Application to Guide People with Visual Disability on Internal Buildings, Using Beacon Bluetooth Positioning Systems
In the actuality there are many devices to help people with visual disability, at the level of mobile devices like Smart Phones, tablets, PCS, some of them increasing the size of the letter, or reading icons or maybe incorporating voice technology to read the text or to recognize the voice, these devices help to people with visual disability that they can interact and do things that people couldn’t do every day, helping their day by day, and above all do activities of interaction of man with machine. Additionally there are several applications that incorporate GPS navigation technology, for localization and geography location, one person can use navigation applications for be able to locate even using just the GPS module without the need to have internet connection, little by little this service has become very popular, it is include in autonomous cars, to be able to go to one place to another easily, just showing the destination the people are directed without the need to drive, however this system doesn’t work inside of the buildings or internal structures because the GPS signal could be lost and the navigation and obtaining the location is not accurate.
The propose of this article is for the use of beacons with techniques based on the received signal strength indication (RSSI), also distance mediation techniques to calculate the exact position of the individual, solving the lost signal of GPS devices, this calculation is done using triangulation algorithms to get the localization, Additionally, it was used beacons, this devices are operate with Bluetooth technology 4.0, and by not having GPS location antenna this devices can be obtained a proximity value and distance to the beacon using UUID, and proximity, connecting to an Smart Phone device or a tablet to the connection through the Bluetooth, In addition an application was developed using Studio Android and a library called proximi.io this library is absolutely compatible with IOS and Android, this application connects to a database to determinate the position and identify the beacons, Additionally to identify the location of the individual through his Smart We use a triangulation algorithm to obtain data with greater precision it is necessary to use at least 3 beacons, to complete the study, were performed test in corridors of buildings and several places obtaining good results it could be verified that the triangulation algorithm with some improvement variants facilitates to obtain the location with greater effectiveness in general, for our purpose it was possible to determine that is feasible to use these devices in favor of people with visual disabilities, you can use many projects with beacons and applications in public places such as hospitals, airports, educational institutions, museums, shopping centers, etc.,. In short, the application is very broad and many benefits can be obtained.
The authors would like to thank Fabricio Lara for proofreading the English translation of this paper.
- 1.RNIB: RNIB, 21 April 2016. [En línea]. https://www.rnib.org.uk/insight-online/facebook-twitter-accessibility-features. Último acceso 01 Aug 2018
- 2.Lahuerta Orte, M.: OwnFone lanza el primer teléfono Braille personalizable. ComputerHoy, España (2014)Google Scholar
- 3.Thompson, R., Stovall, J., Velasquez, D., Rupa, A., Samaylov, A.: All-in-One Urban Mobility Mapping Application with Optional Routing Capabilities. IEEE (2019)Google Scholar
- 4.Yang, L.: Positioning in an Indoor Environment Based on iBeacons. IEEE (2016)Google Scholar
- 5.APPLE: APPLE, 5 August 2017. [En línea]. https://support.apple.com/en-gb/HT202880
- 6.Safari, F., Papapanagiotou, F., Devetsikiotis, M., Hacker, T.: An iBeacon based Proximity and Indoor Localization System. Computing Research Repository. de Computing Research Repository (2017)Google Scholar
- 7.Eddystone: Eddystone, 01 November 2018. [En línea]. https://developer.estimote.com/eddystone/
- 8.Phisical Web: Phisical Web, 01 April 2017. [En línea]. https://google.github.io/physical-web/
- 9.R. Network: guithub, 29 November 2017. [En línea]. https://github.com/AltBeacon/android-beacon-library
- 10.Yu, K., Ji, L., Sang, X.: Kernel Nearest-Neighbor Algorithm (2002)Google Scholar