Federated learning in smart city sensing: Challenges and opportunities
Smart Cities sensing is an emerging paradigm to facilitate the transition into smart city
services. The advent of the Internet of Things (IoT) and the widespread use of mobile …
services. The advent of the Internet of Things (IoT) and the widespread use of mobile …
Cough sound detection and diagnosis using artificial intelligence techniques: challenges and opportunities
Coughing is a common symptom of several respiratory diseases. The sound and type of
cough are useful features to consider when diagnosing a disease. Respiratory infections …
cough are useful features to consider when diagnosing a disease. Respiratory infections …
PACE: Privacy-preserving and quality-aware incentive mechanism for mobile crowdsensing
Providing appropriate monetary rewards is an efficient way for mobile crowdsensing to
motivate the participation of task participants. However, a monetary incentive mechanism is …
motivate the participation of task participants. However, a monetary incentive mechanism is …
BCOSN: A blockchain-based decentralized online social network
L Jiang, X Zhang - IEEE Transactions on Computational Social …, 2019 - ieeexplore.ieee.org
Online social networks (OSNs) are becoming more and more prevalent in people's life, but
they face the problem of privacy leakage due to the centralized data management …
they face the problem of privacy leakage due to the centralized data management …
On blockchain integration into mobile crowdsensing via smart embedded devices: A comprehensive survey
As an integral part of Internet of Things (IoT), mobile crowdsensing (MCS) via smart
embedded devices has recently gained significant attention for being effective in a wide …
embedded devices has recently gained significant attention for being effective in a wide …
Privacy-preserving task allocation for edge computing-based mobile crowdsensing
In the era of big data, edge computing has coped greatly with the increase in data. Recently,
edge computing has been incorporated into mobile crowdsensing (MCS) to collect large …
edge computing has been incorporated into mobile crowdsensing (MCS) to collect large …
User-aware and flexible proactive caching using LSTM and ensemble learning in IoT-MEC networks
To meet the stringent demands of emerging Internet-of-Things (IoT) applications, such as
smart home, smart city, and virtual reality in 5G/6G IoT networks, edge content caching for …
smart home, smart city, and virtual reality in 5G/6G IoT networks, edge content caching for …
PRICE: Privacy and reliability-aware real-time incentive system for crowdsensing
Crowdsensing is regarded as a critical component of the Internet of Things (IoT) and has
been widely applied in smart city services. Incentive mechanism design, data reliability …
been widely applied in smart city services. Incentive mechanism design, data reliability …
An efficient online computation offloading approach for large-scale mobile edge computing via deep reinforcement learning
Mobile edge computing (MEC) has been envisioned as a promising paradigm that could
effectively enhance the computational capacity of wireless user devices (WUDs) and quality …
effectively enhance the computational capacity of wireless user devices (WUDs) and quality …
Incentive mechanisms for mobile crowdsensing with heterogeneous sensing costs
The emerging mobile crowdsensing applications are able to facilitate people's life in various
aspects. A key factor to ensure that these applications can provide high-quality service is the …
aspects. A key factor to ensure that these applications can provide high-quality service is the …