TY - GEN
T1 - Indoor Wayfinding for an Electric Wheelchair Based on Wi-Fi Fingerprinting Localization
AU - Luces, Jose Victorio Salazar
AU - Promsutipong, Kengkij
AU - Hirata, Yasuhisa
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - Currently, society is experiencing a shift in the median age known as population aging. The number of people aged 60 years or over is at its highest, and it's expected to double by 2050. With age, people frequently experience difficulties in mobility, requiring them to use assistive technology, from wearable devices to mobile devices such as wheelchairs or walkers. Recently, power-assisted versions of these systems have been developed to further enhance the provided assistance, such as electric wheelchairs and power-assisted walkers. In scenarios such as shopping malls or airports, people often need to walk long distances to reach their destination, so these power-assisted systems can help them move without difficulties. However, these systems are still quite expensive, and having one device per user might prove difficult. To overcome this, these facilities could have a reduced number of devices and allow users to share them upon request. However, it's not desirable to have each user move toward the assistive device due to their limited mobility. Instead, in this research we propose a method to enable the device to navigate toward the user upon request by using onboard sensors and the existing Wi-Fi infrastructure. Specifically, we create a map with the Received Signal Strength Indicator (RSSI) of existing Wi-Fi access points (using a method called Fingerprinting). When a user requests an assistive device, the RSSI values at the user's position are sent to it, and the device determines the rough position of the user using a KNN algorithm. However, typical Fingerprinting methods are affected by infrastructural changes which alter the profile of RSSI values at each location. Therefore, we propose that the map is constantly updated while the device moves in order to avoid errors due to changes in the infrastructure. Through experiments we confirmed that the device could locate the position where the request originated with an error of 2.612 m, and it was able to navigate towards it.
AB - Currently, society is experiencing a shift in the median age known as population aging. The number of people aged 60 years or over is at its highest, and it's expected to double by 2050. With age, people frequently experience difficulties in mobility, requiring them to use assistive technology, from wearable devices to mobile devices such as wheelchairs or walkers. Recently, power-assisted versions of these systems have been developed to further enhance the provided assistance, such as electric wheelchairs and power-assisted walkers. In scenarios such as shopping malls or airports, people often need to walk long distances to reach their destination, so these power-assisted systems can help them move without difficulties. However, these systems are still quite expensive, and having one device per user might prove difficult. To overcome this, these facilities could have a reduced number of devices and allow users to share them upon request. However, it's not desirable to have each user move toward the assistive device due to their limited mobility. Instead, in this research we propose a method to enable the device to navigate toward the user upon request by using onboard sensors and the existing Wi-Fi infrastructure. Specifically, we create a map with the Received Signal Strength Indicator (RSSI) of existing Wi-Fi access points (using a method called Fingerprinting). When a user requests an assistive device, the RSSI values at the user's position are sent to it, and the device determines the rough position of the user using a KNN algorithm. However, typical Fingerprinting methods are affected by infrastructural changes which alter the profile of RSSI values at each location. Therefore, we propose that the map is constantly updated while the device moves in order to avoid errors due to changes in the infrastructure. Through experiments we confirmed that the device could locate the position where the request originated with an error of 2.612 m, and it was able to navigate towards it.
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U2 - 10.1109/SII46433.2020.9025862
DO - 10.1109/SII46433.2020.9025862
M3 - Conference contribution
AN - SCOPUS:85082583737
T3 - Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020
SP - 513
EP - 518
BT - Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/SICE International Symposium on System Integration, SII 2020
Y2 - 12 January 2020 through 15 January 2020
ER -