Adaptive recognition of time series of images for warehouse inventory cataloging

该项目将把先进的图像识别技术与机器学习相结合，开发一个库存编目系统。Missing Link Technologies管理托管大量机架的数据中心，这些机架由通信服务器组成。为了维护服务器的库存，专家需要对机架进行物理筛选，并就服务器的重新配置做出决策。该公司已经开发了软件，通过对新设备的可用货架提出建议来简化决策过程。该公司提议部署一个系统来获取网络设备机架的图像。图像采集可以通过人工拍摄货架的图像来完成，最终可能在机器人系统的帮助下实现自动化。然而，为了进一步自动化这一过程，该软件需要现有库存的准确数据库。该项目将设计和实现一个模块，该模块将分析获得的图像，以总结服务器机架的内容，并将摘要存储在数据库中。该数据库还将包括一个图像库，其中包含这些机架上发现的设备的清晰图像。机架的内容将与映像库中的设备进行匹配。该模块将包括一个反馈机制，机器学习算法将使用该机制来自动更新系统，以提高未来的性能。因此，该系统将在其业务阶段继续改进，而无需修改软件。该公司的研究表明，市场上没有其他可比的产品。拟议的系统将使他们获得竞争优势，提高生产率和高效的设备管理。

This project will combine advanced image recognition techniques with machine learning to develop an inventory cataloging system. Missing Link Technologies manages data centers hosting a large number of racks consisting of communication servers. In order to maintain the inventory of servers, an expert needs to physically sift through the racks and make decisions on the reconfiguration of servers. The company has developed software to simplify the decision process by making recommendations on available shelves for new equipment. The company proposes to deploy a system to acquire images of racks of networking equipment. The image acquisition can be done by a human taking images of the racks and may eventually be automated with the help of a robotic system. However, in order to further automate this process, the software needs an accurate database of the existing inventory. This project will design and implement a module that will analyze the acquired images to summarize the content of the server racks and store the summaries in a database. The database will also include an image library consisting of crisp and clear images of the equipment that is found on these racks. The contents of the racks will be matched against the equipment in the image library. The module will include a feedback mechanism that will be used by a machine learning algorithm to automatically update the system for improved performance in the future. As a result, the system will continue to improve during its operational phase without software modifications. The company's research shows that there is no other comparable product in the market. The proposed system will give them a competitive advantage with increased productivity and efficient management of equipment.