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

技术在帮助寻找和提供解决世界上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。随着各国政府和大公司探索如何才能更好地应对新冠肺炎疫情，循环经济被强调为“重建更好”的一种解决方案。循环经济颠覆了现有的基于索取、制造和处置的消费线性模型。在循环经济中，没有什么是浪费的：资源尽可能长时间地保持其最高价值，回收是最后的选择。从这一概念中涌现出新的商业模式和产品/服务设计理念，包括可拆卸设计、租赁和共享平台。产品再利用包含了翻新、再制造、升级和再利用的要素，是任何循环经济的核心支柱。作为一个部门，再利用组织(例如慈善机构)提供强大的社会价值，为身体和/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的重复使用障碍包括：*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经成为常态。这是因为购买新的通常比翻新或维修更便宜和更容易；*虽然再利用有助于将一些关键商品，包括那些具体碳含量较高的商品(如衣服)排除在废物管理链之外，但它受到缺乏国家一级政策和财政支持的困扰；*再利用技术的应用有限，这意味着对其监测和记录很差。这导致了一种情况，即再利用的好处没有从避免浪费的角度得到很好的量化，而且操作很少得到优化；*再利用活动往往是劳动密集型的，使其难以有效地扩大规模和增加价值。结果，太多具有重复使用潜力的物品被丢弃。因此，错失了将可重复使用的物品与准备为其支付合理价格的客户相匹配的机会(包括重复使用链中的所有成本)；以及*上述时间/精力问题因产品之间高度的可变性而加剧，这限制了转售潜力和经销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支持的计算机视觉和相关的平台集成，解决与加快识别二手产品的再利用/转售潜力的过程相关的关键挑战。

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.