Walpola Layantha Perera

Xiao Ni, Walpola Layantha Perera, Carsten Kühnel et al.

We propose a vision-based warning system for the maintenance personnel working on short-term construction sites. Traditional solutions use passive protection, like setting up traffic cones, safety beacons, or even nothing. However, such methods cannot function as physical safety barriers to separate working areas from used lanes. In contrast, our system provides active protection, leveraging acoustic and visual warning signals to help road workers be cautious of approaching vehicles before they pass the working area. To decrease too many warnings to relieve a disturbance of road workers, we implemented our traffic flow check algorithm, by which about 80% of the useless notices can be filtered. We conduct the evaluations in laboratory conditions and the real world, proving our system's applicability and reliability.

H. P. Savindu, K. A. Iroshan, C. D. Panangala et al.

Visually impaired people are neglected from many modern communication and interaction procedures. Assistive technologies such as text-to-speech and braille displays are the most commonly used means of connecting such visually impaired people with mobile phones and other smart devices. Both these solutions face usability issues, thus this study focused on developing a user friendly wearable solution called the "BrailleBand" with haptic technology while preserving affordability. The "BrailleBand" enables passive reading using the Braille language. Connectivity between the BrailleBand and the smart device (phone) is established using Bluetooth protocol. It consists of six nodes in three bands worn on the arm to map the braille alphabet, which are actuated to give the sense of touch corresponding to the characters. Three mobile applications were developed for training the visually impaired and to integrate existing smart mobile applications such as navigation and short message service (SMS) with the device BrailleBand. The adaptability, usability and efficiency of reading was tested on a sample of blind users which reflected progressive results. Even though, the reading accuracy depends on the time duration between the characters (character gap) an average Character Transfer Rate of 0.4375 characters per second can be achieved with a character gap of 1000 ms.