Delivering Sustainable Growth through the application of 'Tech' for Reuse

技术在帮助寻找和提供解决方案以应对世界紧迫的气候紧急情况和资源效率挑战方面发挥着重要作用。随着各国政府和大型企业探索如何从COVID-19大流行中更具弹性，循环经济被强调为“重建更好”的解决方案。循环经济打破了现有的基于获取、制造和处理的线性消费模式。在循环经济中，没有什么是浪费的：资源尽可能长时间地以最高价值保留，回收是最后的选择。从这一概念中出现了新的商业模式和产品/服务设计理念，包括拆卸，租赁和共享平台的设计。产品再利用，包括翻新，再制造，升级和再利用的元素，是任何循环经济的中心支柱。作为一个部门，再利用组织（如慈善机构）提供强大的社会价值，为那些有身体和/或学习障碍的人提供有价值的培训和工作。这个项目旨在帮助克服再利用的障碍，包括：* 作为一个一次性社会，丢弃可重复使用的物品并购买新的已成为常态。这是因为购买新的通常比清洗或修理更便宜，也更容易; * 虽然再利用有助于将一些关键商品，包括那些具有高水平隐含碳的商品（如服装），排除在废物管理链之外，但它缺乏国家层面的政策和财政支持; * 再利用技术的应用有限，这意味着它的监测和记录很差。这导致了再利用的好处在避免废物方面没有得到很好的量化，运营也很少得到优化; * 再利用活动往往是劳动密集型的，因此难以有效地扩大规模和增加价值。因此，太多具有再利用潜力的物品被丢弃。因此，错过了将可重复使用的物品与愿意支付合理金额（涵盖重复使用链中的所有成本）的客户相匹配的机会;以及 * 产品之间的高度可变性加剧了上述时间/精力问题，这限制了转售潜力和转售商实现最佳价格的能力。这项可行性研究旨在通过应用人工智能驱动的计算机视觉和相关平台集成，解决与加快识别二手产品再利用/转售潜力相关的关键挑战。

Technology has a significant role to play in helping find and deliver solutions to the world's pressing climate emergency and resource efficiency challenges. With Governments and large corporations exploring how we can emerge from the COVID-19 pandemic more resilient, the Circular Economy is highlighted as a solution to 'build back better'. A Circular Economy disrupts existing linear models of consumption based on take, make and dispose. In a Circular Economy nothing is wasted: resources are retained at their highest possible value for as long as possible and recycling is the option of last resort. Emerging from this concept are new business models and product / service design philosophies, including design for disassembly, leasing and sharing platforms. Product reuse, incorporating elements of refurbishment, remanufacturing, upgrade and repurposing, represents a central pillar of any Circular Economy. As a sector, reuse organisations (e.g. charities) deliver strong social value, providing valuable training and jobs for those with e.g. physical and/or learning disabilities. Barriers to reuse that this project aims to help overcome, include: * As a throwaway society, it has become the norm to discard reusable items and buy new. This is because it is commonly cheaper and easier to buy new than to refurbish or repair; * Whilst reuse helps keep a number of key commodities, including those with high levels of embodied carbon (e.g. clothing), out of the waste management chain, it suffers from a lack of national level policy and fiscal support; * The application of technology to reuse is limited, meaning it is poorly monitored and recorded. This contributes to a situation where the benefits of reuse are not well quantified in waste avoidance terms, and operations are rarely optimised; * Reuse activities tend to be labour intensive, making it difficult to efficiently scale and add value. As a result, too many items with reuse potential are disposed of. Hence, opportunities to match reusable items with customers prepared to pay a fair amount for them (covering all costs in the reuse chain) are missed; and * The above time/effort issue is exacerbated by the high level of variability between products, which limits resale potential and the ability of resellers to achieve the best price. This feasibility study aims to address a key challenge associated with speeding up the process of identifying a used product's reuse/resale potential, through the application of AI-powered computer vision, and associated platform integration.