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OmegaLambdaTec GmbH

Automatized Water Leakage Detection & Localization

Germany
Market: Artificial Intelligence
Stage of the project: Prototype or product is ready

Date of last change: 29.07.2020
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Idea

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.

Current Status

Prototype solution piloted in 2 major German cities, next pilot in preparation in Spain.

Market

16 Billion Euros globally, about 1.2 billion Euro in Europe/EU

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 (product or service)

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.

Competitors

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.

Finance

Pricing Model:
One-time Setup Fee: 30-100 kEUR
Data Processing Fee: 150 EUR per Sensor
Success Fee per identified Leak: 1500 EUR

Money will be spent on

Team expansion, product development, software and solution development, pilot installations of solution, marketing and market rollout

Offer for investor

Up to 10% Equity

Team or Management

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
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Idea
Current Status
Market
Problem or Opportunity
Solution (product or service)
Competitors
Advantages or differentiators
Finance
Invested in previous rounds, $
Business model
Money will be spent on
Offer for investor
Team or Management
Mentors & Advisors
Lead investor
Risks
Incubation/Acceleration programs accomplishment
Won the competition and other awards
Invention/Patent
Photos
Product Video