Sector: Water

Problem: Rural Tuscany, Italy has a relatively low population density, and despite the size of its network AdF serves only around 400,000 customers. Acquedotto del Fiora SpA (AdF) is Tuscany’s largest water company in terms of the size of its network, which covers 55 municipalities, including all 28 in the province of Grosseto and 27 in the province of Siena. With many water treatment and distribution assets, AdF’s pipeline network stretches across 8,000 km. With unaccounted-for water totaling around 42.5% of its treated water, this extended network makes it particularly challenging to identify failures and the sources of losses.

Solution: Rezatec’s Geospatial AI, Pipeline Risk product was deployed across 674km of the AdF water network in a pilot program launched in January 2021. The solution is being used to verify the network trends and identify those parts of the network that must be replaced in the following investment plan period.

Problem: One of the world’s most pressing needs is to protect water resources, ensure water quality, and develop and sustain effective water and wastewater treatment operations. The problems range from water pollution, to water contamination.

Solution: iShed is IO Sight’s algorithm-based system for water quality monitoring and water security in rivers and watersheds. The system enables continuous monitoring and detection of contamination of water sources, sends alerts in real-time while providing estimations for downstream contamination propagation along the northern river basin (the Jordan River watershed) flowing into the Sea of Galilee.

Probem: Chicago’s urban waterway is often seen as unsuitable for human interaction due to its real or perceived pollution levels. In the past, detecting microbial pollutants in waterways required water samples to be drawn from the river and sent to a testing lab, delaying the ability to give the public accurate and timely information about fluctuating pollution levels.

Solution: H2NOW is a technology created to measure microbial pollutants in an urban waterway in real-time and to contribute critical microbial data to a bigger-picture understanding of factors affecting water quality in the Chicago River.

Problem: Large Cities face challenges in efficient water distribution and intermittent supply operations. The first challenge is real water losses because of physical leaks, overflows, etc. The second challenge, often unaddressed, is apparent or commercial losses. The objective of the project is to enable long-term environmental and city sustainability by addressing both these challenges.

Solution: To address the challenges, a three-step process is used. At the topmost layer, an AI-powered analytics and monitoring system is customized, which targets deficiencies in the data, identifying connections and network elements like pipes, pumps, valves, and stores to find anomalies.

Problem: Around 25 million people lack access to safe drinking water in India. This leads to health issues, which leads to annual loss of around ‚360,000,000 Crores INR ($5,400,000) to the economy, in addition to thousands of health issues, which could be avoided by providing safe and affordable drinking water.

The objective is to provide safe drinking water through customized decentralized drinking water solutions at selected urban / rural locations.

Solution: Based on water profile of community, appropriate purification technology is used. All purification machines are equipped with remote monitoring and information layering. A remote monitoring device called‚ Soochak‚ is mounted on the water purification plant. This device captures minute-by-minute machine status on their technology backend. The software designed by them uses AI and IOT and remotely tracks community-level drinking water purification systems by bringing accountability to day-to-day operations.

Problem: The world is witnessing a huge scarcity of water resources. Still many people believe water to be a resource that is free to spend, worsening the water crisis. The problem especially persists in apartments wherein individual meters are not installed to check water consumption, which later becomes a main focal point of water usage.

Solution: DrizzleX is a smart water metering solution with FlowDx, a device that monitors water usage and recognizes leakages, consumption trends and overconsumption using AI powered insights.
The FlowDx sensors specifically work in multi-family units. They measure each unit‚ water usage, in case of multi-family properties like apartments and upload this data to the cloud.

Problem: Water distribution inequality is on the rise along with supply networks that do not meet the needs of real-world conditions. Countries and organizations are trying out every measure they can to provide their people with enough water. But even in places where water is easily available, most of it is lost through leakages behind walls and sinks.
Solution: Phyn is an intelligent water solution that uses sensors and AI to activate auto-shutoff as well as conserve water and save money. Phyn detects water usage, water wastage and provides tools to address issues such as pinhole leaks and frozen pipe bursts, even before they happen. It detects unusual water usage as well, ensuring a reduction in water bills and consumer awareness on water consumption and the importance of conserving it.

Problem: Water distribution is a growing concern, with water inequality on the rise along with supply networks that do not meet the needs of real-world conditions. There is an alarming water bill that consumers themselves have to pay for. The need for a technology that could reduce water consumption, leakages, wastage and energy usage is greater now than ever.
Solution: HydroIQ’s solution “SmartGrid” monitors water consumption trends, water pressure, metering and quality using IoT, analytics and predictive maintenance. Real-time analytics, data and various reports to meet regulatory compliance requirements as well as ensure sustainability are provided. Physical water infrastructure is virtualized which allows users to monitor metering, level, quality and pressure at both a household level and in the water network. It also allows for billing, payments, monitoring by property managers which also enables cutting down of operational and revenue losses.

Problem: Water utilities spend billions just in pumping energy to transport water from the original source to the consumers. They deal with inflated energy costs, inefficient networks, leave a huge carbon footprint, have low returns on investment and also deal with decision making processes manually. Another requirement is huge dataset to manage this decision-making process, which includes information about water consumption, network’s hydraulic models, energy prices, energy production and more. Another issue that is overlooked is the water losses in the network that are either detected late or unaccounted for. Predicting future water demand is another task that is difficult to manage manually.
Solution: SCUBIC uses machine learning algorithms to optimize water distribution networks in real-time. They do this by simulating water networks which uses datasets both from the network itself and from external sources like weather and economic data. Advanced algorithms then use this data to predict water and energy demands in real-time across various parts of the network. Using historical data, they use AI to predict the behavior of consumption and systems precisely. It also uses energy supply information on the grid and the current electricity prices to optimize the energy costs of valves and pumps operation.

Problem: Agriculture being extremely dependent on water, it consumes almost 70% of the world’s freshwater resources. Agriculture suffers from improper irrigation technology and leakages during distribution, special the surface irrigation. It becomes vital to ensure that water wastage is reduced and plants get optimal water in the most efficient way possible.
Accordingly need was felt to develop tech enabled irrigation solution, which analyses the water necessity for plants, and deploy water at the most effective time, in the most effective manner.
Solution: The SWAMP project uses Internet of Things (IoT), data analytics, autonomous devices and other related technologies to address irrigation issues. It optimizes the water distribution process based on an analysis done after taking all parts of the system including the type of plantation and water cycle into consideration. It also detects any leakages and sends alerts. It identifies the main water sources such as lakes, rivers, dams etc. near the plantation.