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DyStore: Dynamic Item Location Encoding and Navigation for Smart Locker Systems

Yan Yu, Haimo Zhang, Ting Lyu, Can Wang, Yuejia Zhang, Kaigui Bian, Li Hong

发表年份
2024
引用次数
1

摘要

In logistics industry, hospitals and pharmacies, the demand for item storage management (e.g., item storage and access) is rapidly increasing and expanding. Intelligent item storage management systems based on Internet of Things (IoT) can largely save labor costs through contactless item dispensing and robotic item access. In this paper, we propose, DyStore, a framework of item location encoding and navigation that can encode the locations of cabinets, drawers, and boxes for efficient item access in an intelligent locker system. DyStore includes a user interface, a central control server, and an item storage system built upon cabinets/lockers. Given storage space constraints, we propose a hybrid data structure that combines trees and bitmaps for encoding the item locations. Additionally, DyStore employs a path planning algorithm to help access the stored items at the minimal time-distance combined cost. Results show that the performance of the data compression and path planning algorithms is superior to existing methods.

关键词

Encoding (memory)Computer scienceArtificial intelligence

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