Location-aware smart campus security application
Publication Date
June 2018
Document Type
Article
Publication Title
2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
DOI
10.1109/UIC-ATC.2017.8397588
Abstract
One of the biggest challenges that Universities face today is the safety of its people on campus from crimes like mugging, battery and even shooting in or around the campus area. Using SJSU campus as an example, over 50 alert cases of burglaries, thefts, batteries, sexual assaults and other incidents have been reported in and around the SJSU campus over the last year. We have Bluelight emergency telephones placed all over the campus, in all buildings, elevators and on the campus grounds. These phones can be used to report emergency situations, suspicious activities, request escorts etc. However, there is a huge delay between the occurrence of incidents and the arrival of the policeman at the site. There is a critical need for a system that would allow the authorities to locate victims and respond faster to these incidents. To reduce the delay in reporting incidents and their occurrence time, we have developed a mobile application that will let users send alerts along with their real-time location to the UPD directly from their mobile phones. However, finding the position of a victim in a building is the most important challenge we are facing. Many existing systems do not work in indoor environment, and the state-of-the-art localization systems are either inconvenience to use or inaccurate enough to pin-point user's locations inside the building. In this paper, we propose a fine-grained location-aware smart campus security systems that leverages hybrid localization approaches with minimum deployment cost. Specifically, we effectively combines the Wi-Fi fingerprinting localization approach with the Bluetooth beacon based trilateration approach, and improves the location accuracy to the meter-level with low cost.
Recommended Citation
Kaikai Liu, Navjot Warade, Tejas Pai, and Keertikeya Gupta. "Location-aware smart campus security application" 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (2018). https://doi.org/10.1109/UIC-ATC.2017.8397588
