Nonintrusive Fault Monitoring (NiFM)

英国家庭平均每年处理价值800 GB的电器和电子产品，其中40%是可维修的。其中40%是由洗衣机等大型家用电器组成。目前，维修成本经常超过更换成本，这意味着几乎没有动力来提高家电的资源效率和延长产品寿命-导致每年都会造成重大的资源损失。伦敦的人工智能专家Green Running认为，应用新型机器学习算法可以实现家电维修流程的现代化，并通过提高运营效率在此过程中实现成本节约。NiFM项目超越了能源和信息通信基础设施，将进行一项免费的工作方案，以确定技术可行性，并设计一个工作原型，以便吸引潜在客户和投资者。为了充分利用可用的机会，Green Run将评估协调商业模式创新以增加中小企业收入、创造就业机会和盈利能力的潜力。

Each year the average UK household disposes of £800 worth of electrical and electronics items, 40% of which is repairable. 40% of this is made up of large household electricals such as washing machines. At present, the cost of repair too often exceeds the cost of replacement, meaning there is little incentive to improve the resource efficiency of appliances and increase product lifetimes - resulting in significant resource loss each year. London based artificial intelligence experts, Green Running believe the application of novel machine learning algorithms can be used to modernise the process of appliance repair - and achieve cost savings in the process through improved operational efficiencies. The NiFM project, transcending energy and information communications infrastructure, will undertake a complimentary programme of works to establish technical feasibility and devise a working prototype from which to engage potential clients and investors. To fully exploit the opportunity available Green Running will evaluate the potential to orchestrate business model innovation to increase SME revenues, job creation and bottom line profitability.