DE-WASTE: Digitally Empowered Holistic Management and Recycling of Industrial Waste

DE-WASTE：数字化赋能工业废物的整体管理和回收

• 批准号: 10077683
• 金额: $ 42.8万
• 依托单位: COMPUTATIONAL MODELLING CAMBRIDGE LIMITED
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10077683
• 关键词: DE; WASTE; Digitally; Empowered; Holistic

Management and recycling of waste from industrial and commercial buildings is a multi-domain problem that is inter-connected with the transport, environment (air quality), energy, weather, built infrastructure and climate sectors. A holistic optimisation and on-ground demonstration of waste management while taking into account this interconnected nature using a combined digital and physical engineering approach are the main aims of this project.The proposed work presents an advanced approach to transform BNL's waste collection operations, delivering significant enhancements in efficiency, sustainability, and customer service. By adopting state-of-the-art digitalisation technology and data-driven decision support, BNL will be equipped to tackle future challenges and seize opportunities, driving growth and success in an increasingly competitive and environmentally-conscious market.This project's innovation includes an integrated and automated system that harnesses digitalisation through Internet of Things (IoT) sensors, multi-sector data (both open data and confidential asset owner data) and multiple third-party (both open source and commercial) software using Connected Digital Twin (CDT) technology, empowered by The World Avatar (TWA). This approach leverages the latest advancements in Artificial Intelligence (AI), Machine Learning (ML), smart process control, and semantically linked data. The proposed innovation enables effective decision support based on a digital ecosystem approach and the continuous insights gathered from data sharing across multiple heterogeneous sectors and sources.A collaboration comprising UK-based CMCL with its deep expertise in connected digital twins and BNL, a waste management company based in Singapore is planned to deliver two innovative outcomes that will be exploited by these ambitious companies:1. BNL's tested and validated on-ground demonstrator for optimal management of its physical assets such as the Rear End Loader (REL) and Open Top Containers (OTC) trucks, its data, sensors, and the corresponding industrial waste collection operations to help grow their customer base by enabling them to reduce their waste, aligned with Singapore's national net-zero targets.2. CMCL's The World Avatar digital ecosystem with a clear demonstration use case to serve the interconnected waste management market segment within sustainable smart cities, while overall enabling its end-users in terms of behaviour change and demand reduction in the waste sector, as highlighted in the Climate Change Committee's recommendation in The Sixth Carbon Budget for Waste.

工业和商业建筑废物的管理和回收是一个多领域的问题，与运输、环境(空气质量)、能源、天气、已建基础设施和气候部门相互关联。本项目的主要目标是利用数字和物理工程相结合的方法对废物管理进行整体优化和实地演示，同时考虑到这种相互关联的性质。拟议的工作提出了一种先进的方法来转变BNL的废物收集操作，显著提高了效率、可持续性和客户服务。通过采用最先进的数字化技术和数据驱动的决策支持，BNL将具备应对未来挑战和抓住机遇的能力，在竞争日益激烈和具有环保意识的市场中推动增长和成功。该项目的创新包括一个集成的自动化系统，该系统通过物联网(IoT)传感器、多部门数据(包括开放数据和机密资产所有者数据)以及使用互联数字双胞胎(CDT)技术的多个第三方(开源和商业)软件，由世界阿凡达(TWA)支持。这种方法利用了人工智能(AI)、机器学习(ML)、智能过程控制和语义链接数据方面的最新进展。拟议的创新基于数字生态系统方法和从多个异类部门和来源的数据共享中收集的持续洞察力，实现了有效的决策支持。总部位于英国的CMCL与新加坡的废物管理公司BNL计划进行合作，以提供两个创新成果，这些雄心勃勃的公司将利用这些成果：1.BNL经过测试和验证的地面演示程序，用于优化管理其物理资产，如后端装载机(REL)和开顶式集装箱(OTC)卡车、其数据、传感器和相应的工业废物收集操作，以帮助他们通过减少废物来扩大客户基础，与新加坡的全国净零目标保持一致。CMCL的世界阿凡达数字生态系统具有明确的示范用例，以服务于可持续智能城市中相互关联的废物管理市场，同时总体上使其最终用户能够改变行为和减少废物部门的需求，正如气候变化委员会在第六次废物碳预算中的建议所强调的那样。