Machine learning & image recognition to reduce post-consumer food waste and identify contamination of food waste by non food items

全球酒店业有两个重大的环境和经济挑战，目前还没有得到解决。首先，每年有价值340亿美元的食物浪费来自消费后的食物垃圾(“餐盘垃圾”)。目前还没有一种简单的方法来自动测量和分析盘子垃圾，以便厨师能够以数据为导向进行干预，以减少这种浪费。其次，为了回收和处置，该行业被要求小心地将他们的食物垃圾与其他非食物产品分开，如果发生交叉污染，将面临巨额罚款。没有厨房内的实时解决方案来帮助员工识别非食品何时污染食物垃圾。这些都是WINNOW解决方案有限公司(WSL)处于独特地位的日益增长的机会。WSL是市场领先的尖端数字解决方案提供商，超过1000家商业厨房使用这些解决方案来准确监控和减少食物浪费。然而，这些现有的解决方案侧重于消费前的食物浪费，如变质、准备和生产过剩。WSL的计算机视觉模型被训练用于识别非复杂的食物垃圾(例如鱼和薯条)，但需要大量的工作来研究是否有可能使该模型适用于复杂的餐盘垃圾(例如顾客在自助餐后留下的食物的混合物)，并提供非食物垃圾物品(例如塑料陶器)污染的实时通知。等待公共项目摘要

The global hospitality industry has two significant environmental and economic challenges which are not currently being met. Firstly, $34bn worth of food waste happens every year from post-consumer food waste ("plate waste"). There is currently no easy way to automatically measure and analyse plate waste so that chefs can make data led interventions to reduce this waste. Secondly, for recycling and disposal purposes, the industry is being required to carefully separate their food waste from other non-food products, and faces heavy fines if cross-contamination occurs. There is no in-kitchen real-time solution to help staff identify when non-food items contaminate food waste.These are both growing opportunities which Winnow Solutions Limited (WSL) is in a unique position to tackle. WSL are market leading providers of cutting edge digital solutions that over 1000 commercial kitchens use to accurately monitor and reduce their food waste. However, these existing solutions are focused on pre-consumer food waste, such as spoilage, preparation and overproduction. WSL's computer vision model is trained on recognising non-complex food waste (e.g. fish and chips), but significant work is required to research if it is possible to adapt the model for complex plate waste (e.g. the mixture of food a customer leaves on their plate post buffet) and to provide real-time notifications of contamination by non-food waste items (e.g. plastic crockery).Awaiting Public Project Summary