Pollution Avoidance Support System (PASS) using GIS, Machine Learning and Big Data

使用 GIS、机器学习和大数据的污染避免支持系统 (PASS)

• 批准号: 10009455
• 金额: $ 50.17万
• 依托单位: NAZIR ASSOCIATES LTD
• 依托单位国家: 英国
• 项目类别: Feasibility Studies
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10009455
• 关键词: Pollution; Avoidance; Support; System; PASS

Air-pollution kills millions every year. Like a 'pandemic in slow motion', dirty air is a plague on our health, causing 7-million deaths and many preventable illnesses like stroke, heart disease, lung cancer and acute respiratory infections worldwide each year (WHO, 2021). Yearly, in the UK, it causes 36,000 premature deaths (Government's Committee on Medical Effects of Air-Pollutants COMEAP) and costs £20-billion.Although, pandemic-induced lockdowns caused largest drop in annual global emissions in 2020, lockdown easing has seen a surge to more than pre-pandemic levels. Despite various actions taken by many governments (e.g. enacting clean-air-zones), poor air quality is projected to continue into 2050 (OECD,2019).Scientists recommend dodging approach to pollution-vulnerable people like those with respiratory illness (e.g. asthma, bronchitis, etc.) who develop complications and sometimes die due to exposure to high pollution levels (European Public Health Alliance, 2020). Pollution levels can vary widely between many locations within a city/town and will vary from time to time for a location. Current solutions provide city-wide information and are thus ineffective for dodging approach as a vulnerable person is unable to decipher which location(s) within a city/town to use or avoid if they were out on walk/journey/exercise etc. A solution with pollution-data on a much smaller scale, e.g. at postcode-units level, can solve this problem. However, the UK does not, and probably cannot, have monitoring equipment for each of its approximately 1.7 million postcode-units (a city/town can have 100s of postcode-units). Nonetheless, the thousands of emission-sensors operational across UK (BBC, 2019) provide enough data to develop models for all postcode-units if the right tools are deployed.This project therefore aims to develop a system that can provide postcode-units-specific pollution data to users using machine learning algorithms, GIS data, telematics, weather data and big data analytics. The system will be available via web and mobile app and will include**Live-Pass:** will provide live pollution data for each UK postcode-unit to support users in deciding for or against an outdoor activity (e.g. journey, outdoor exercise etc.) in a specific location/postcode-unit. It will suggest cleaner alternatives.**Future-Pass:** will provide hourly 7-day future pollution forecast for each UK postcode-units to support planning/scheduling future outdoor events for a cleaner location/time.**City/town analytics dashboard (CAD):** provide data and insights on the different levels of pollution for all the postcode-units within a city/town (targeted at local authorities)

空气污染每年造成数百万人死亡。就像“慢动作的流行病”一样，肮脏的空气是对我们健康的瘟疫，每年在全球造成700万人死亡和许多可预防的疾病，如中风，心脏病，肺癌和急性呼吸道感染（WHO，2021）。在英国，每年有36，000人过早死亡（政府空气污染物医学影响委员会COMEAP），耗资200亿英镑。尽管疫情引发的封锁导致2020年全球年度排放量下降幅度最大，但封锁放松已超过疫情前的水平。尽管许多政府采取了各种行动（例如制定清洁空气区），但预计空气质量将持续到2050年（经合组织，2019年）。科学家建议避开易受污染的人群，如患有呼吸道疾病的人（例如哮喘，支气管炎等）。这些人会出现并发症，有时会因暴露于高污染水平而死亡（欧洲公共卫生联盟，2020年）。污染水平可能在城市/城镇内的许多位置之间变化很大，并且会因时间而异。当前的解决方案提供了城市范围的信息，因此对于躲避接近是无效的，因为脆弱的人如果外出步行/旅行/锻炼等，则无法破译使用或避免城市/城镇内的哪个（哪些）位置。具有小得多的规模上的污染数据的解决方案（例如，在邮政编码单元级别）可以解决这个问题。然而，英国没有，也可能不可能，为大约170万个邮政编码单位中的每一个都配备监控设备（一个城市/城镇可以有100个邮政编码单位）。尽管如此，英国各地运行的数千个排放传感器（BBC，2019）提供了足够的数据，如果部署了正确的工具，可以为所有邮政编码单元开发模型。因此，该项目旨在开发一个系统，可以使用机器学习算法，GIS数据，远程信息处理，天气数据和大数据分析向用户提供邮政编码单元特定的污染数据。该系统将通过网络和移动的应用程序提供，并将包括 **Live-Pass：** 将提供每个英国邮政编码单位的实时污染数据，以支持用户决定是否进行户外活动（例如旅行，户外运动等）。在特定位置/邮政编码单元中。它将建议更清洁的替代品。** Future-Pass：** 将为每个英国邮政编码单位提供每小时7天的未来污染预测，以支持规划/安排未来的户外活动，以获得更清洁的位置/时间。城市/城镇分析仪表板（CAD）：** 提供关于城市/城镇内所有邮政编码单位的不同污染水平的数据和见解（针对地方当局）