Applying electrical gas sensors to monitor food quality in households to reduce food waste.

BlakBear发明了一种新型的纸基印刷电子气体传感器(PEGS)，它可以通过测量肉类、鱼和家禽等易腐烂食品释放的腐败气体来检测食品降解。我们将把我们的传感器安装在食品盒里，以监测和减少不必要的和可以避免的食物浪费。食物浪费是一个主要问题，无论是在全球还是在英国。英国一半以上的食物浪费是在家里产生的，60%的食物浪费被认为是“可以避免的”。2015年，英国家庭将本可以消费的130亿GB食物装入垃圾箱，产生了1900万吨温室气体(WRAP，2015)。原因是多方面的，但主要原因是消费者仅根据保质期就扔掉了三分之一仍可食用的食物，消费者失去了冰箱里易腐烂的食物的踪迹，发现这些食物“来得太晚”。由于隔离，大多数英国劳动力在家工作，随后在家里吃了三顿饭。根据我们的估计，由于需求激增，这将在食物短缺的时候增加12%-15%的潜在食物浪费。这个项目是BlakBear和OXO的合作项目。我们将向50户家庭分发装有我们传感器的食品盒。在3个月的时间里，我们将使用电子秤测量家庭中的食物浪费，并测试BlakBear传感器的行为轻推是否会改变家庭行为。通过这个项目，我们的目标是了解BlakBear传感器对家庭食物管理和垃圾产生的影响。我们将捕获有关使用频率、故障、敏感度、效率、点击率、一天中的使用时间和参与时长的数据。我们将使用这些数据来估计高价值易腐烂食品组：肉、鱼和家禽避免食物浪费的数量。

BlakBear have invented a novel paper-based printed electrical gas sensor (PEGS) that can detect food degradation by measuring the spoilage gases emitted by perishable foods like meat, fish and poultry. We will deploy our sensors in food-boxes to consumer households, to monitor and reduce unnecessary and avoidable food waste.Food waste is a major problem, both globally and in the UK. Over half of UK food waste is generated at home and 60% is deemed "avoidable". In 2015, UK households binned £13bn of food that could have been consumed, generating 19m tonnes of greenhouse gases (WRAP, 2015). There are multiple causes, but the major contributor is that consumers throw away 1/3 of food that is still edible based solely on use-by-dates, and consumers lose track of the perishable food in their fridge, discovering items "too late".Due to quarantine, the majority of the UK workforce is working from home, and subsequently consuming 3-meals a day in the household. By our estimates, this will increase potential food waste by 12-15% at a time of food shortages, due to a spike in demand.This project is a collaboration between BlakBear and OXO. We will distribute food-boxes to 50 households with our sensor incorporated. Over a 3-month period we will measure food waste in households using a digital scale, and test whether the BlakBear sensors' behavioural nudges change household behaviour. Through this project we aim to understand the effects of BlakBear sensors on food management and waste generation in the home. We will capture data on usage frequency, faults, sensitivity, efficiency, click-rate, time of day usage, and length of engagement. We will use this data to estimate the amount of food waste avoidance from high-value perishable food groups: meat, fish and poultry.