Multi-Modal Dictionary Learning for Smart City Operation and Management

智慧城市运营管理的多模态词典学习

• 批准号: LP190100079
• 负责人: Prof Marimuthu Palaniswami
• 金额: $ 26万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2020
• 资助国家: 澳大利亚
• 起止时间: 2020-09-14 至 2023-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP190100079
• 关键词: Multi; Modal; Dictionary; Learning; Smart

This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.

该项目旨在为市议会提供新的数字资产管理工具，通过利用新的传感和自动学习技术来识别、跟踪和审计资产，从而改善城市服务。目前，没有数字化工具可用于处理这些服务。该项目通过构建新的多模态字典学习程序，提出了新的多模态感知和城市资产映射技术。新框架将实时识别城市资产的不同状况，以做出决策。该项目的预期成果包括集成和轻松访问具有独特数字身份的资产，以帮助市议会、政府和导航服务进行实时资产监控。