Car Monitoring System in Apartments’ Garages by Small Autonomous Car Using Deep Learning

Abstract

Currently, there is an increase in the number of Peruvian families living in apartments instead of houses for the lots of advantage; however, in some cases there are troubles such as robberies of goods that are usually left at the parking lots or the entrance of strangers that use the tenants parking lots (this last trouble sometimes is related to kidnappings or robberies in building apartments). Due to these problems, the use of a self-driving mini-car is proposed to implement a monitoring system of license plates in an underground garage inside a building using a deep learning model with the aim of recording the vehicles and identifying their owners if they were tenants or not. In addition, the small robot has its own location system using beacons that allow us to identify the position of the parking lot corresponding to each tenant of the building while the mini-car is on its way. Finally, one of the objectives of this work is to build a low cost mini-robot that would replace expensive cameras or work together in order to keep safe the goods of tenants.

Performing Deep Recurrent Double Q-Learning for Atari Games

“…Currently, there is an increase in the number in of applications in Reinforcement Learning. One recently application of Deep Reinforcement Learning (DRL) is self-driving cars [1], [2], another one is in games like AlphaZero (Go, Chess, etc) and video games like Mario, Top racer, Atari, etc. Deep Reinforcement Learning is considered as a third model in Machine Learning (with Supervised Learning and Unsupervised Learning) with a different learning model and architecture.…”