What are the Intelligent warehousing logistics management system solutions

Intelligent warehousing logistics mainly use big data, scenario algorithms and Internet of Things technology to conduct a comprehensive analysis of logistics management and services. Among them, reasonable logistics channels, holographic logistics process supervision, comprehensive logistics data analysis, and smart logistics cost optimization are all related solutions.

According to the survey of the relevant logistics industry, its big data has changed the operation methods of logistics enterprises to a certain extent, but it is not systematic. Especially in traditional logistics companies, the manifestation is more obvious. Logistics services generate a large amount of data every day, but our utilization of data is not high, or not systematic. So, how do we design intelligent warehouse logistics management system solutions from the perspective of big data products.

1. Reasonable logistics channels 

Establish more reasonable transportation tasks between logistics point-to-point, and ensure that inter-regional transportation tasks can be completed smoothly with minimal risk. And rational use of inter-area joint tasks to maximize logistics value and rationalize costs.  

2. Holographic logistics process supervision 

Collect and analyze information on logistics tools, such as vehicles and deployed IoT devices (Internet of Vehicles). In addition, holographic monitoring and management of the entire logistics information is carried out. Analysis such as fuel consumption, vehicle speed and driving conditions combined with weather, traffic big data and other information to comprehensively analyze the logistics process, and timely improve the problems that occur in the circulation process.

3. Comprehensive logistics data analysis 

Logistics big data generally includes transportation, warehousing, distribution, handling, and packaging. Its large amount of data and multiple dimensions increase the potential value of data. We can integrate in-depth mining to provide enterprises with more decision-making support, improve efficiency, and reduce costs.  

4. Intelligent logistics cost optimization 

Through big data analysis and scenario algorithms, it is possible to predict logistics risks, analyze the causes of problems, find the weights of influencing factors such as warehousing layout and personnel, and analyze optimization methods.