Quality of information in mobile crowdsensing: Survey and research challenges

F Restuccia, N Ghosh, S Bhattacharjee… - ACM Transactions on …, 2017‏ - dl.acm.org
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 …

Mobile crowd sensing–taxonomy, applications, challenges, and solutions

DE Boubiche, M Imran, A Maqsood… - Computers in Human …, 2019‏ - Elsevier
Recently, mobile crowd sensing (MCS) is captivating growing attention because of their
suitability for enormous range of new types of context-aware applications and services. This …

A survey on security, privacy, and trust in mobile crowdsourcing

W Feng, Z Yan, H Zhang, K Zeng… - IEEE Internet of …, 2017‏ - ieeexplore.ieee.org
With the popularity of sensor-rich mobile devices (eg, smart phones and wearable devices),
mobile crowdsourcing (MCS) has emerged as an effective method for data collection and …

Cost-and-quality aware data collection for edge-assisted vehicular crowdsensing

L Liu, L Wang, Z Lu, Y Liu, W **g… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
In view of the rapid development of edge computing and vehicular network, edge-assisted
vehicular crowdsensing system has brought significant benefits to Intelligent Transportation …

Steering crowdsourced signal map construction via Bayesian compressive sensing

S He, KG Shin - IEEE INFOCOM 2018-IEEE Conference on …, 2018‏ - ieeexplore.ieee.org
Mobile crowdsensing with increasing pervasiveness of smartphones has enabled a myriad
of applications, including urban-scale signal map monitoring and revision. Despite the …

A method for sensor-based activity recognition in missing data scenario

T Hossain, MAR Ahad, S Inoue - Sensors, 2020‏ - mdpi.com
Sensor-based human activity recognition has various applications in the arena of
healthcare, elderly smart-home, sports, etc. There are numerous works in this field—to …

A cost-quality beneficial cell selection approach for sparse mobile crowdsensing with diverse sensing costs

Z Zhu, B Chen, W Liu, Y Zhao, Z Liu… - IEEE Internet of Things …, 2020‏ - ieeexplore.ieee.org
The Internet of Things (IoT) and mobile techniques enable real-time sensing for urban
computing systems. By recruiting only a small number of users to sense data from selected …

Truth discovery in sequence labels from crowds

N Sabetpour, A Kulkarni, S **e… - 2021 IEEE International …, 2021‏ - ieeexplore.ieee.org
Annotation quality and quantity positively affect the learning performance of sequence
labeling, a vital task in Natural Language Processing. Hiring domain experts to annotate a …

Learning-assisted optimization in mobile crowd sensing: A survey

J Wang, Y Wang, D Zhang, J Goncalves… - IEEE Transactions …, 2018‏ - ieeexplore.ieee.org
Mobile crowd sensing (MCS) is a relatively new paradigm for collecting real-time and
location-dependent urban sensing data. Given its applications, it is crucial to optimize the …

Discovering pollution sources and propagation patterns in urban area

X Li, Y Cheng, G Cong, L Chen - Proceedings of the 23rd ACM SIGKDD …, 2017‏ - dl.acm.org
Air quality is one of the most important environmental concerns in the world, and it has
deteriorated substantially over the past years in many countries. For example, Chinese …