Smart Solutions for Blind Bus Riders
Using IoT to aid visually impaired individuals in urban transport.
Nádia Aparecida de Oliveira Silva, Rodrigo Moreira, Larissa Ferreira Rodrigues, Rafael Marinho e Silva
― 4 min read
Table of Contents
Urban mobility can be a tough challenge, especially for people with visual impairments. Imagine trying to catch a bus when you can’t see the bus stop or the approaching vehicle. This is a daily struggle for many visually impaired individuals. However, with advancements in technology, there are ways to make their travel easier and safer. One such technological approach involves using the Internet of Things (IoT) to improve urban mobility for these individuals.
What is IoT?
The Internet of Things (IoT) refers to the connection of everyday objects to the internet. This can include anything from smart home devices to cars that can communicate with each other. In the case of urban mobility, IoT can help create systems that provide real-time information about public transport, making it easier for people to navigate their environment.
The Problem
Approximately 2.2 billion people around the world have some form of visual impairment. Out of these, around 1 billion could have been helped through early treatment or prevention. In Brazil, many people rely on buses for transportation, with a significant portion of the population using public transport for their daily activities. However, navigating this transport system can be difficult for those with visual impairments, which can lead to isolation and limited access to opportunities.
The Proposed Solution
To tackle this issue, a low-cost IoT architecture was proposed. This system utilizes small computers, known as Single-Board Computers (SBCs), to gather and transmit data about bus locations. The use of affordable technology makes this solution more accessible and suitable for various regions, especially in developing countries.
How Does it Work?
The architecture comprises several key components:
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GPS Sensors: These sensors are placed in buses to regularly send location information (like latitude and longitude) every five seconds.
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IoT Gateway: This is a Raspberry Pi that collects the location data from the buses and sends it to a cloud-based application.
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Mobile Application: Users can download an app that provides audible and mechanical notifications about bus proximity. This means that as a bus approaches, users will get alerts, making it easier for them to catch their ride.
Unique Features
What sets this architecture apart from other solutions is that it allows both visually impaired and sighted users to track bus routes on a map. This means everyone can benefit from the technology, making public transport more inclusive.
While other solutions have focused on individual locations and limited-range technologies, this system uses a long-range communication method, known as LoRa, which allows data to travel longer distances. This is particularly valuable in urban environments where distances can vary significantly.
Experimental Evaluation
To ensure the proposed architecture is effective, a series of tests were carried out. The goal was to measure how well the system could handle the data from public transport vehicles.
Test Setup
The tests involved sending different sizes of messages to the IoT gateway and measuring the response times. Researchers monitored how the system performed under various conditions, such as the number of buses sending data and the message quality.
Results
The findings were encouraging. As message size increased, a strong connection was found between message size and response time. In simple terms, bigger messages took longer to process. However, the system was still able to handle multiple messages without losing reliability.
Moreover, when looking at Quality Of Service (QoS) settings, which ensure messages are delivered reliably, the system showed varied results based on the number of buses in operation. For example, when only a few buses were sending data, there wasn't much impact on performance. However, with many active buses, resources were more challenged, leading to increased CPU usage.
Conclusion
This IoT architecture shows promise in improving urban mobility for visually impaired individuals. By making use of low-cost technology and real-time data, the system allows users to navigate public transport more effectively.
As with any new invention, there’s room for improvement. Future work may focus on exploring different methods of data transmission, such as using mobile networks, and further optimizing existing IoT gateways for even better performance.
In the grand scheme of things, making the world a bit more accessible for everyone should be a priority. And if that means using some smart gadgets to help people catch their bus, then we are all for it!
Original Source
Title: A Low-cost IoT Architecture to support Urban Mobility for Visually Impaired People
Abstract: People with visual impairments struggle with urban mobility and independent travel, opening up opportunities for technological advances to improve their quality of life. The Internet of Things (IoT) plays an essential role in bringing improvements and accessibility for visually impaired people. Although alternatives aimed to use IoT in urban mobility, those solutions are still in the initial stages and do not supports urban mobility for people with visual impairment. This paper proposed and evaluated a low-cost IoT architecture that uses Single-Border Computers (SBCs) to support urban mobility. A performance evaluation showcased that our low-cost architecture handles bus trace workload and is suitable for supporting impaired people to get information concerning bus location on Smart Cities scenarios.
Authors: Nádia Aparecida de Oliveira Silva, Rodrigo Moreira, Larissa Ferreira Rodrigues, Rafael Marinho e Silva
Last Update: 2024-12-15 00:00:00
Language: English
Source URL: https://arxiv.org/abs/2412.11363
Source PDF: https://arxiv.org/pdf/2412.11363
Licence: https://creativecommons.org/licenses/by/4.0/
Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.
Thank you to arxiv for use of its open access interoperability.