Digitally enabling Local Authorities to tackle food poverty

多亏了小企业研究倡议，Olio将把其粮食贫困预测地图从与诺丁汉大学合作建立的学术项目转变为地方当局的强大工具。食物贫困预测地图是由Olio和诺丁汉大学商学院的N/LAB合作创建的，得到了Innovate UK知识转移伙伴关系的支持。最初的目标是通过使用数据分析来更好地理解、建模和预测用户的食物分享行为。该项目的结果是创建了Olio N/Lab食物贫困预测地图原型。该项目将使粮食贫困预测地图能够获取“地面真相”，并建立一个以地方当局为中心的界面，供地方当局使用。该接口将帮助地方当局确定哪些地区正遭受粮食贫困，哪些地区有陷入粮食贫困的风险。这些数据使地方当局能够将其资源集中在最需要的地区，并在不久的将来将受到粮食贫困影响的地区开展预防运动。

Thanks to the Small Business Research Initiative, OLIO will transition its Food Poverty Prediction map from an academic project built in partnership with the University of Nottingham, to become a powerful tool for Local Authorities. The Food Poverty Prediction Map was created in partnership between OLIO and the N/LAB at the University of Nottingham's Business School, with the support of Innovate UK's Knowledge Transfer Partnerships. The original goal was to better understand, model and predict food sharing behaviour of users through the use of data analytics.The outcome of this project was the creation of the OLIO N/Lab Food Poverty Prediction Map prototype. This project will enable the Food Poverty Prediction Map to acquire 'ground truth' and build a Local Authority centered interface for Local Authorities to use. The interface will help Local Authorities identify which areas are suffering from food poverty and which ones are at risk of falling into food poverty. This data with enable Local Authorities to target their resources in areas that need it the most, and set up preventative campaigns in areas that are going to be affected by food poverty in the near future.