Open AccessGreen Intelligent Logistics Sorting System in Big Data Environment
Author(s) -
Xinyue Gao,
Lei Liu
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/711/1/012040
Subject(s) - sorting , computer science , big data , process (computing) , plan (archaeology) , data science , automation , point (geometry) , space (punctuation) , operations research , data mining , engineering , mechanical engineering , history , geometry , mathematics , archaeology , programming language , operating system
By referring to the current sorting process of logistics sorting equipment, combined with emerging technologies, green concepts and big data statistics, it is possible to predict the trend of future sorting systems and integrate existing technologies. First, investigate and research existing logistics warehousing. Next, the intelligence and automation of existing intelligent sorting are investigated. After investigating, on the basis of the above, this study analyzes the trend of the future sorting system and combines with the concept of green logistics. It optimized classification under principles of green warehousing conceptual to make the classification more efficient, more space-saving and more convenient; it uses the big data statistics technology to collect logistics information, provides information to the logistics company to re-plan the sorting point, and feedback to the electronic merchants to obtain the location of different kinds of online shopping products in each region, and make it possible to purchase goods in a targeted manner.