In general, tasks such as optimizing the loading of transport units and transport routes, online tracking of goods throughout the entire journey require processing speed, high accuracy and consistency in supply chains. Only modern innovative ICTs make it possible to carry out tasks of this scale. Nowadays, there are many box solutions that allow you to reduce the delivery time of goods and the associated costs, optimally plan and monitor the movement of goods. Such solutions exist for all types of transport, but especially this area has been widely developed in motor transport with the introduction of GPS navigation, which allows you to monitor the location of each transport unit in real time. In this paper, the smart optimization and automation for supply chain management was proposed using deep learning model. Due to the standards prevailing in various transport sectors, logistics work is relevant in the area where docking occurs in the transport of goods between different modes of transport. Modern innovations in the form of GPS tracking, virtual distributed computing or cloud computing and Internet services make it possible to implement modern logistics tasks.
A. Vaniprabha
SNS College of Technology, India
Optimization, Loading, Transport, Routes, Online, Tracking, Journey, Processing, Speed, Accuracy, Consistency, Supply Chain
| January | February | March | April | May | June | July | August | September | October | November | December |
| 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 4 , Issue: 1 , Pages: 388 - 392 )
Date of Publication :
December 2022
Page Views :
167
Full Text Views :
3
|