Related papers: SASE: Complex Event Processing over Streams
The increasing variety of input data and complexity of tasks that are handled by the devices of internet of things (IoT) environments require solutions that consider the limited hardware and computation power of the edge devices. Complex…
Complex event processing systems process the input event streams on-the-fly. Since input event rate could overshoot the system's capabilities and results in violating a defined latency bound, load shedding is used to drop a portion of the…
We present CASE, an open-source framework for adaptive participatory research and disease surveillance. Unlike traditional survey platforms with static branching logic, CASE uses an event-driven architecture that adjusts survey workflows in…
In this paper, we develop a scalable system which can do real-time analytics for different health applications. The occurrence of different health conditions can be regarded as the complex events and thus this concept can be extended to…
Searching for all occurrences of a pattern in a text is a fundamental problem in computer science with applications in many other fields, like natural language processing, information retrieval and computational biology. In the last two…
Today, massive amounts of streaming data from smart devices need to be analyzed automatically to realize the Internet of Things. The Complex Event Processing (CEP) paradigm promises low-latency pattern detection on event streams. However,…
Autonomous systems (AS) are systems that have the capability to take decisions free from direct human control. AS are increasingly being considered for adoption for applications where their behaviour may cause harm, such as when used for…
Event extraction (EE) is a fundamental task in natural language processing (NLP) that involves identifying and extracting event information from unstructured text. Effective EE in real-world scenarios requires two key steps: selecting…
Complex Event Recognition (CER) systems have become popular in the past two decades due to their ability to "instantly" detect patterns on real-time streams of events. However, there is a lack of methods for forecasting when a pattern might…
Active event perception, the ability to dynamically detect, track, and summarize events in real time, is essential for embodied intelligence in tasks such as human-AI collaboration, assistive robotics, and autonomous navigation. However,…
As modern software systems expand in scale and complexity, the challenges associated with their modeling and formulation grow increasingly intricate. Traditional approaches often fall short in effectively addressing these complexities,…
Due to intelligent, adaptive nature towards various operations and their ability to provide maximum comfort to the occupants residing in them, smart buildings are becoming a pioneering area of research. Since these architectures leverage…
Deep learning systems have become increasingly energy- and computation-intensive, raising concerns about their environmental impact. As organizers of the Detection and Classification of Acoustic Scenes and Events (DCASE) challenge, we…
In this paper, we present an approach to Complex Event Processing (CEP) that is based on DeepProbLog. This approach has the following objectives: (i) allowing the use of subsymbolic data as an input, (ii) retaining the flexibility and…
Several alternatives for more efficient spectrum management have been proposed over the last decade, resulting in new techniques for automatic wideband spectrum sensing. However, while spectrum sensing technology is important,…
In modern advanced emergency management systems many solutions for decision support have been provided as attempts to support humans to take important decisions for the critical situations recovery. The critical situation detection is a…
Event extraction (EE) is a crucial information extraction task that aims to extract event information in texts. Most existing methods assume that events appear in sentences without overlaps, which are not applicable to the complicated…
Event management in sensor networks is a multidisciplinary field involving several steps across the processing chain. In this paper, we discuss the major steps that should be performed in real- or near real-time event handling including…
Although synthetic aperture imaging (SAI) can achieve the seeing-through effect by blurring out off-focus foreground occlusions while recovering in-focus occluded scenes from multi-view images, its performance is often deteriorated by dense…
Complex Event Processing (CEP) is a stream processing model that focuses on detecting event patterns in continuous event streams. While the CEP model has gained popularity in the research communities and commercial technologies, the problem…