Results 51 to 60 of about 1,427,497 (206)
Quality-Aware Pricing for Mobile Crowdsensing [PDF]
IEEE/ACM Transactions on Networking, 2018 Mobile crowdsensing has been considered as a promising approach for large scale urban data collection, but has also posed new challenging problems, such as incentivization and quality control. Among the other incentivization approaches, posted pricing has been widely adopted by commercial systems due to the reason that it naturally achieves ...
Kai Han 0003 +2 more
openaire +2 more sources
IET Blockchain, Volume 6, Issue 1, January/December 2026.The study presents C3Crowd$C^3Crowd$, a blockchain‐based framework designed to enhance security in crowd management through decentralization, cryptography and smart contracts. It uses reputation management and a credit‐based incentive model to encourage user participation while safeguarding sensitive crowd data.
Sukanta Chakraborty, Abhishek Majumder
wiley +1 more source
Task bundling in worker-centric mobile crowdsensing [PDF]
, 2021 Most existing research about task allocation in mobile crowdsensing mainly focus on requester-centric mobile crowdsensing (RCMCS), where the requester assigns tasks to workers to maximize his/her benefits.
Yang, Y. +4 more
core +1 more source
Anchor-Assisted and Vote-Based Trustworthiness Assurance in Smart City Crowdsensing
IEEE Access, 2016 Smart city sensing calls for crowdsensing via mobile devices that are equipped with various built-in sensors. As incentivizing users to participate in distributed sensing is still an open research issue, the trustworthiness of crowdsensed data is ...
Maryam Pouryazdan +3 more
doaj +1 more source
Crowdsensed Performance Benchmarking of Mobile Networks [PDF]
IEEE Access, 2019 In recent years, the boom of mobile-network-measurement apps has stimulated the growth of publicly available datasets, which contain up to billions of measurements conducted by anonymous end-users. Although the crowdsensing has proven its value in different areas, in the context of performance monitoring in cellular mobile networks, convincing ...
Vaclav Raida +3 more
openaire +3 more sources
IET Wireless Sensor Systems, Volume 16, Issue 1, January/December 2026.This article surveys the integration of the Internet of things (IoT) and machine learning (ML) in agricultural monitoring, highlighting their role in data collection, analysis and decision‐making for smart farming. It reviews application domains, data collection strategies, network architectures and learning methods whilst identifying key challenges ...
Ado Adamou Abba Ari +5 more
wiley +1 more source
A privacy-preserving collaborative reputation system for mobile crowdsensing
International Journal of Distributed Sensor Networks, 2018 Mobile crowdsensing is an emerging technology in which participants contribute sensor readings for different sensing applications. This technology enables a broad range of sensing applications by utilizing smartphones and tablets worldwide to improve ...
Bayan Hashr Alamri +2 more
doaj +1 more source
Efficient Processing of Geospatial mHealth Data Using a Scalable Crowdsensing Platform
Sensors, 2020 Smart sensors and smartphones are becoming increasingly prevalent. Both can be used to gather environmental data (e.g., noise). Importantly, these devices can be connected to each other as well as to the Internet to collect large amounts of sensor data ...
Robin Kraft +9 more
doaj +1 more source
Complexity, Volume 2026, Issue 1, 2026.This paper investigates the consensus problem in leader–follower connected vehicle systems (CVSs) under deception attacks—including coordinated position, velocity, and acceleration attacks as well as delays and disturbances. Centralized and decentralized event‐triggered control strategies are proposed, allowing follower actuators to update at ...
Azmat Ullah Khan Niazi +5 more
wiley +1 more source
A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities
IEEE Open Journal of the Computer Society, 2022 Sparse mobile crowdsensing (SMCS) has emerged as a promising sensing paradigm for urban sensing, leveraging the spatial and temporal correlation among data sensed in distinct sub-areas to cut sensing expenses dramatically. It intelligently selects only a
Shiting Zhao +5 more
doaj +1 more source