Membrane-Cyber-Physical System (m-CPS) for Smart Water Treatment

过滤膜在提供清洁饮用水方面发挥着关键作用，获得清洁饮用水是最关键的人权之一。通常情况下，过滤器的操作依赖于手动，本地监测操作标记，如流速和污染物浓度。这种对专家维护的需求阻碍了膜技术发挥其全部潜力。为了纠正这一点，需要通过传感器来实现对滤水器的监控，实时传输数据，以进行集中的人工智能（AI）分析。这种人工智能驱动的水过滤系统必须具有可扩展性，以满足全球对清洁水的需求。因此，作为网络物理系统（CPS），膜系统在全球范围内有巨大的机会受益。该学科跳跃补助金（DHG）将为PI和学科跳跃Das提供身临其境的信息和通信技术（ICT）体验。这将使他能够将信息通信技术的能力和智能无线传感器技术的使用用于自主、实时监控，以及在更广泛的CPS领域内的人工智能驱动的数据分析应用到他的家庭学科中，与膜水处理相关。这将通过支持/指导PI在2年内以50%的FTE来实现，以体验开发基于智能CPS架构的膜-CPS （m-CPS）的方法，该架构嵌入智能无线传感器网络（WSN），通过基于云的AI数据分析和决策来增强膜处理单元的性能，从而持续实时监控膜处理单元的性能。

Filter membranes play a critical role in providing clean drinking water, access to which is one of the most pivotal human rights. Typically, the operation of the filters has relied on manual, local monitoring of operational markers such as flow rates and contaminants' concentrations. This need for hands on expert maintenance is preventing membrane technology from reaching its full potential. To correct this, the monitoring of water filter needs to be achieved by sensors, transmitting data in real-time for centralised artificial intelligence (AI) based analysis. Such an AI driven water filter system must be scalable to meet with the global demands for clean water. There is therefore a massive global opportunity for membrane systems to benefit from being implemented as cyber-physical systems (CPS). This discipline hopping grant (DHG) will provide the PI and discipline hopper Das with an immersive information and communication technology (ICT) experience. It will enable him to bring the ICT capabilities and use of smart wireless-sensor technologies for autonomous, real-time monitoring, together with AI driven data analytics within the broader area of CPS into his home discipline relating to membrane water treatment. This will be achieved by supporting/mentoring the PI at 50% FTE for 2 years to experience ways for developing a membrane-CPS (m-CPS) based on intelligent CPS architecture, embedded with a smart wireless sensor network (WSN) for continuous real-time monitoring of the performance of a membrane-treatment unit enhanced by cloud-based AI data analytics and decision making.