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Internet of Thing for Smart Water Innovative Networks

Periodic Reporting for period 1 - IoT4Win (Internet of Thing for Smart Water Innovative Networks)

Reporting period: 2018-03-01 to 2020-02-29

IoT4Win aims to establish a European Industrial Doctorate (EID) training program and extend the traditional academic research training setting, equipping researchers with the right combination of research and transferable competences, developing joint research training programs. This programme brings together interdisciplinary expertise of European research group, industry partners and user organizations. These different partners bring together all required knowledge, skills, and stakeholders to offer a comprehensive set of transferable skills and a training program on ICT, data science and water engineering, including industry practice and longer-term benefit in further industrial partner collaborations and further knowledge transfer. IoT4Win will respond to well defined and interdisciplinary scientific questions and challenges relating to the Internet of Things for Smart Water Networks (SWN) technological area by recruiting 3 ESRs to undertake research in the context of a joint research training on concepts and methodologies of IoT enabled SWN as a PhD project. The project has designed 3 topically individual and personalized research projects covering the core SWN research areas, namely smart sensing and trusted communication within energy limited heterogeneous devices in IoT enabled urban water environment; dynamic sensor web and interoperable open platform with Integrated Knowledge Management for smart water networks; data security and intelligence in IoT enabled SWN. The interdisciplinary collaborations and cross- sectoral industrial interactions between the ICT and water sectors will expose the ESRs to both the academic and non-academic sectors. By combining three projects, an interoperable, secure and intelligent underlying technology leading to an open platform for IoT enabled SWN applications will be developed. This project meets the current and anticipated demand for highly skilled entrepreneurs in Internet of Things and water research by developing and advancing European capacity in the design and development of SWN. The project will investigate IoT smart frameworks, integrated and intelligent data management for smart sustainable urban water environments through the transformation from internet-based management to real-time dynamic management on the basis of IoT. This will include investigation of the heterogeneous device connectivity, semantic sensor web in urban water system and integrated and interoperable data management platform, taking into account data intelligence and security for Smart Water Network application.
Work package (WP1), the research project for ESR1 (based at BCU) aims to design IoT context-aware framework in heterogeneous sensor and network device for smart water networks by bringing analytics, context-awareness and decision making closer to the network edge to achieve nearly real time water quality monitoring by using smart sensing and IoT technologies. This research has two main objectives, namely the optimal deployment of water quality sensors and water contamination detection in SWN. So far in this project, a method of optimal sensor placement using an artificial intelligence algorithm called evolutionary algorithm (EA), which aims to cover the whole water distribution network with minimising small number of sensors for effective real time water quality monitoring and contamination detection in water distribution network has been developed. The results published at the 16th IEEE international conference on ubiquitous intelligence and computing in August 2019, and the 17th international computing & control for the water industry conference, in September 2019 (CCWI2019). A journal article was under review for publication in the Journal of Ambient Intelligence & Humanized Computing.
Work package (WP2), the research project for ESR2 (based at Singular Logic Greece/ SLG-GR) aims to investigate methodologies for developing IoT smart frameworks for sustainable water management applications, with a focus on interoperability and semantic annotations of heterogeneous data for automated discovery and knowledge-based processing and Integrate heterogeneous sources of information in a dynamic web model for decision making.
Work package (WP3), the research project for ESR3 (based at BCU) aims to develop a secure and intelligent framework towards Cyber-physical System (CPS) in Smart Water Network (SWN) to improve the security and resilience of water networks. This research addresses the potential risks and security issues in IOT enabled smart water system through two approaches using Blockchain technology and artificial intelligent applying on water CPS system for attack detection and prevention in SWN. The research results has been published at the 25th IEEE international conference on Automation and Computing in September 2019 and CCWI 2019, and an article has been submitted to IEEE Transactions on Industrial informatics.
The innovative aspect of IoT4Win’s training programme is to ensure researchers to develop a range and balance of scientific competences across ICT and water sector, and wider perspectives and transferable skills that are required for their career prospects. The training will develop broadly educated researchers with hands-on expertise to be excellent entrepreneurs in the R&D of intelligent sensing and monitoring, telecommunication, IoT technologies, water engineering research, in addition to giving them the skills to pursue an academic career. IoT4Win has a strong focus on the training of personal development of ESRs, which involves the researchers in collaboration with joint supervision team, academic advisers and professionals from university and industries. Systematic structured training in IOT4win is significantly impact on IoT4Win ESRs’ career development. ESR 1 and 3 have undertaken training at A-CING, and AQUA industrial R&D company in Spain to develop hands on industrial R &D experience and in depth cross-disciplinary water research and applications. ESR 1 and 3 have also undertaken training in a water company, United Utilities, located in UK, in order to understand the requirements of end users, and develop knowledge in water engineering. ESR 1 and 3 are now currently undertaking a secondment at Singular logic Greece (SLG-GR), a research organisation in related IoT technology. ESR2, based at SLG-GR is now currently undertaking a secondment at BCU for doctoral training to strengthen the knowledge and academic experiences and helping to develop as an independent researcher and to build the necessary mind set. All of these training events throughout the consortium have had a great impact on the ESRs career development. The consolidated efforts in IOT4Win at a European level fits well with the EC research agenda and will produce highly qualified research entrepreneurs, engineers and technologists with practical experience in the industrial environment. These researchers will be highly valuable assets for the European research on smart sensing. The developed intelligent, interoperable, secured smart water platform will benefit water utilities for efficiently manage their cyber physical system in IoT enabled environment. Context aware sensor deployment, intelligent contaminant detection approach and smart water platform will create a great socio-economic impact on improving water services and contribute to develop smart water, lead to heathy living and smart society.