Artificial Intelligence and Global Challenges — Clean Water and Sanitation

Apr 3, 2019 · 8 min read

Goal nº 6. “Clean Water and Sanitation: Ensure availability and sustainable management of water and sanitation for all.”

How Artificial Intelligence technologies can play a central role in the achievement of the Sustainable Development Goals one by one.

The concern with the availability of safe drinking water for all is at the heart of SDG6. Sanitation and hygiene are key issues since the lack of these can lead to soil contamination, and pollution of water bodies. In this article, we will identify options on how Artificial Intelligence can be harnessed to achieve the goal of ensuring sustainable water and sanitation for all by the year 2030.

“Be formless, shapeless, like water. Put water into a cup, it becomes the cup. Put water into a teapot, it becomes the teapot. Water can flow, creep, drip, or crash. Be water, my friend.” — Bruce Lee

Access to water is vital for each and every individual. As a human right, everyone should be entitled to this asset without discrimination. Sadly, the facts and figures paint a completely different reality. Today, water scarcity affects more than 40% of the global population and about 2.2 billion people lack access to safely managed drinking water. The data on sanitation is even more shocking with 4.5 billion people lacking access to a safe sanitation system. Of those, 2.4 billion doesn’t even have access to basic services such as toilets or latrines and at least 892 million people still continue practicing open defecation. But it doesn’t stop there, and each day nearly one thousand children die due to preventable water and sanitation related diarrheal diseases. (UN)

The intensifying environmental degradation together with climate change and the continued growth of the world population also pose considerable challenges to water security. Floods and other water-related disasters account for 70 per cent of all deaths in natural disasters. More than 80 per cent of wastewater resulting from human activities is discharged untreated into rivers or sea leading to pollution while about 70 per cent of all water abstracted from rivers, lakes and aquifers is used for irrigation. Inserted in this context, SDG 6’s audacious goal is to ensure availability and sustainable management of water and sanitation leave no one behind in just 11 years from now.

To reach this goal, the 2030 agenda split SDG 6 in 7 main targets, going from achieving universal and equitable access to safe and affordable drinking water for all to support and strengthen the participation of local communities in improving water and sanitation management. Between those two targets there is also the achievement of access to adequate and equitable sanitation and hygiene for all while ending open defecation, improving water quality, increase water-use efficiency, protect and restore water-related ecosystems and more. Special attention is given to the needs of women and girls and those in vulnerable situations.

Without better infrastructure and management, millions of people will keep dying every year with increasing losses in biodiversity as well. The impact of water-related decisions can affect everyone across borders. Here, the increasing role of AI can play a pivotal role in providing a data-driven approach for good governance and reliable information. To reshape the current scenario, AI has the power to revolutionize water-use efficiency and sanitation management in terms of engineering, mapping and forecasting while widely improving sustainability and scalability of water and sanitation services.

Quality water

Using AI to detect dangerous bacteria and harmful particles in the water is the goal of Clean Water AI. Moved by the astonished data that currently about 2 billion people use a drinking water source contaminated with feces, this prototype device uses pattern recognition and machine learning to monitor and inspect water quality. Clean Water AI can run continuously in real time and the analysis is accomplished with a digital microscope connected to a laptop computer running the Ubuntu operating system. The application also marks the contaminated sites on a map. For regions in the world in which access to clean water is an enduring problem, simple test systems like this could dramatically help prevent disease and save thousands of lives.

Artificial intelligence, and machine learning can be used for more effective water treatment processes as well as detect problems and assure an early allocation of efforts. This is the case of EMAGIN, that uses AI for more accurate and timely information to save money and water. Their software can offer accurate and timely information about the kinds of pollutants in water and make recommendations for treatment. EMAGIN’s software can also allow facility operators to more effectively clean incoming wastewater and manage the system to prevent overflows.

According to ITU report, a 40% gap in water resources and usages is expected to hit us by 2030. As a consequence of the increasing global population, this gap also impacts the health and food security and sanitation of the population. The more people without proper toilets or unsafe hygiene, the larger the danger of deadly and contagious diseases outbreaks. There is no one-size-fits-all solution and AI is still in its early stages in the water sector, but early applications are already showing great promises.


The power of AI can unleash developments such as AI toilets capable of analyzing feces, and diagnosing diseases. However, with still 2.4 billion people lacking access to basic sanitation services and 892 million people continue to practice open defecation, this possibility of AI toilets seems to divide the world in two. Notwithstanding, with water progressively becoming scarce, the costs of improving sanitation and supplying water for drinking, washing and cooking are also rising.

Dedicated to helping organizations understand the world with data and AI, Alto Analytics modelled an AI-powered image recognition analysis of toilets, for a more exact number of people impacted by unsafe sanitation conditions on a global scale. Their data science team used open data from Dollar Street with a website of images of living conditions of real families around the world, categorized by income levels. Alto Analytics discovered that there’s a correlation between Google’s AI accuracy and family income, revealing that 30.3% of the world’s toilets cannot be recognized by AI. Essentially, the poorest families in the data did not have access to a distinguishable toilet.

To solve the issue of poor sanitary conditions, there is no sure fire solution for AI. In a reality where isolated or less densely populated rural areas still survive without any kind of sewage system, the problem is more related to the issue of economic development, the provision of public services and the fight against extreme poverty discussed in our first article. The water and sanitation sectors must be prioritized and well-funded but at least AI can point us the direction to concentrate those efforts.


Data-driven water management can use artificial intelligence to fundamentally improve the use of water and its waste in agriculture. When applied to an irrigation control system, the collected data can automatically implement solutions to minimize water usage, manage nutrient losses, or succeed in a more required or uniform soil moisture throughout the field. With approximately 70 percent of all irrigation water abstracted from rivers, lakes and aquifers being used for irrigation, applying AI to improve the efficiency of this sector can play a main role in the sustainability of the world’s water resources.

Likewise, AI could be applied to learn the correlations between weather, crop and soil condition data, and the irrigation recommendations of a qualified agronomist. ConserWater is an example of this . Claiming to be the world’s first AI to predict how much water is needed to irrigate crops. This application can help save up to 30% on water use at any time globally. ConserWater uses NASA satellite data, historical weather data, and a variety of other factors with geospatial deep learning to predict water needs to the level of ground soil moisture sensors.

Water-use efficiency

Increasing water-use efficiency across all sectors is a shared target for SDG6 and Pluto AI. By offering a predictive performance monitoring solution for industrial processes and assets, their platform uses analytics and AI to work with water facilities and better administer their process. Pluto’s predictive analytics for industry enables wastewater systems to optimize process automation technologies for greater energy efficiency and lower operational costs. They also offer solutions for chemical, beverage and food manufacturing processes to improve wash water recovery and reduce loss.

To assist in smart water management is an organization named Smart Energy Water — SEW. Powered by AI, their products named Smart Customer Mobile, and SmartiQ are playing an important role in improving water-use efficiency. With Smart Customer Mobile, customers can reduce water usage, enroll in water conservation programs, and receive refunds. The platform also allows users to report water waste and leaks through any mobile device. Smart iQ, a cloud AI and machine learning IoT platform, provides real time analysis,for energy efficiency, water conservation, peak load management, customer segmentation, gas and water leak.

Other examples worth mentioning here is FATHOM and Water Smart. While the former uses AI to assist in smart water management in the utility industry, the latter provides customer self-services and data analytics for water utilities. Projects at the regional and national level using AI can significantly improve water and waste management systems to make it easier to monitor water quality, manage usage, and predict maintenance needs. AI-enabled online platforms can also help take the responsibility to the individual level by offering consumers a tailored, attractive and informative way to view real-time water consumption, pay bills and access information about dynamic water resources conditions.

Role of AI

Access to water and sanitation matters for all aspects of human dignity: from food and energy security to human and environmental health. AI-driven solutions can combine data analysis to generate more effective water treatment processes. These improvements can not only detect harmful bacteria and pollutants in water, as well as minimize waste in several sectors. AI can improve water-use efficiency and point to precise directions for an early allocation of efforts in sanitation supports. To achieve SDG6 and ensure the access to and sustainable management of water and sanitation, AI can also play a fundamental role to manage water resources and change the way water utilities operate.

Water is at the heart of sustainable development and its three dimensions — environmental, economic and social. Water resources, as well as the services associated with them, underpin efforts to eradicate poverty, economic growth and environmental sustainability. To access the full potential AI, we need to adapt the technologies at our disposal, mixing physical infrastructure, data management and communication in an ecosystem of collaboration and sharing of technical and cognitive resources. Back to Bruce Lee’s line of reasoning and thinking about AI of being like water it is important to have in mind that water can also be blocked, dammed, mistreated, evaporate and lack for good. To live within the limits of water availability and at the same time reach SDG6, AI is struggling to overcome challenges in infrastructure, data and smart water management services because after all, the real importance of being like water is to make its way through cracks.

Text by Camila Froede

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The immense potential of AI means that it can either increase the inequalities of our societies or liberate us from numerous sufferings. We believe the best way forward is to come together and work practically toward creating a better future. We see a massive potential for evolution in the established centralized corporations. We believe tech giants can contribute immensely toward making the vision of DAIA a reality.

DAIA welcomes the participation of those corporations that are sincere about their aim and goal of democratizing AI. The open access networks that have come together to form DAIA are the enabling layer for such a democratization process.

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