Warehouse IoT Management System Based On Internet Of Things And AGV Path Optimization

With the development of the logistics industry and the rise of e-commerce,warehouse management has become critical.Take warehouse handling equipment(manual forklift and AGV forklift)as an example;in the traditional warehouse management process,there is a general problem of untimely access to information such as equipment operating status information,real-time location,and working hours;moreover,a modern information management platform has not been used,and it is impossible to optimize resource allocation by systematically integrating valuable data in the warehouse handling process,which is not conducive to the overall control of provincial and even national material warehouse management departments.In addition,automated storage equipment AGV forklift transporting goods or materials,when facing the storage environment where obstacles exist,how to quickly select the best path is the primary problem to be solved in storage management.In this thesis,we design and develop a warehouse IOT management system based on IOT and AGV path optimization by optimizing the ant colony algorithm and online monitoring technology,using the characteristics of IOT,such as intelligent sensing and automatic transmission.By adopting this non-contact warehouse management method,the scattered data in the warehouse management process can be centralized and networked to effectively control materials and personnel and enhance the enterprise’s overall efficiency.The main research and work contents are as follows:(1)Relying on the Internet of Things and intelligent algorithms,the path optimization algorithm of automated storage equipment AGV forklift truck is studied.This thesis addresses the shortcomings of the traditional ant colony algorithm,such as slow convergence speed and the existence of locally optimal solutions,and improves the algorithm’s performance by improving the heuristic function and pheromone volatility factor.The raster method is used to model the storage environment and optimize the obstacle avoidance path planning of the AGV forklift.Through simulation testing and analysis,the effectiveness of the optimized algorithm is verified,and the improved algorithm can help the AGV forklift to find the optimal path quickly.This path-planning algorithm has been practically integrated and applied to the embedded control system of the AGV forklift by a third party.(2)This thesis introduces Io T technology into the field of warehouse equipment(manual forklift and AGV forklift)for the design,development,and deployment of warehouse Io T management system software.The vehicle-mounted intelligent terminal collects and processes the relevant data of the storage equipment in the working process and adopts the MQTT transmission protocol to realize the data transmission between the vehicle-mounted terminal and the storage management platform;The Django project file is deployed on the Huawei cloud server platform,and the monitoring and management of the whole system are realized through the WEB browser.The warehouse IOT management system can realize real-time monitoring of data related to two types of forklifts and intelligent management of warehouse equipment.For manual forklifts,the management system platform establishes an exceptional employee real-time work performance assessment interface and uses the My SQL database to store data.(3)Finally,test cases are designed to test the function and performance of the warehouse IOT management system in a material storage unit to verify the real-time monitoring of warehouse equipment operation data,real-time employee work status collection and performance assessment,path optimization of AGV forklifts and warehouse equipment management functions of the warehouse IOT management system.The test results show that this thesis’ s warehouse IOT management system meets the design requirements.