From SMT Project Experience
Jump to navigation
Jump to search
|
|
| Line 21: |
Line 21: |
| | |} | | |} |
| | <!--/MENU--> | | <!--/MENU--> |
| − |
| |
| − | ==Project Background==
| |
| − | An inclusive smart city is a citizen-centered approach that extends the experiences provided by smart city solutions to all citizens, including seniors and persons with disabilities (PwDs). Despite existing regulations on barrier-free accessibility for buildings and public infrastructure, pedestrian infrastructure is generally still inaccessible to PwDs in many parts of the world.
| |
| − |
| |
| − | SmartBFA (Smart Mobility and Accessibility for Barrier Free Access) is a publicly-funded initiative in Singapore that aims to design a scalable and sustainable system that can collect, classify and determine accessible point-to-point routes to address interconnection gaps in first and last mile BFA paths for persons requiring barrier-free access (such as wheelchair users and seniors with mobility aids). In SmartBFA, point-to-point accessibility information is passively crowdsourced from IoT devices that are retrofitted on the wheelchairs of participants, as they go about their daily commute. The original SmartBFA team has already shared preliminary findings from data acquired from 68 wheelchair participants between May 2018 to Mar 2019, spanning across 23,000 hrs and 40,000 km of traveled paths. The team also aims to compare travel patterns of participants with varying wheelchair types, as well as demonstrate the feasibility and scalability of such a crowdsourced approach for acquiring accessibility data.
| |
| − |
| |
| − | ==Participant Demographics==
| |
| − | A total of 68 unique wheelchair participants are recruited between May 2018 to Mar 2019 across a total of 5 runs, with each run spanning 8 weeks. Table I summarizes the demographic statistics of the participants. Survey results reveal that the top 3 obstacles that participants fear the most are uneven ground (52.9%), small steps (50.0%) and ramps/slopes (41.2%). 28% of participants with motorized wheelchairs indicate that they do not fear obstacles, as compared to only 5.6% for those with manual wheelchairs. This highlights that the former are more confident than the latter when traveling outdoors. In addition, participants rate themselves as doing fairly well in terms of levels of opportunity and participation in social and family life, but much less in economic and community life.
| |
| − |
| |
| − | [[File:Participant.png|500px|thumb|center|TABLE I: Demographic statistics of the 68 unique wheelchair participants in the study between May 2018 to Mar 2019.]]
| |
| − |
| |
| − | ==Data Collection from Wheelchair==
| |
| − | The IoT device is mounted on a fixed location on the wheelchair that is non-obstructive for the participant; the mounting location may vary slightly depending on the wheelchair model. Each IoT device comprises a Raspberry Pi 3B+ as the single-board computer (SBC), GlobalSat BU-353S4 USB GPS receiver, Adafruit LSM9DS1 Inertial Measurement Unit (IMU), Adafruit DS3231 Real-Time Clock (RTC) and portable power bank. The IMU provides accelerometer and gyroscope readings, which are used to measure the angle and minute differences in vibrations that are experienced by the wheelchair as it traverses across pedestrian paths with varying surface conditions. The readings from the GPS and IMU are captured at frequencies of 1 Hz and 200 Hz respectively and cached on the SBC. The cached data is opportunistically published to the backend server via MQTT [25] - a lightweight publish-subscribe messaging paradigm - whenever pre-configured WiFi connectivity is detected by the SBC.
| |
Revision as of 20:42, 13 August 2020
