Honorable Mention
Parcel lockers have become an increasingly prevalent last-mile delivery method. However, a recent study revealed their accessibility challenges to blind and low-vision (BLV) people. Informed by the study, we designed FetchAid, a standalone intelligent mobile app assisting BLV in using a parcel locker in real-time by integrating computer vision and augmented reality (AR) technologies. FetchAid first uses a deep network to detect the user's fingertip and relevant buttons on the touch screen of the parcel locker to guide the user to reveal and scan the QR code to open the target compartment door and then interactively guide the user to reach the door safely with AR-based context-aware audio feedback. Moreover, FetchAid provides an error-recovery mechanism and real-time feedback to keep the user on track. We evaluated it with 12 BLV people and found that FetchAid substantially improved task accomplishment and efficiency, and reduced frustration and overall effort.
doi.org/10.1145/3613904.3642213
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)