  With the widespread adoption of smartphones, ensuring pedestrian safety on
roads has become a critical concern due to smartphone distraction. This paper
proposes a novel and real-time assistance system called UWB-assisted Safe Walk
(UASW) for obstacle detection and warns users about real-time situations. The
proposed method leverages Impulse Radio Ultra-Wideband (IR-UWB) radar embedded
in the smartphone, which provides excellent range resolution and high noise
resilience using short pulses. We implemented UASW specifically for Android
smartphones with IR-UWB connectivity. The framework uses complex Channel
Impulse Response (CIR) data to integrate rule-based obstacle detection with
artificial neural network (ANN) based obstacle classification. The performance
of the proposed UASW system is analyzed using real-time collected data. The
results show that the proposed system achieves an obstacle detection accuracy
of up to 97% and obstacle classification accuracy of up to 95% with an
inference delay of 26.8 ms. The results highlight the effectiveness of UASW in
assisting smartphone-distracted pedestrians and improving their situational
awareness.
