe earthquake, the elaboration of tweets clashes with the need to act promptly. Our proposal allows a huge reduction of the processing time. This goal is reached by introducing a service and a mobile app, the latter is an intermediate tool between Twitter and the citizens, suitable to assist them to write structured messages that act as surrogates of tweets. The article describes the architecture of the software service and the steps involved in the retrieval, from the Twitter server, of the messages coming from citizens living in the places hit by the earthquake; moreover, it details the storage of those messages into a geographical database and their processing using SQL.

GRC-Sensing: An Architecture to Measure Acoustic Pollution Based on Crowdsensing

Noise pollution is an emerging and challenging problem of all large metropolitan areas, affecting the health of citizens in multiple ways. Therefore, obtaining a detailed and real-time map of noise in cities becomes of the utmost importance for authorities to take preventive measures. Until now, these measurements were limited to occasional sampling made by specialized companies, that mainly focus on major roads. In this paper, we propose an alternative approach to this problem based on crowdsensing. Our proposed architecture empowers participating citizens by allowing them to seamlessly, and based on their context, sample the noise in their surrounding environment. This allows us to provide a global and detailed view of noise levels around the city, including places traditionally not monitored due to poor accessibility, even while using their vehicles. In the paper, we detail how the different relevant issues in our architecture, i.e., smartphone calibration, measurement adequacy, server design, and client⁻server interaction, were solved, and we have validated them in real scenarios to illustrate the potential of the solution achieved.

Advanced Smartphone-Based Sensing with Open-Source Task Automation

Smartphone-based sensing is becoming a convenient way to collect data in science, especially in environmental research. Recent studies that use smartphone sensing methods focus predominantly on single sensors that provide quantitative measurements. However, interdisciplinary projects call for study designs that connect both, quantitative and qualitative data gathered by smartphone sensors. Therefore, we present a novel open-source task automation solution and its evaluation in a personal exposure study with cyclists. We designed an automation script that advances the sensing process with regard to data collection, management and storage of acoustic noise, geolocation, light level, timestamp, and qualitative user perception. The benefits of this approach are highlighted based on data visualization and user handling evaluation. Even though the automation script is limited by the technical features of the smartphone and the quality of the sensor data, we conclude that task automation is a reliable and smart solution to integrate passive and active smartphone sensing methods that involve data processing and transfer. Such an application is a smart tool gathering data in population studies.

A natural user interface to integrate citizen science and physical exercise

Citizen science enables volunteers to contribute to scientific projects, where massive data collection and analysis are often required. Volunteers participate in citizen science activities online from their homes or in the field and are motivated by both intrinsic and extrinsic factors. Here, we investigated the possibility of integrating citizen science tasks within physical exercises envisaged as part of a potential rehabilitation therapy session. The citizen science activity entailed environmental mapping of a polluted body of water using a miniature instrumented boat, which was remotely controlled by the participants through their physical gesture tracked by a low-cost markerless motion capture system. Our findings demonstrate that the natural user interface offers an engaging and effective means for performing environmental monitoring tasks. At the same time, the citizen science activity increases the commitment of the participants, leading to a better motion performance, quantified through an array of objective indices. The study constitutes a first and necessary step toward rehabilitative treatments of the upper limb through citizen science and low-cost markerless optical systems.

Activating social strategies: Face-to-face interaction in technology-mediated citizen science

The use of crowds in research activities by public and private organizations is growing under different forms. Citizen science is a popular means of engaging the general public in research activities led by professional scientists. By involving a large number of amateur scientists, citizen science enables distributed data collection and analysis on a scale that would be otherwise difficult and costly to achieve. While advancements in information technology in the past few decades have fostered the growth of citizen science through online participation, several projects continue to fail due to limited participation. Such web-based projects may isolate the citizen scientists from the researchers. By adopting the perspective of social strategy, we investigate within a measure-manipulate-measure experiment if motivations to participate in a citizen science project can be positively influenced by a face-to-face interaction with the scientists leading the project. Such an interaction provides the participants with the possibility of asking questions on the spot and obtaining a detailed explanation of the citizen science project, its scientific merit, and environmental relevance. Social and cultural factors that moderate the effect brought about by face-to-face interactions on the motivations are also dissected and analyzed. Our findings provide an exploratory insight into a means for motivating crowds to participate in online environmental monitoring projects, also offering possible selection criteria of target audience.

Chatty maps: constructing sound maps of urban areas from social media data

Urban sound has a huge influence over how we perceive places. Yet, city planning is concerned mainly with noise, simply because annoying sounds come to the attention of city officials in the form of complaints, whereas general urban sounds do not come to the attention as they cannot be easily captured at city scale. To capture both unpleasant and pleasant sounds, we applied a new methodology that relies on tagging information of georeferenced pictures to the cities of London and Barcelona. To begin with, we compiled the first urban sound dictionary and compared it with the one produced by collating insights from the literature: ours was experimentally more valid (if correlated with official noise pollution levels) and offered a wider geographical coverage. From picture tags, we then studied the relationship between soundscapes and emotions. We learned that streets with music sounds were associated with strong emotions of joy or sadness, whereas those with human sounds were associated with joy or surprise. Finally, we studied the relationship between soundscapes and people's perceptions and, in so doing, we were able to map which areas are chaotic, monotonous, calm and exciting. Those insights promise to inform the creation of restorative experiences in our increasingly urbanized world.

Can Observation Skills of Citizen Scientists Be Estimated Using Species Accumulation Curves?

Volunteers are increasingly being recruited into citizen science projects to collect observations for scientific studies. An additional goal of these projects is to engage and educate these volunteers. Thus, there are few barriers to participation resulting in volunteer observers with varying ability to complete the project's tasks. To improve the quality of a citizen science project's outcomes it would be useful to account for inter-observer variation, and to assess the rarely tested presumption that participating in a citizen science projects results in volunteers becoming better observers. Here we present a method for indexing observer variability based on the data routinely submitted by observers participating in the citizen science project eBird, a broad-scale monitoring project in which observers collect and submit lists of the bird species observed while birding. Our method for indexing observer variability uses species accumulation curves, lines that describe how the total number of species reported increase with increasing time spent in collecting observations. We find that differences in species accumulation curves among observers equates to higher rates of species accumulation, particularly for harder-to-identify species, and reveals increased species accumulation rates with continued participation. We suggest that these properties of our analysis provide a measure of observer skill, and that the potential to derive post-hoc data-derived measurements of participant ability should be more widely explored by analysts of data from citizen science projects. We see the potential for inferential results from analyses of citizen science data to be improved by accounting for observer skill.

A statistical method for assessing network stability using the Chow test

A statistical method is proposed for the assessment of stability in noise monitoring networks. The technique makes use of a variation of the Chow test applied between multiple measurement nodes placed at different locations and its novelty lies in the way it utilises a simple statistical test based on linear regression to uncover complex issues that can be difficult to expose otherwise. Measurements collected by a noise monitoring network deployed in the center of Pisa are used to demonstrate the capabilities and limitations of the test. It is shown that even in urban environments, where great soundscape variations are exhibited, accurate and robust results can be produced regardless of the proximity of the compared sensors as long as they are located in acoustically similar environments. Also it is shown that variations of the same method can be applied for self-testing on data collected by single stations. Finally it is presented that the versatility of the test makes it suitable for detection of various types of issues that can occur in real life network implementations; from slow drifts away from calibration, to severe, abrupt failures and noise floor shifts.

Participatory Patterns in an International Air Quality Monitoring Initiative

The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.