Open Data and Artificial Intelligence - a good interaction
Water is one of three basic needs for humans. Our earth is mostly covered with water, while only two percent is fresh water. However, this topic does not only concern cities, but intelligent water management is one of the most vital challenges for smart cities in the future. With Open Data, it is possible to compare the water resources of countries as well as cities and derive measures from that. Regarding resource water management, the combination of Open Data and Artificial Intelligence (AI) builds a good interaction to help managing it. Read more about the symbiosis of Open Data and AI, in the article How Open Data and Artificial Intelligence improve the air quality in smart cities.
Nowadays, the water shortage is already felt
For a very long time, the sedentary nature of humans has been determined by water. This has mostly changed in developed countries but not so much in developing ones. Around the globe, forty percent of people are affected by the changes in the climate, including the reduction of fresh water. However, water shortage does not only appear in Africa but also recently within Europe. Since this summer provides hot temperatures for a long period of time, the German press announced that in certain parts of Germany a drinking water shortage my come soon if the weather remains the same.
In the future, the demand for water will increase
Scientists expect a temperature increase on the earth of five degrees Celsius. This, in connection with desert spread, river dehydrations and groundwater pollution leads to an increased importance of water. By 2025, the UN Food and Agriculture Organization states that drinking water will be insufficient for all people on earth. One cause is the population increase - by then the population will grow by 2.5 billion, all to be provided with drinkable water. Indeed, this topic does not only apply to remote countries but will also affect Europe in the future. By 2070, forty-four million Europeans will be affected by water shortage because rivers in Central and South Europe will carry eighty percent less water - even power plants may be on dry land. Therefore, the UN states that in fifty years, drinking water will be more valuable than gold.
The construction of dams, deep wells or water pipes will not solve the problem, but new technology will
The urban water supply industry should be guided into the new technological era. Predominantly, the current infrastructure of the water industry still needs a human engineer and/or operator for anticipating and understanding how to best react to recurring changes in inlet water quality, e.g. episodic, daily or seasonal, hoping for achievements regarding sustainable operations. Nevertheless, also a well-trained engineer and/or operator, who is familiar with big data, needs time to analyse and predict, which system changes need to be done. A solution for this is the combination of new technologies such as Artificial Intelligence (AI) and Open Data. The idea is that urban water suppliers include data-driven technology allowing them to find previously unattained information regarding water demand and supply.
There are many ways of how AI replicates the human learning process. In the AI learning phase, input data is coincided to well-known outputs allowing the algorithm to learn. As a next step, during the AI operational phase, the system starts with the introduction of new data. Since AI is permanently able to process a huge amount of data in real time, it is the perfect instrument for water resource management in a constantly changing world and the water business. This allows water suppliers to achieve higher revenues as well as plan effectively for the next years.
AI can support (smart) cities to manage their water resources more efficiently in multiple ways
As the figure below displays, AI can improve the water management within (smart) cities regarding water supply, catchment control, water efficiency, adequate sanitation and drought planning.
Resource volatility, supply optimisation and automated supervisory control are examples of how AI can help to manage water resources better
Water suppliers have two options: either search for new supply, which deals with the water resource volatility, or optimise the existing supply. Rome, well-known for its historic aqueducts, had to ration their fresh water this summer due to the drought. One reason for that is their leaking urban water infrastructure, which loses about forty-four percent of the fresh water in their pipes. AI can help to solve this issue in applying predictive analytics to the legacy water equipment as well as data management systems. The data from disparate sources, e.g. pumps or filtration systems, run through algorithms and delivers optimal control and management protocols, which then can be used to conserve energy.
In using new Software-as-a-Service platforms and AI, better financial, strategic and tactical utility operations can be created. With AI, municipalities can gain a better understanding of real-time water loss and a more efficient distribution network - while coping with the rising customer demand in their cities.
Another area, in which AI supports the water resource management is concerning automated supervisory control. Via a system, data from different sources is evaluated and based on that, the water pumping from the aquifer is regulated. This data contains a mixture of weather- and system-related data in order to optimise the fresh water supply. According to waterworld.com "pairing these automated controls with an extended knowledge base will lead to a network of systems that can automatically communicate with each other and acclimate when one system requires more resources than another in order to keep operating costs as low as possible."
In the future, AI will support water resource management even more
Soon, urban water supplier will use AI to identify and quantify various types of cyanobacteria, or blue-green algae, threatening to shut off water systems when they proliferate. AI combines a software and a microscope to analyse water samples for algae cells within one or two hours. This includes already that a human analyst confirms the AI results. Currently, samples are sent to labs and manually analysed by a technician, which takes one or two days. Since water sample testing would be quicker and can be conducted more frequently, AI would offer an early warning system of occurring issues. The aim is to provide an AI-based system, which permanently monitors the water flowing through microscopes to track contaminants as well as microorganisms.
Another futuristic approach of how AI can help to manage water resources is based on machine and deep learning. With the household smart meters, a huge data set is generated, which may be used for water flow predictions, inconsistency identification and/or leak controls. As a next step, machine learning, Internet of Things and blockchain will be combined creating a decentralised water system in which local water resources and closed water loop recycling add value. Giving an example, rivers can be designed "to autonomously adjust their own sediment flow". Pairing this with AI-informed price models, it may optimise the usage of water and change people's behaviour.
Therefore, in AI lies the future of the water industry, better to say, water resource management. It may play the pivotal role to make our present water infrastructure more robust and safer. However, AI can only be as good as its underlying data is, therefore, Open Data plays a significant part in this process.
Read more about how AI and Open Data can support smart cities in terms of clean air on the European Data Portal.