The main objective of this project is to develop a sales intelligence system. The training dataset has been downloaded from Kaggle and by the process of data preprocessing has been transformed into a desirable dataset for the sales intelligence system to analyze and provide accurate results. The Project includes work on various fields of computer science which have been collaborated to form an intelligent system for analysis and prediction of sales of retail shops. It includes Exploratory Data Analysis (EDA), Prediction using Linear Regression Supervised Machine Learning Algorithm, Flask Framework, React JS, etc as the tech stack. The project’s main focus is to provide a monthly analysis of sales of retail shops to the owner for the purpose of profit maximization.
The main objective of this project is to develop a vehicle detection and speed tracking system. In order to achieve better performance, the test videos and training videos of this proposed approach are limited to the top and rear section of moving vehicle videos that consist of multiple moving vehicles. The quality of videos captured plays a vital role in detecting vehicles and tracking the speed of vehicles in motion. In addition, only the registered vehicles are acquired, so a non-registered vehicle may also be tracked. The prediction can be seen in real-time as well as in an output video format.