Published in Personal and Ubiquitous Computing
In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million d...
Published in Personal and Ubiquitous Computing
COVID-19 has caused a serious impact on the global economy. Effectively stimulating consumption has become a momentous mission in responding to the impact of the epidemic. The popularity of mobile shopping makes shopping behavior no longer limited by time and space, so impulse purchase is more commonly seen nowadays; it can effectively promote resi...
Published in Personal and Ubiquitous Computing
Bluetooth (BT) data has been extensively used for recognizing social patterns and inferring social networks, as BT is widely present in everyday technological devices. However, even though collecting BT data is subject to random noise and may result in substantial measurement errors, there is an absence of rigorous procedures for validating the qua...
Published in Personal and Ubiquitous Computing
Face detection perceives great importance in surveillance paradigm and security paradigm areas. Face recognition is the technique to identify a person identity after face detection. Extensive research has been done on these topics. Another important research problem is to detect concealed faces, especially in high-security places like airports or c...
Published in Personal and Ubiquitous Computing
In large-scale emotional events and complex emotional recognition applications, how to improve the recognition accuracy, computing efficiency, and user experience quality becomes the first problem to be solved. Aiming at the above problems, this paper proposes an emotional computing algorithm based on cross-modal fusion and edge network data incent...
Published in Personal and Ubiquitous Computing
Published in Personal and Ubiquitous Computing
We investigate the predictability of the next unlock event on smartphones, using machine learning and smartphone contextual data. In a 2-week field study with 27 participants, we demonstrate that it is possible to predict when the next unlock event will occur. Additionally, we show how our approach can improve accuracy and energy efficiency by sole...
Published in Personal and Ubiquitous Computing
Frequently, people with dementia exhibit abnormal behaviors that may cause self-injury or burden their caregivers. Some audible manifestations of these problematic behaviors are of vocal nature (e.g., shouting, mumbling, or cursing), others are environmental sounds (e.g., tapping or slamming). The timely detection of these behaviors could enact non...
Published in Personal and Ubiquitous Computing
As a nonverbal body language, gestures undoubtedly can play a very significant role when interacting with smart devices. One of the most discrete ways of gesture recognition is through the use of Wi-Fi signals. Recent literatures start to explore the feasibility of utilizing the widely deployed Wi-Fi infrastructure to track human motions and intera...
Published in Personal and Ubiquitous Computing
In today’s dynamic environment, an appropriate performance evaluation method for industries is a complex problem considering its funding scale. Performance evaluation in present industries has become a key part of the strategic approach. Existing performance evaluation approaches are based on manual estimations. These are prone to bias and nepotism...
