Rule based complex event processing for IoT applications: Review, classification and challenges
In recent decades, data aggregation and correlation have emerged as a significant and
challenging area of research for finding useful relationships between different features of …
challenging area of research for finding useful relationships between different features of …
UWHear: Through-wall extraction and separation of audio vibrations using wireless signals
An ability to detect, classify, and locate complex acoustic events can be a powerful tool to
help smart systems build context-awareness, eg, to make rich inferences about human …
help smart systems build context-awareness, eg, to make rich inferences about human …
DeepProbCEP: A neuro-symbolic approach for complex event processing in adversarial settings
Detecting complex events from subsymbolic data streams (such as images, audio
recordings or videos) is a challenging problem, as traditional symbolic approaches cannot …
recordings or videos) is a challenging problem, as traditional symbolic approaches cannot …
The synergy of complex event processing and tiny machine learning in industrial IoT
Focusing on comprehensive networking, the Industrial Internet-of-Things (IIoT) facilitates
efficiency and robustness in factory operations. Various intelligent sensors play a central …
efficiency and robustness in factory operations. Various intelligent sensors play a central …
Neuroplex: learning to detect complex events in sensor networks through knowledge injection
Despite the remarkable success in a broad set of sensing applications, state-of-the-art deep
learning techniques struggle with complex reasoning tasks across a distributed set of …
learning techniques struggle with complex reasoning tasks across a distributed set of …
Semirings for probabilistic and neuro-symbolic logic programming
The field of probabilistic logic programming (PLP) focuses on integrating probabilistic
models into programming languages based on logic. Over the past 30 years, numerous …
models into programming languages based on logic. Over the past 30 years, numerous …
ENSURE: A deep learning approach for enhancing situational awareness in surveillance applications with ubiquitous high-dimensional sensing
VK Garg, TL Wickramarathne - IEEE Journal of Selected Topics …, 2022 - ieeexplore.ieee.org
Judicious processing of High-Dimensional Sensing (HDS) data streams is often the first step
in a data-driven decision-support system. However, how one goes about processing large …
in a data-driven decision-support system. However, how one goes about processing large …
Deep convolutional bidirectional lstm for complex activity recognition with missing data
Complex activity recognition using multiple on-body sensors is challenging due to missing
samples, misaligned data times tamps across sensors, and variations in sampling rates. In …
samples, misaligned data times tamps across sensors, and variations in sampling rates. In …
Cepair: an AI-powered and fog-based predictive CEP system for air quality monitoring
Air pollution is one of the influential problems threatening the environment and human
health today. Therefore, it is critical to develop predictive systems for proactive decisions in …
health today. Therefore, it is critical to develop predictive systems for proactive decisions in …
A neuro-symbolic approach to structured event recognition
Events are structured entities with multiple components: the event type, the participants with
their roles, the outcome, the sub-events etc. A fully end-to-end approach for event …
their roles, the outcome, the sub-events etc. A fully end-to-end approach for event …