Simulating Wave Propagation Distribution Through GIS Integration-Reference-Cited by-同舟云学术

Simulating Wave Propagation Distribution Through GIS Integration

Published:2021-07-07 Issue: Volume:18 Page:82-90
ISSN:2224-3402
Container-title:WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
language:en
Short-container-title:

Author:

Manrique Luis Carlos¹,Weiss Anthony¹,Puentes Sandra¹

Affiliation:

1. Data scientist, Engineer, Assistant professor Credit Engine Inc., Moneytree Inc., The University of Tsukuba Tokyo Minato-ku Roppongi 7-15-7, Tokyo Minato-ku Castalia 2F, 3-13-3 Nishiazabu Ibaraki Prefecture Tsukuba 1-1-1 Tennodai JAPAN

Abstract

The use of electronic devices designed for user location estimation has become widely popular in the last decade. This is thanks to emergent technologies such as Bluetooth Low Energy, Radio-Frequency Identification, and Ultra-WideBand (UWB) among others. In the present study; the authors provide a method for using a Geographic Information System (GIS) to define spatial constraints, in order to simulate the lines of sight of anchors to make an informed selection of adequate locations for installation. By leveraging GIS, researchers or enterprises can improve the installation process by reducing costs while setting up arrangements that will ensure reliable data collection. We include a scenario illustrating the possibility of budget reduction of around 30% related to the orientation and survey of the devices.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

Computer Science Applications,Information Systems

Reference31 articles.

1. Rahayu, Yusnita and Abd Rahman, et al., 2008 5th IFIP International Conference on Wireless and Optical Communications Networks (WOCN ’08), doi: 10.1109/WOCN.2008.4542537, 2008.

2. Nguyen, C. and Miao, M., Fundamentals of UWB Impulse Systems. Design of CMOS RFIC Ultra-Wideband Impulse Transmitters and Receivers, Springer International Publishing, 2017.

3. Abdulrahman Alarifi and AbdulMalik S and et al, Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances, Sensors (Basel), doi: 10.3390/s16050707, 2016.

4. Gabriel-Adrian Deak and Kevin Curran and Joan Condell, Filters for RSSI-based measurements in a Device-free Passive Localisation Scenario, Image Processing and Communications, Vol.15, No.1, 2010, pp. 23–34.

5. Barrett, S., Optimizing Sensor Placement for Intruder Detection with Genetic Algorithms, IEEE Intelligence and Security Informatics, 2007, pp. 185-188, doi: 10.1109/ISI.2007.379555.