Management of freshwater, wastewater and stormwater is still a big deal for many cities around the world. The pace at which the global population is growing marks the increase in the volume of sewage as well. And along with the rising threat from climate change, matters are becoming more complicated.
Furthermore, the United Nations stresses the impact of the amount of dangerous chemicals, toxic substances and debris linked with modern consumer lifestyle. Plastic materials, microbial pollutants and traces of medications also threaten water security and human health.
Contaminated water, at the global level, poses significant risks of malnutrition, diarrhoea, opportunistic diseases and infections. The result is 1.7 million deaths each year, of which nearly half are children. More than 90% of the cases are in developing countries.
As a matter of fact, developed nations are also experiencing peril to a great extent. For example, in 1993, the city of Ocoee in Florida experienced direct contact with a discharge of untreated sewage leading to 39 cases of Hepatitis A.
Hence, this year’s World Water Day was celebrated with the theme ‘Leaving no one behind.’ As a part of the Sustainable Development Goals (SDG) of the UN, it aims to improve water quality. The approach needs to be reducing pollution, minimising the release of toxic substances, treating wastewater, solving water crisis while increasing recycling and reuse of water by 2030.
While the goal is set, artificial intelligence (AI) is marking the route to reach the destination. We have handpicked three different AI systems that are helping smart cities to solve their water crisis underground. As you read further, you will come to know that each one has been successful in providing solutions through AI.
SmartCover Systems based in California, US is working closely with wastewater utility leaders across the country to develop robust technological solutions. It combines sensors, satellite communication ability and analytics, event notification platform to inform sewer condition in real-time. Issues relating to sewer infrastructure are being managed by AI pattern recognition that has eliminated the need for ‘entering a manhole.’
The company has developed and strategically positioned remote field units that help operators identify blockages before an overflow occurs. Alongside, it detects stormwater infiltration before it results in a problem. It also helps prevent sewer spills before they back up into homes and businesses.
Until now, the SmartCover System has collected 200 million hours of sewer and stormwater data.
Case Study 1
San Antonio Water System (SAWS) deployed the SmartCover AI-based trend analysis tool combined with 200 remote field units. The aim was to operate a real-time sewer cleaning optimisation program. Eventually, the program enabled SAWS to identify areas that required cleaning. This resulted in an overall reduction in cleaning operations. SAWS was successful in eliminating sanitary sewer overflows and reducing wear and tear on its collection system due to high pressure jetting. Three years after the deployment, SAWS has been able to save more than $3.4 million and managed water crisis.
Case Study 2
Mount Crested Butte in Colorado, home to 6500 residents experienced sewer spills in 2005 and 2006. The estimations done by the local engineers showed that it would cost nearly $10 million to fix the 10-mile pipeline. As the region employed with SmartCover, it provided real-time visibility to the pipe network often covered by snow. Installation of smart monitors across the collection system cost $96,000 instead of $10 million. The town was successful in eliminating the spills with immediate return on investment.
CENTAUR System (Cost Effective Neural Technique to Alleviate Urban Flood Risk) created at the University of Sheffield, UK uses AI to manage water flow in cities. The system operates by installing “gates” in the sewer networks that can control water flow from one end to another. The system is integrated with sensors that monitor water level on either end of the gates.
The gates can be operated remotely to control the flow during extreme weather conditions to prevent flooding in specific areas. For instance, if a segment of the sewer starts overflowing downstream, the system detects rising water levels and closes a gate upstream. This retards water flow or diverts it to other parts of the network with spare capacity – preventing water from spilling on the streets.
Centaur System is developed by researchers at the university with the capability to manage operations independently. In other words, it works without human involvement and learns from its mistakes.
In 2017, the Centaur System was installed at a test site in Coimbra in Portugal. The system included two major components i.e Flow Control Device (FCD) and Local Monitoring and Control System (LMCS). The system was regularly checked and sensors were installed to record performance. The testing was successful and additional knowledge was gained after which the technology became operational in October 2017.
In 2018, the system was deployed in Toulouse, France. It turned out to be a low-cost solution capable of reinforcing existing flood defence programmes.
However, without the spare capacity in the sewer network, the AI poses a problem. The floodwater is diverted from urban areas to rural farmlands where the population is low. Hence, this cannot be left on AI and is important that different groups are involved in decision-making.
For instance, farmers may be in control of some drainage channels. Utility companies need to be responsible for the sewerage network while environment agencies take care of the river systems. To make this happen, local, regional and national governments need to listen and negotiate with all groups who are affected. This can help create a robust and comprehensive strategy against flooding.
Fluid Robotics System
Fluid Robotics was established by Asim Bhalerao in India in 2016 after he noticed the water crisis in residential societies and offices in Mumbai. Signboards displaying ‘No water from 9 am to 5 pm’ due to problems with the sewer network.
Asim carried out in-depth research after which he learnt that the government lacked proper maps of the network. And this leads to digging for weeks to identify a particular problem in the network.
The problem inspired Asim to use AI-powered solutions to diagnose water and wastewater pipeline networks to address water loss and water pollution. This lead to the birth of Fluid Robotics – claimed to be the first company in India to use AI to address the water crisis.
Currently, the startup creates multi-sensor robots that inspect pipes as small as six inches in diameter and as big as 5×5 metre tunnels. The robotic system is deployed for better management of the sewer network and to reduce the pollution of water bodies.
The robotic system utilises AI capabilities that enable it to perform fault detection without manual interference. It supports seamless data acquisition and visualisation while restricting data manipulation.
Fluid Robotics system not just eliminates the need for human employees to involve in dangerous jobs such as entering gutters. But at the same time, it also reduces the human effort to interpret data.
Today, Fluid Robotics works on Robot-as-a-Service business model and provides its service through subscriptions. It also includes topographic surveys, flow surveys, hydraulic and hydrological modelling as add ons.
Fluid Robotics’ first two projects were Powai Lake and Mithi River rejuvenation. With its technology, the startup helped in intercepting, diverting, and treating over 400 million litres of untreated wastewater per day. It prevented the wastewater from entering freshwaters without the need to build new treatment capacity.
In addition, the system has been successful in preventing thousands of hours of manual scavenging while able to identify 20 million litres of water leaks.
As per Asim, to achieve zero water pollution and 24×7 water supply, collaborations are essential. Wastewater and water crisis are interlinked and need to be solved together.