< Project Overview >
Poor air quality causes millions of deaths across the world, and modelling air quality can be a challenge in the context of constantly growing and developing cities.
This project will use air quality as a focus of integrating and adapting an already existing IoT system to collate a wealth of data sources for accurate monitoring and modelling. By extending an already existing platform (Siemens MindSphere), the project aims to combine Edge and Could based data storage, as well as archive data to improve real time sensing, modelling, inference and scalability of IoT supporting risk management applications.
By partnering with Newcastle City Council, the project will not only ensure excellent societal benefits (i.e. real-time AQ monitoring and modelling) but also transfer of innovative knowledge into a software product for the public good.
- An Osmotic MindSphere Orchestrator prototype which is a co-design system, including MindSphere platform and Osmotic Orchestrator as shown in the figure above.
- An adaptive AQ monitoring system which makes AQ predictions in real-time or semi real-time, based on given past AQ measurements of nearby locations. Specifically, the system is geographically distributed, monitoring the air quality while making air quality predictions. Also, it is capable of updating the deployed models on the edge side after first deployed, without terminating the servces. The orchestrator plays key role in the cross-server-edge coordination, including the edge node registration, model deployment, model fine-tune and model updating. The deployed AQ models of the whole system areup to date, adapting to the specific data pattern across different locations.
- Development of significant working relationship between HE, an industrial partner, anda public body in the development of IoT platforms, leading to further Innovation and research funding opportunities
- Newcastle City Council