Revamping the Smart Water Network Architecture
Established in 2010, SWAN’s five-layered model of a Smart Water Network (see figure below) is based on the following:
- The physical layer consisting of pipes, pumps, valves etc.
- The sensing and control layer consisting of sensors and actuators.
- The collection and communication layer consisting of data exchange and transmission.
- The data management and display layer consisting of various types of dashboards especially the SCADA system.
- The data fusion and analysis layer consisting of all the smart algorithms that make the system ’smart’.
This model serves a number of strategic and functional purposes. Firstly, it provides the industry with a terminology baseline and structured way of discussing smart water networks. The model enables us to point at a certain layer to get our point across. It can also be used when we develop new concepts when we discuss smart water in a troubleshooting session when we seek to optimise operations, and in a sense, it gives us a way to describe the very different fields of competence that are required across each level.
In this blog, we want to suggest two extensions of this model to reflect the evolving, multi-faceted nature of the smart water sector. The purpose of the extensions is to open up two additional fields for discussion and delineate two additional domains of competences necessary to succeed with SMART water networks.
Layer 0: Value Creation Layer
The first extension is even below layer 1 and could, moving forward, be called layer 0. We suggest the name of this proposed layer to be `The value creation layer`. Value creation is critical for moving SMART Water from the domain of nerds and experts we don’t understand’ to the domain that belongs to everybody. Essentially, developing smart water systems is everybody’s job.
This is the layer or domain where stakeholders can ask questions like: How can we optimise this process? Why is this unit performing poorly at times? How can I monitor good performance? How can we make our utility consume less energy, chemicals, etc.? How can I optimise the maintenance of this system?
It is a domain where everybody from operations, to engineering, to finance, to customer service can ask questions and formulate challenges. It is also in this layer that consultants and providers of systems or products can discuss smart solutions with their customers. This is the very place where the value of what SMART can offer is discussed.
We need this domain in the model. As long as these types of questions are not in the model, we can not achieve the full potential of what we see in smart water systems and our stakeholders can’t ’talk’ with or to us.
Additionally, it is important to understand – and everybody who has tried knows this – that it is not an easy task to understand what exactly creates value: what kind of value and to whom? Likewise, it is actually quite complex to prove or validate value. I think all of us are a bit tired of SMART claims of around 20% improvements. Improvements compared to what? To a poor performing plant? In simulations? What? Therefore, it would be of vital importance to in a sense ’professionalise’ this discussion.
A professionalisation of the field would also enable more intelligent value creation discussions than the constant focus on return on investment (ROI). ROI discussions often end up being too one-dimensional for our times. A time where sustainability, community engagement, long-term planning and deep understanding are emerging key success factors. The combination of ROI discussions and an unclear starting point makes a lot of the current discussions in this domain less intelligent than they could be.
Layer 6: User Interaction Layer
The second extension comes after the fifth layer and could therefore be called layer 6 – `The user interaction layer`. In this layer, the people who are responsible for operating the smart system are located. Today, this is a very vulnerable connection. This is also where the value-added promised in Layer 0 is delivered.
This is especially relevant as systems are becoming increasingly ’intelligent’ in a complicated way based on highly advanced math methods such as machine learning, model predictive control, artificial intelligence, grey-box models, cluster analysis, etc. The number of tools is booming and there are very few people who know how to set up and develop ’smart systems’ based on these methods. As they are setting up the systems, they have to make a number of assumptions that are very hard to understand and hence validate or invalidate by those who – on the other hand - understand the water system on which the advanced math is going to operate. Making this communication work is non-trivial.
When the design work has been finalised, operators will have to interact with these advanced systems. What are they to do if they don’t understand what is going on? If something looks wrong? How are they supposed to continue the optimisation efforts? What if a special non-predicted event happens, should they turn it all off? If they haven’t interacted with the system for years – how are they going to operate it manually now? There are a ton of unanswered questions in this domain and without answers, SMART is not going to work out in practice.
Operators play an especially important role in SMART water systems - they are the ones that will play together with the system on a daily basis. Far too little attention has been paid to making this interaction intelligent and attractive. Instead, it has often been feared by operators that the SMART system will replace them in their job. Hence, a SMART system has to some extent been perceived with hostility by those who should work most closely together with the systems and embrace the transition/acceleration of smart water so that they can perform their tasks more efficiently. This is not viable. We need research in user interaction, user interface, collaborative design, etc.
A focus on Level 6 will also lead to a better design of the Smart Water interface that will meet its intended need. We often expect a higher level of data literacy from the Digital System users than what is typical in the field. A well designed Smart Water interface should be no more complex than a traffic light, where Green means to keep going, Red means stop and Yellow means that more data analysis is needed.
Why revamp the five-layer model?
Besides the important reasons mentioned under each layer, we must also embrace that we are moving from the ’Age of Smart’ to the ’Age of Sustainable’. ’Sustainability’ does not stand in contrast to ’smart’, it is better understood as building on top of ’smart’.
Applying ’Smart’ in the service of ’sustainable’ means to minimise energy consumption – or even better to minimise greenhouse gas emission by shifting energy consumption when possible to periods where green energy is available. It means minimising the emission of nitrogen and phosphorus – or even better to minimise it in response to the needs of aquifers. It means reducing chemical consumption – or even better control of the process so that biological phosphorus removal plays a major part in the cleaning process. It means controlling combined sewer overflows (CSO’s) to minimise first flush events – or even better to flush the sewers so that no debris builds in the pipes. It means monitoring water loss in drinking water systems – or even better monitoring for bursts to enable rapid localisation and repair.
Sustainability also has a social aspect. When looking at the concept of Integrated Water Resource Management (IWRM) which currently is the golden standard for sustainability, we have to understand all the water stakeholders – and they have to relate to the water systems we are managing. That means we need to communicate and to make the systems transparent to stakeholders – this is the only way stakeholders can take responsibility. On top of that, we experience again and again in IWRM projects that local stakeholders also contribute with information that was in our blind spots. Hence, collaboratively we will be able to engineer better systems and operate them more intelligently and eventually contribute to a more sustainable world.