Related papers: A methodology and a platform for high-quality rich…
Consumer applications are becoming increasingly smarter and most of them have to run on device ecosystems. Potential benefits are for example enabling cross-device interaction and seamless user experiences. Essential for today's smart…
Applications in the Internet of Things (IoT) utilize machine learning to analyze sensor-generated data. However, a major challenge lies in the lack of targeted intelligence in current sensing systems, leading to vast data generation and…
Understanding student behaviour in higher education is essential for improving academic performance, supporting mental well-being, and informing institutional policies. However, most existing behavioural datasets originate from Western…
Smart video sensors for applications related to surveillance and security are IOT-based as they use Internet for various purposes. Such applications include crowd behaviour monitoring and advanced decision support systems operating and…
Autonomous driving algorithms rely heavily on learning-based models, which require large datasets for training. However, there is often a large amount of redundant information in these datasets, while collecting and processing these…
Dynamic analysis has emerged as a pivotal technique for testing Android apps, enabling the detection of bugs, malicious code, and vulnerabilities. A key metric in evaluating the efficacy of tools employed by both research and practitioner…
This paper presents a data-centric and security-focused data fabric designed for digital health applications. With the increasing interest in digital health research, there has been a surge in the volume of Internet of Things (IoT) data…
In this article, we present a distributed framework for collecting and analyzing environmental and location data recorded by human users (carriers) with the use of portable sensors. We demonstrate the data mining analysis potential among…
The prevalent engagement with mobile apps underscores the importance of understanding their data practices. Transparency plays a crucial role in this context, ensuring users to be informed and give consent before any data access occurs.…
The widespread diffusion of connected smart devices has contributed to the rapid expansion and evolution of the Internet at its edge. Personal mobile devices interact with other smart objects in their surroundings, adapting behavior based…
In this short paper, we explore the enrichment of event logs with data from wearable devices. We discuss three approaches: (1) treating wearable data as event attributes, linking them directly to individual events, (2) treating wearable…
Mixed Reality (MR) and Artificial Intelligence (AI) are increasingly becoming integral parts of our daily lives. Their applications range in fields from healthcare to education to entertainment. MR has opened a new frontier for such fields…
This study presents high-throughput, real-time multi-agent affective computing framework designed to enhance classroom learning through emotional state monitoring. As large classroom sizes and limited teacher student interaction…
The importance of big data is a contested topic among social scientists. Proponents claim it will fuel a research revolution, but skeptics challenge it as unreliably measured and decontextualized, with limited utility for accurately…
Large Language Models (LLMs) enable unprecedented social science experimentation by creating controlled hybrid human-AI environments. We introduce Epitome (www.epitome-ai.com), an open experimental platform that operationalizes this…
Recent progress in imitation learning from human demonstrations has shown promising results in teaching robots manipulation skills. To further scale up training datasets, recent works start to use portable data collection devices without…
Datasets sourced from people with disabilities and older adults play an important role in innovation, benchmarking, and mitigating bias for both assistive and inclusive AI-infused applications. However, they are scarce. We conduct a…
IoT devices and sensors have been utilized in a cooperative manner to enable the concept of a smart environment. In these smart settings, abundant data is generated as a result of the interactions between devices and users' day-to-day…
For decades, the growth and volume of digital data collection has made it challenging to digest large volumes of information and extract underlying structure. Coined 'Big Data', massive amounts of information has quite often been gathered…
The emergence of "big data" offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery. Scientific progress in many disciplines is increasingly enabled by our ability to examine…