Water Meter Reading Based On Deep Learning And Its Application

Water resource is the basic resource related to the national economy and people’s livelihood.With the increasing consumption of water resource,it is of great significance to accurately record the water meter reading of individual and enterprise users.On the other hand,with the growth of population and the development of social economy,water meter users are widely distributed.Therefore,manual water meter reading is becoming more and more difficult,and has no longer adapted to the needs of the current era.The intelligent water meter reading system has become the current and future development focus of water enterprises.With the process of computer and communication technology in modern society,automatic intelligent water meter reading has gradually become a reality.In this paper,we propose to detect the digital area and recognition the reading of the water meter image by using computer vision and image processing methods.And the capture of water meter images can be used to prevent cheating on water consumption.The main work of this paper includes:1)A “fully convolutional sequence recognition network” for water meter reading is proposed and a data set for training is presented.The data set includes 5,000 difficult samples and 1,000 easy samples.Within the difficult samples,there is a wide range of variation caused by illumination,refraction and occlusion.Both the difficult and easy samples are labeled with sequential characters such as ‘‘0,1,5,0,6’’.2)To deal with the problem of “intermediate state” for a single water meter number,an “augmented loss function” is proposed.This loss function instructs the model to learn the number at "lower state" rather than "intermediate state",thereby reducing errors in recognition and effectively improving the accuracy of recognition.3)An intelligent water meter cloud service system is constructed based on image detection and text recognition algorithm.By saving the water meter images and recognition results in the server,we provide useful functions such as image query,recognition result query and correction,so as to reduce manual labor cost.4)An application demonstration system for water meter reading on smart mobile devices was designed and implemented.The 8-bit lightweight quantized digital area detection model and reading recognition model were trained on the gpu machine and deployed on an android device as a demonstration application.