Intelligent energy-saving parking system design based on deep learning

To improve the efficiency and management of electricity consumption in indoor parking lots, an intelligent energy-saving parking lot based on deep learning is designed. Compared with traditional parking lots, this parking lot combined with deep learning algorithm can effectively solve the phenomenon of no one lights on and no car lights on. It adopts diverse data collection and optimized energy-saving control strategies to meet lighting needs while saving power resources and management costs, reducing human resource expenses, and significantly improving energy utilization. The system is lowcost, easy to debug and install and use, and has broad application prospects and market promotion value.

I. Introduction

At present, the domestic vigorously promote the concept of green lighting, the use of high-efficiency lighting products instead of traditional low efficiency, high energy consumption products, according to the newly invented energy-saving technology synchronized with the launch of a new generation of green light sources, which is a more prominent example of LED green lighting to transform traditional parking lots. [1]–[3] Foreign lighting energy-saving technology is mainly in the promotion of green lighting, the use of new light source materials, improve the performance of power devices and establish a perfect effective mechanism, and now has developed many energy-saving lighting intelligent control and management system. LUMA company launched the LEP plasma lamp to replace traditional lighting, energy-saving effect can reach 50%; Philips Lighting and OSRAM are also studying LED lighting, chip luminous efficiency from 100 lm / W to 150 lm / W. [4]–[6] Intelligent lighting control system using a combination of lighting, automation, microcontrollers and other technologies, making full use of natural light to reduce artificial lighting abuse brought The intelligent lighting control system integrates lighting, automation and microcontroller technologies to make full use of natural light to reduce energy consumption caused by artificial lighting abuse, thus truly realizing situational, automated and humanized intelligent lighting. [7]–[8]