GLO: Geolocation of Origins. Creating better access through deep learning validation of origin.

Trade in Space是咖啡和可可市场创新供应链软件的开发商。我们的旗舰产品Sustainimaps处理地球观测图像和同行评审的数据集，为农业供应链的可持续性绩效提供有意义的见解和可视化。该软件目前正在使用，监测超过250 000项资产。我们通过一个名为Digitrak的移动的数据收集工具补充了我们的技术产品，该工具目前正由世界上最大的可可生产商之一使用。这款移动的工具可通过供应链追踪可可从农民到加工厂的整个过程，从而实现真正的可可豆到可可棒的可追溯性。随着欧盟最近宣布立法要求所有主要商品的进口商确认原产地农场没有砍伐森林，我们的产品在2022年和2023年变得更加重要。对于咖啡和可可进口商来说，这项新立法面临着许多挑战，其中一些挑战已经作为我们标准产品的一部分得到了解决，然而，咖啡和可可进口商面临的最大问题之一是缺乏可靠的数字化地理定位数据。许多进口商都在争先恐后地与其供应链合作，寻找解决方案来获取准确、数字、经过验证的地理定位数据。通过该项目，Trade in Space将创建地理定位输入软件，该软件由深度学习验证模型支持，并数字化到区块链中以获得护照。

Trade in Space are developers of innovative supply chain software for the coffee and cacao markets. Our flagship product called Sustainimaps processes earth observation imagery, and peer reviewed datasets to provide meaningful insights and visualisation of agricultural supply-chains sustainability performance. This software is currently in use monitoring over 250,000 assets. We have supplemented our technology offering with a mobile data collection tool called Digitrak, which is currently in use by one of the world's largest cacao producers. This mobile tool tracks cacao from the farmer through the supply chain, to the processing facility creating true bean-to-bar traceability.Our products have become even more relevant throughout 2022 and into 2023 as the EU have recently announced legislation requiring all importers of key commodities to confirm the originating farm is deforestation free. There are a number of challenges to this new legislation for coffee and cacao importers some of which Trade in Space has already addressed as part of our standard product offering, however, one of the biggest issues for importers of Coffee and Cacao is the lack of reliable digitised geolocation data for their origin farms. Many importers are scrambling to work with their supply chain to find a solution to obtain accurate, digital, verified geolocation data.Through this project will see Trade in Space create geolocation input software, which is backed by deep-learning verification models, and digitised into blockchain for passportability.