Paper Contents
Abstract
Around the world the technological advancements are ailing to make the lives even better. To curtail the losses incurred by collusion during unloading of materials in the construction sector a Machine Learning based system is proposed to make use of the technology which helps to reduce the losses due to lack of personal monitoring of materials dumping. During the process of downloading these materials lot of scams are happening in counting the loads and quantity of the loads in liaison with supervisors and other monitoring staff which incurs huge losses to the contractor or company. Owners are not completely aware of the count and quantity the of loads that is being received. The proposed system is able to count the number of vehicles unloaded and also it analyzes the amount of load received. Few Machine Learning concepts are used to analyze the captured images from the cameras connected. It reduces human involvement and counters the frauds while receiving the load. Initially the model is trained with some vehicle images with load and without load. Later on, when the vehicle enters the ground, the system captures the image of the vehicle from behind. The captured image is now sent to the model for analysis. Using certain machine learning algorithms and libraries, the quantity of load in the vehicle can be assessed. At the end of the day the owner will be able to see the final data in an excel sheet that comprises of count of load, quantity of load, the date and time at which the load arrived etc.
Copyright
Copyright © 2023 Eti Sri Harika. This is an open access article distributed under the Creative Commons Attribution License.
