Results 81 to 90 of about 5,365 (199)
CENTURION: Incentivizing Multi-Requester Mobile Crowd Sensing
, 2017 The recent proliferation of increasingly capable mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource the collection of sensory data to a crowd of participating workers that carry various mobile devices.
Jin, Haiming, Nahrstedt, Klara, Su, Lu
core +1 more source
IET Information Security, Volume 2025, Issue 1, 2025.The increasing adoption of artificial intelligence (AI)‐driven unmanned aerial vehicles (UAVs) in military, commercial, and surveillance operations has introduced significant security challenges, including cyber threats, adversarial AI attacks, and communication vulnerabilities. This paper presents a comprehensive review of the key security threats and
Deafallah Alsadie, Jiwei Tian
wiley +1 more source
Density-Based Location Preservation for Mobile Crowdsensing With Differential Privacy
IEEE Access, 2018 In recent years, the widespread prevalence of smart devices has created a new class of mobile Internet of Thing applications. Called mobile crowdsensing, these techniques use workers with mobile devices to collect data and send it to task requester for ...
Mengmeng Yang +3 more
doaj +1 more source
Applied Sciences, 2022 Mobile crowdsensing (MCS) has recently emerged as an urban-sensing paradigm that takes advantage of smartphone sensing capabilities and user mobility.
Dat Van Anh Duong, Seokhoon Yoon
doaj +1 more source
Towards a Data‐Driven Digital Twin AI‐Based Architecture for Self‐Driving Vehicles
IET Intelligent Transport Systems, Volume 19, Issue 1, January/December 2025.ABSTRACT Recent advancements on digital technologies, particularly artificial intelligence, have been resulted into remarkable transformations in automobile industry. One of these technologies is artificial intelligence (AI). AI plays a key role in the development of autonomous vehicles. In this paper, the role of AI in autonomous vehicle (AV) platform
Parinaz Babaei +3 more
wiley +1 more source
Ensemble Transformer–Based Detection of Fake and AI–Generated News
Applied Computational Intelligence and Soft Computing, Volume 2025, Issue 1, 2025.The proliferation of fake online and AI–generated news content poses a significant threat to information integrity. This work leverages advanced natural language processing, machine learning, and deep learning algorithms to effectively detect fake and AI–generated content.
Md. Ishraquzzaman +4 more
wiley +1 more source
Sensors, 2017 Monitoring the status of urban environments, which provides fundamental information for a city, yields crucial insights into various fields of urban research.
Xu Kang, Liang Liu, Huadong Ma
doaj +1 more source
Secure Mobile Crowdsensing with Deep Learning
CoRR, 2018 In order to stimulate secure sensing for Internet of Things (IoT) applications such as healthcare and traffic monitoring, mobile crowdsensing (MCS) systems have to address security threats, such as jamming, spoofing and faked sensing attacks, during both the sensing and the information exchange processes in large-scale dynamic and heterogenous networks.
Liang Xiao 0003 +3 more
openaire +2 more sources
User-centric context inference for mobile crowdsensing [PDF]
Proceedings of the International Conference on Internet of Things Design and Implementation, 2019 Mobile crowdsensing is a powerful mechanism to aggregate hyper-local knowledge about the environment. Indeed, users may contribute valuable observations across time and space using the sensors embedded in their smartphones. However, the relevance of the provided measurements depends on the adequacy of the sensing context with respect to the phenomena ...
Du, Yifan +2 more
openaire +1 more source
International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.Ambient temperature estimation plays a vital role in various domains, including environmental monitoring, smart cities, and energy‐efficient systems. Traditional sensor‐based methods suffer from high deployment costs and limited scalability, while centralized machine learning approaches raise significant privacy concerns.
Saeid Zareie +3 more
wiley +1 more source