Evolving Telecoms scope 3 decarbonisation: an open-access emissions datasource powered by Vision Machine Learning

不断发展的电信范围 3 脱碳：由视觉机器学习提供支持的开放获取排放数据源

• 批准号: 10111834
• 金额: $ 6.37万
• 依托单位: MYCELIUM NETWORK LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10111834
• 关键词: Evolving; Telecoms; scope; decarbonisation; open

**The problem:**The majority of the UK telecoms sector's 3.4 million tons of CO2e annual emissions fall in 'Scope 3'. Addressing these indirect emissions would be comparable to removing 1.7 million cars from UK roads annually.To decarbonise, telecoms operators urgently need reliable data on supply chain emissions - but currently, far more direct data exists than can be readily accessed. Vast amounts of important supplier data are buried in unstructured visual format in online corporate PDF reports that existing, expensive AI methods don't prioritise extracting accurately. So for operators _and_ suppliers, work towards net zero isn't optimised _or_ rewarded because accounting is still based on industry average emissions factors: a huge drag factor.**The innovation:**Transforming Telecoms Scope-3 data with pioneering vision Machine Learning: a new open-access platform.Through pioneering vision-based Machine Learning techniques, Mycelium locates and extracts hard-to-access 'unstructured' emissions data from corporate reports and facilitates seamless access, to reduce reliance on industry estimates, transform accuracy and help ethical actors compete.Currently in its second phase of development in partnership with the University of Sheffield, Mycelium is the first platform to train vision-based machine learning techniques specifically to process unstructured emissions data. It will also be first to train a module specifically to recognize data relevant to decarbonisation efforts in Telecoms scope 3, and make it available via an open-access platform, and subscription Application Programming Interface (API) for large-volume users. A specialist module supported by proprietary ML innovations, Mycelium has the potential to surpass the accuracy of less cost-effective services like ChatGPT in extracting the data Telecoms operators need to get serious about decarbonising scope 3\.**Democratising data-access to accelerate Net Zero**Unlike platforms focused on monetising data access, Mycelium prioritises open access and user control of data profiles. Companies whose data was previously 'buried' are incentivised to improve their listing, add their own detailed data and compete accordingly; promising higher quality and transparency in emissions reporting, and challenging incumbent data companies to evolve their services.**Refining the offering**Our Machine Learning module is built, and testing is ongoing. Next we'll train the module to recognise emissions data in Telecoms scope 3 and extract the kind of unstructured data that can support decarbonisation in this tricky area. This data will be available to anyone who needs it via our forthcoming open-access platform, and we'll develop an API to make it available by subscription for large-volume corporate users.

**问题：**英国电信部门的340万吨二氧化碳年度排放量的大多数落在“范围3”中。解决这些间接排放将与每年从英国道路上拆除170万辆汽车相提并论。要脱碳，电信运营商迫切需要有关供应链排放的可靠数据 - 但目前，与容易访问的直接数据相比，数据的直接数据要多得多。大量重要的供应商数据以非结构化的视觉格式掩埋在在线企业PDF报告中，这些报告现有的，昂贵的AI方法无法准确提取。因此，对于运营商_和_供应商，努力努力并未优化_or_奖励，因为会计仍然基于行业平均排放因素：一个巨大的阻力因素。从公司报告并促进无缝访问，以减少对行业估计的依赖，改变准确性并帮助道德参与者竞争。目前，在其第二阶段开发中，与谢菲尔德大学合作，Mycelium是第一个专门培训基于机器的机器学习技术的平台，以专门用于处理非结构化的发射数据。它也将首次训练一个专门识别与电信范围3中脱碳工作相关的数据，并通过开放式平台和大型用户的订阅应用程序编程接口（API）提供。由专有ML创新支持的专业模块，菌丝体有可能超过较低的成本效益服务的准确性，例如ChatGpt提取数据电信操作员需要认真对待脱碳范围3 \。激励以前被“埋葬”的数据以改善清单，添加自己的详细数据并进行相应竞争的公司；有望在排放报告中提高质量和透明度，并挑战现任数据公司发展其服务。接下来，我们将训练模块以识别电信范围3中的排放数据，并提取可以支持此棘手区域中脱碳化的非结构化数据。这些数据将适用于我们即将出现的开放访问平台需要它的任何人，我们将开发一个API，使其可通过订阅大型企业用户提供。