Solid Waste Detection Service Platform: An Integrated Technology Aspect

This paper utilized the use of TensorFlow2 and computer vision techniques to enhance a service platform for solid waste classification systems in response to increasing global waste disposal challenges. By diversifying the training dataset and utilizing the pre-trained SSD MobileNet V2 320×320 model, the study aims to improve the accuracy and effectiveness of solid waste management solutions. The results demonstrate the significant impact of incorporating a more varied dataset, leading to reduced loss and improved performance in object localization of the AI-model. This model is then used for solid waste detection service as an online platform. This research contributes valuable insights into the potential of artificial intelligence and computer vision to revolutionize waste management practices for a more sustainable future.