Results 71 to 80 of about 1,427,497 (206)
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
How sustainable is social based mobile crowdsensing? An experimental study
, 2016 The wide spread of smart mobile devices such as tablets and phones makes mobile crowdsensing a viable approach for collecting data and monitoring phenomena of common interest.
Bermejo, Carlos +5 more
core +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
Mobile crowdsensing for road sustainability: exploitability of publicly-sourced data [PDF]
, 2020 This paper examines the opportunities and the economic benefits of exploiting publicly-sourced datasets of road surface quality. Crowdsourcing and crowdsensing initiatives channel the participation of engaged citizens into communities that contribute ...
Peter Parfitt +7 more
core +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
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
FairCs—Blockchain-Based Fair Crowdsensing Scheme using Trusted Execution Environment
Sensors, 2020 Crowdsensing applications provide platforms for sharing sensing data collected by mobile devices. A blockchain system has the potential to replace a traditional centralized trusted third party for crowdsensing services to perform operations that involve ...
Yihuai Liang, Yan Li, Byeong-Seok Shin
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 +3 more sources
Structural Control and Health Monitoring, Volume 2025, Issue 1, 2025.As aging bridge infrastructure poses increasing safety risks, there is a critical need for reliable and scalable Structural Health Monitoring (SHM) systems. Traditional SHM methods, which rely on fixed sensor networks and assessments of individual bridges, face significant challenges in scalability, cost, and efficiency—particularly in complex urban ...
Jiangyu Zeng +3 more
wiley +1 more source