Monitoring vehicle plate detection in Brazilian Universities - Santos, Daniel; Claro, Daniela Barreiro; Gondim, João (Anais do Simpósio Brasileiro de Sistemas de Informação (SBSI), 2023)
Context: With the growth of smart cities, surveillance camera systems have increased their monitoring capacity in different environments. In public Universities, monitoring requires subtle and precise alerts, in order to curb actions that may present a lack of security for the academic community. Problem: Although the detection objects in videos is possible, the high cost of acquiring, installing high-quality cameras and machines capable of executing high-precision models of customized solutions is expensive. In addition, most solutions achieve high precision in controlled environments, with high resolution still images, and focus on objects, which does not portray the reality of surveillance cameras in Universities. Solution: Faced with this problem, the objective is to build a Automatic License Plate Recognition system(ALPR) to control vehicles entering and leaving Universities. It is proposed to interoperate with camera systems in order to alert the competent authorities. Information systems theory: This work was conceived under the General Theory of Systems with regard to interoperate with already existing heterogeneous systems. Furthermore, as part of the theory of socio-technical systems, this approach aims to improve the performance of the organization, offering improvements in the productivity of the task due to the alerts of the offered approach. Method: This research is descriptive and its evaluation is done through proof of concept. Results: The artifact developed showed good performance, allowing to recognize license plates in surveillance cameras with 76.6% accuracy. Contributions and Impact in the area of information systems: Our main contribution is the artifact to detect vehicles. A secondary contribution is our dataset with Old and Mercosul Plaques versions. Such method impacts the three pilars from IS area: People, Process and Technology.