ENHANCING DISTRIBUTION COMPANIES' PERFORMANCE USING DEEP LEARNING TECHNIQUES

Abstract

In the distribution companies’ sector, managing operational expenditures and ensuring efficiency are of utmost importance. With an escalating workload, the sales workforce and its ancillary departments often find themselves stretched, impacting the time and effort allocated to daily tasks and overarching monthly objectives. By leveraging deep learning, there are avenues to alleviate these challenges, potentially leading to reduced effort and costs. This paper unveils a cohesive system that harnesses deep learning methodologies to reduce burdens on sales representatives. Instead of an over-reliance on manual human interventions, the system incorporates deep learning solutions, such as the real-time object detection capability of the YOLO algorithm. Detected objects from images are processed, turned into actionable data, and stored in a MySQL database. Employing Google API, these results are seamlessly transferred from cloud storage to the company's internal servers. The compiled data is then analyzed using a BI tool.