Automatized Water Leakage Detection & Localization
Germany
Market: Artificial Intelligence
Project stage: Prototype or product is ready
Also this project:
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Find investments
- Participate in the Unicorn Battle
Idea or High Level Concept
We have developed a new Data Science & AI method dubbed Virtual Triangulation. The method combines extensive physics-based Digital Twin simulations, state-of-the-art signal extraction techniques and machine learning algorithms for achieving the fastest alerts of new emerging water leakages with the maximum sensitivity and position precision possible. This way, up to 5 times more leaks can be found, up to 90% of the cost for the to leak finding process can be reduced and up to 100000 cubic meters of precious drinking water can be saved for every additionally detected leak.
Territory of the product or service implementation
Europe, North America
Traction and Current Status
Prototype solution piloted in 2 major German cities, next pilot in preparation in Spain.
Problem or Opportunity
In EU-countries between 6% (Germany) and more than 40% (Bulgaria) of the overall drinking water consumption is lost due to undetected leakages in the water grid infrastructure. However, detecting and locating water leakages is currently a very costly and resource-intensive process for utility companies.
Solution
We have developed a new Data Science & AI method dubbed Virtual Triangulation. The method combines extensive physics-based Digital Twin simulations, state-of-the-art signal extraction techniques and machine learning algorithms for achieving the fastest alerts of new emerging water leakages with the maximum sensitivity and position precision possible. This way, up to 5 times more leaks can be found, up to 90% of the cost for the leak finding process can be reduced and up to 100000 cubic meters of precious drinking water can be saved for every additionally detected leak.
Customer Segments and Market
16 Billion Euros globally, about 1.2 billion Euro in Europe/EU
Revenue Streams and Cost Structure
Pricing Model: One-time Setup Fee: 30-100 kEUR Data Processing Fee: 150 EUR per Sensor Success Fee per identified Leak: 1500 EUR
Competitors and Existing Alternatives
Sooqua: very early stage, no traction yet, questionable method
RBS-Wave: only distributor is solution components, no on-premise solution for critical infrastructures
Advantages or differentiators
We start with the maximal physical understanding of the water grid within our Digital Twin Framework and add machine learning and AI-components to improve our model. This way, we use the maximum information content possible for the fastest and most precise solution obtainable.
Risks
Smart Grid activities and sensor rollout in respective cities should have started. The achievable precision for the detection and localization of new leakages depends in the number of sensors, the data quality, the proper positioning of the sensors, and the grid complexity.
Incubation/Acceleration programs accomplishment
InnoEnergy HighWay Program starting in July 2019
Won the competition and other awards
1) Data Hub Ruhr Winner - February 2019 2) Bavarian Start?Zuschuss! Award 2016 for leading Digitization & Data Startups
Presence of invention or patent
No
Money will be spent on
Team expansion, product development, software and solution development, pilot installations of solution, marketing and market rollout