On the resilience of modern power systems: A comprehensive review from the cyber-physical perspective
The digital transformation of power systems into cyber-physical systems (CPSs) is the
inevitable trend of modern power systems with the integration of large-scale renewable …
inevitable trend of modern power systems with the integration of large-scale renewable …
A survey of sparse mobile crowdsensing: Developments and opportunities
Sparse mobile crowdsensing (SMCS) has emerged as a promising sensing paradigm for
urban sensing, leveraging the spatial and temporal correlation among data sensed in …
urban sensing, leveraging the spatial and temporal correlation among data sensed in …
[HTML][HTML] Veracity assessment of online data
Fake news, malicious rumors, fabricated reviews, generated images and videos, are today
spread at an unprecedented rate, making the task of manually assessing data veracity for …
spread at an unprecedented rate, making the task of manually assessing data veracity for …
CovidSens: a vision on reliable social sensing for COVID-19
With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming
inherently important to disseminate accurate and timely information about the disease. Due …
inherently important to disseminate accurate and timely information about the disease. Due …
Fedsens: A federated learning approach for smart health sensing with class imbalance in resource constrained edge computing
The advance of mobile sensing and edge computing has brought new opportunities for
abnormal health detection (AHD) systems where edge devices such as smartphones and …
abnormal health detection (AHD) systems where edge devices such as smartphones and …
Crowdlearn: A crowd-ai hybrid system for deep learning-based damage assessment applications
Artificial Intelligence (AI) has been widely adopted in many important application domains
such as speech recognition, computer vision, autonomous driving, and AI for social good. In …
such as speech recognition, computer vision, autonomous driving, and AI for social good. In …
Socialdrone: An integrated social media and drone sensing system for reliable disaster response
Social media sensing has emerged as a new disaster response application paradigm to
collect real-time observations from online social media users about the disaster status. Due …
collect real-time observations from online social media users about the disaster status. Due …
On scalable and robust truth discovery in big data social media sensing applications
Identifying trustworthy information in the presence of noisy data contributed by numerous
unvetted sources from online social media (eg, Twitter, Facebook, and Instagram) has been …
unvetted sources from online social media (eg, Twitter, Facebook, and Instagram) has been …
On fine-grained geolocalisation of tweets and real-time traffic incident detection
Recently, geolocalisation of tweets has become important for a wide range of real-time
applications, including real-time event detection, topic detection or disaster and emergency …
applications, including real-time event detection, topic detection or disaster and emergency …
A multi-modal graph neural network approach to traffic risk forecasting in smart urban sensing
Forecasting traffic accidents at a fine-grained spatial scale is essential to provide effective
precautions and improve traffic safety in smart urban sensing applications. Current solutions …
precautions and improve traffic safety in smart urban sensing applications. Current solutions …