  Smartphones have become essential to people's digital lives, providing a
continuous stream of information and connectivity. However, this constant flow
can lead to moments where users are simply passing time rather than engaging
meaningfully. This underscores the importance of developing methods to identify
these "time-killing" moments, enabling the delivery of important notifications
in a way that minimizes interruptions and enhances user engagement. Recent work
has utilized screenshots taken every 5 seconds to detect time-killing
activities on smartphones. However, this method often misses to capture phone
usage between intervals. We demonstrate that up to 50% of time-killing
instances go undetected using screenshots, leading to substantial gaps in
understanding user behavior. To address this limitation, we propose a method
called ScreenTK that detects time-killing moments by leveraging continuous
screen text monitoring and on-device large language models (LLMs). Screen text
contains more comprehensive information than screenshots and allows LLMs to
summarize detailed phone usage. To verify our framework, we conducted
experiments with six participants, capturing 1,034 records of different
time-killing moments. Initial results show that our framework outperforms
state-of-the-art solutions by 38% in our case study.
