Crowdsensing: Socio-Technical Challenges and Opportunities

Noureen, Javeria; Asif, Muhammad

doi:10.14569/ijacsa.2017.080351

Cited by 8 publications

(7 citation statements)

References 60 publications

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“…The widespread availability of smartphones, which are equipped with different sensors and cameras, has paved the way for large-scale MCS and a multitude of crowdsensing applications [3,4]. These include use cases such as temperature and traffic monitoring [5], detection of traffic regulators [6], WiFi localization [7], as well as WiFi characterization [8].…”

Section: Crowdsensing Systemsmentioning

confidence: 99%

Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments

Hirth

Seufert

Lange³

et al. 2021

Sensors

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Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data; however, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such systems allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data are typically available. In this work, we first used a simulation study to analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participate in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for the given detection time thresholds in our exemplary scenario.

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Section: Crowdsensing Systemsmentioning

confidence: 99%

Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments

Hirth

Seufert

Lange³

et al. 2021

Sensors

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“…• Public Safety; Includes assistive applications in the domains of safety and protection of the user by helping avoid situations that could potentially endanger their wellbeing. Proposed applications have been researched in [15].…”

Section: A Applications Of Crowdsourced Systemsmentioning

confidence: 99%

Circularity Principles in Crowdsourced Systems

Voulgaridis

Angelopoulos

2020

2020 Global Information Infrastructure and Networking Symposium (GIIS)

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High adoption rates of handheld smart devices, such as smartphones, have motivated the rise of crowdsensing methodologies. The corresponding crowdsourced systemssystems whose constituent infrastructure is provided or augmented by the end-users -have been proven very efficient and scalable systems for collecting data from the crowd. However, successfully and sustainably engaging the crowd introduces costs in the form of incentives. Also, the fragmented landscape of crowdsensing applications aggravates the problem of dark data. In this work we address this problem with the introduction of a reference framework for crowdsourced systems that entails circularity principles. Derived from recent developments in Circular Economy, the circularity principles enable the development of crowdsourced systems that are circular by design, by sharing and re-using already existing resources and data. We exemplify the use of the framework via an example use case.

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“…The social environment in which the participating users are at the specific moment -alone or in a group, for professional or personal concerns, out of curiosity or to get pieces of evidence of a noise environment-contributes to the way they engage in the MPS-based process. The users' IT skill and trust in privacy protection (Noureen & Asif, 2017) are other criteria that influence the sensing process. Noise or soundscapes sensing must thus be acknowledged as an experience (Bonfils, 2015).…”

Section: Mps For a Contributive Characterization Of Urban Soundscapesmentioning

confidence: 99%

Mobile crowd-sensing as a resource for contextualized urban public policies: a study using three use cases on noise and soundscape monitoring

et al. 2019

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Environmental noise is a major pollutant in contemporary cities and calls for the active monitoring of noise levels to spot the locations where it most affects the people's health and well-being. However, due to the complex relationship between environmental noise and its perception by the citizens, it is not sufficient to quantitatively measure environmental noise. We need to collect and aggregate contextualized-both quantitative and qualitative-data about the urban environmental noise so as to be able to study the objective and subjective relationships between sound and living beings. This complex knowledge is a prerequisite for making efficient territorial public policies for soundscapes that are inclined towards living beings welfare. In this paper, we investigate how Mobile Phone Sensing (MPS)-aka crowdsensing-enables the gathering of such knowledge, provided the implementation of sensing protocols that are customized according to the context of use and the intended exploitation of the data. Through three case studies that we carried out in France and Finland, we show that MPS is not solely a tool that contributes to sensitizing citizens and decision-makers about noise pollution; it also contributes to increasing our knowledge about the impact of the environmental noise on people's health and well-being in relation to its physical and subjective perception.

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Crowdsensing: Socio-Technical Challenges and Opportunities

Cited by 8 publications

References 60 publications

Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments

Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments

Circularity Principles in Crowdsourced Systems

Mobile crowd-sensing as a resource for contextualized urban public policies: a study using three use cases on noise and soundscape monitoring

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