IoT na segurança pública como técnica para identificar furto e roubo de veículos em ambiente Smart Campus

Abstract

Along with the areas of health and education, public safety is one of the main social concerns of the Brazilian population. In recent years, Brazil has become a country with high crime rates, which directly affects socio-economic behavior within the national territory. In contrast to the scenario of safety indices, smart cities provide increasingly better living conditions and access to culture for the population. Following this same model are the smart campuses, which have needs similar to those found in cities and take advantage of the potential of the academic community to develop solutions to the most relevant local problems. In smart environments, Bluetooth is one of the main technologies that contributes to the creation of loT applications, especially after version 4 that introduced BLE (Bluetooth Low Energie). It was after this version that BLE beacon devices appeared, which enabled the use of the so-called indoor location. Its main characteristic is the ability to provide data on the approximation between devices through the emission of signals, which can be generated and also identified by any program executed in a device that has BLE technology. Most applications found in the bibliography that employ approximation point to use at short distances and on fixed objects, not taking advantage of the full capacity of the devices. Furthermore, they highlight problems with oscillation of these signals, making it difficult to implement certain functionalities. In this context, a research with an experimental approach was carried out, seeking to enable the use of loT in order to identify theft and robbery of vehicles in a smart campus environment through BLE beacons. Two experiments were carried out in an open environment, the first one seeks to identify the area of ​​operation of the devices; and observe the oscillation behavior of signals in order to draw a strategy for the development of an application that can identify the movement of a beacon. The second experiment was carried out with an application that manages the monitoring of a BLE beacon installed inside a vehicle, which, when moving during the surveillance period, causes the system to identify its movement and issue a risk alert indicating that the vehicle is at risk.