[NJTechDiv] Fwd: [tech-vi Announce List] Microsoft mobile app is making bus stops more accessible

[Mario Brusco]

-------- Forwarded Message --------
From: David Goldfield [mailto:david.goldfield at outlook.com]
Subject: [tech-vi Announce List] Microsoft mobile app is making bus 
stops more accessible
Date: Monday, April 25, 2022, 9:47 AM
To: List <tech-vi at groups.io>
COOL BLIND TECH - Monday, April 25, 2022 at 9:01 AM


   Microsoft mobile app is making bus stops more accessible

A team at Schepens Eye Research Institute of Mass Eye and Ear, led by 
Associate Professor Gang Luo, has been focusing on vision assistive 
technology for over a decade, running research studies on technology 
development, intervention, evaluation, and human factors in mobility for 
people who are blind or low vision. While transit agencies have a 
mandate to improve accessibility to public transportation as part of the 
Americans with Disability Act, opportunities exist to improve existing 
technologies and further remove barriers. Developing a cost-effective 
tool was paramount for the team in their aim to make bus stops more 
accessible and easily identifiable to all.

In their effort, they have developed and released a free app called All 
Aboard <https://apps.apple.com/ca/app/all-aboard/id1580638469> which 
prototypes 10 bus transit services across the US, Canada, UK and Germany.


     How does the app work?

To use the app, a user needs to hold their mobile phone in upright 
orientation in proximity to the stop. The service will make a sonar-like 
sound to indicate it’s searching for the bus stop sign, followed by a 
beeping sound to indicate the bus stop was identified. The latter has 
different levels of pitch roughly representing various distances as 
demonstrated in this video tutorial. 
<https://www.youtube.com/watch?v=GYQd5DpsHys>


     How does the app recognize bus stop signs?

The All Aboard app used deep neural networks to recognize bus stop 
signs, with the assumption the user is aware of the bus route they wish 
to take and is in proximity of the bus stop. By using object 
recognition, it can correctly identify bus signs which have the same 
design for a particular transit, while ignoring the exact route number 
on the signs. For each bus transit, around 5,000 to 10,000 bus stop sign 
images were collected, labelled, and used to train the neural network to 
automatically learn the features of the signage patterns. 
Consequentially, the neural network is capable of differentiating the 
bus stop signs from other objects and other types of road signs in 
images. For the recognition neural network to run in real time on a 
mobile device with lower computational power, a lightweight neural 
network was created, allowing processing on a mobile device.


     What has been the feedback from users?

Since its release in December 2021, the app has been used by more than 
130 users in over 1,500 instances across the US, Canada, Germany and the 
UK. The preliminary results are encouraging; based on the team’s 
research, the rate of successful navigation of main stream navigation 
apps averages at 60%, while All Aboard had a 95% detection of bus stops 
signs. The main stream apps failed mostly in urban area with many high 
rises. Even for successful navigation instances, All Aboard was able to 
lead users to bus stops more precisely.


     What is next up for the app?

Next up for the app is a plan to expand coverage of bus transit services 
to more cities in the US, as well as make it available on Android, and 
build new futures for navigation such as subways, and other popular 
destinations.

Source 
<https://blogs.microsoft.com/accessibility/all-aboard-an-ai-based-mobile-app-is-making-bus-stops-more-accessible/>

https://coolblindtech.com/microsoft-mobile-app-is-making-bus-stops-more-accessible/ 
<https://coolblindtech.com/microsoft-mobile-app-is-making-bus-stops-more-accessible/>



       David Goldfield
Assistive Technology Specialist

Feel free to visit my Web site
WWW.DavidGoldfield.info