Context-aware frameworks in sensors for water distribution networks

Developing smart water sensor and distribution networks to identify contaminated water, resulting in quicker identification and crisis management. 

Researchers 

• Porfessor Wenyan Wu
• Essa Shahra
• Dr Michael Romano (UU)
• Dr Stamatia Rizou (SLG)
• Dr Shadi Basurra

Research background 

Water distribution systems are seeing the increased deployment of new technologies that use Internet of Things (IoT) to gather, analyse and extract useful information from data; further enabling Smart Water Networks (SWNs). IoT type technologies have a huge potential to enable more efficient water resources management. Heterogeneous IoT sensors/devices/technologies from different vendors are starting to be employed in SWNs. The deployment of IoT sensors is a critical issue that significantly affects a wireless sensors network’s real-time monitoring performance created and this model aims to satisfy the requirements of near real-time monitoring of water quality.

Research aims 

This research is aim to develop real-time monitoring by using the emerging technologies for sensor deployment method, distributed computing and communication technology. The deployment of IoT sensors (i.e. nodes) for wireless networks is to find the most efficient number, type and locations of sensors that enable satisfying a SWN’s hydraulic and water quality requirements (among the others) while considering issues such as energy consumption of the nodes and coverage of the target monitoring area.  

Research methods

This research will address sensor deployment, especially in the areas of water quality and contamination detection. Water quality monitoring will be investigated and sensor deployment criteria will be investigated using the evolutionary algorithm (EA). This method aims to cover the whole water network using a small number of sensors to detect contamination. 

Projected outcomes 

The potential outcomes expected from this project can be summarised as follows:

• The primary outcome is to design an IoT network, which makes use of context-aware heterogeneous sensors for water quality monitoring that can benefit water supplier companies and end-users.
• Development of a deployment mechanism for wireless sensors for the construction of a reliable sensor network that offers high data accuracy, good coverage and network stability.
• Allow decision making to occur near the edge for rapid response to water contamination events. It will also avoid a single point of failure when the connectivity with the cloud is lost.

Funding