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AI-based Smart Water Management

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India

Environment

High

Implementing Organisation

LivNSense GreenOps Private Limited

India, Karnataka, Bengaluru

Private Sector

Implementing Point of Contact

Avnish Kumar

Co-founder and CEO

Contributor of the Impact Story

Carnegie India

Year of implementation

2023

Problem statement

Almost 10% of the population in India lacks access to safe and potable water. Even though efforts are being made to provide drinking water to households, there is a perennial problem of water leakage in public water distribution systems which results in water not reaching every household properly. With India, having access to only 4% of global water resources, the water leakage management is one of the significant problems for immediate attention in our country. There are four key aspects to water resources scarcity and the need for innovative solutions to address this perennial problem: 1. National Water Crisis - India possesses only 4% of global water resources for its massive population, with per capita availability dropping below 1,100 cubic meters. 2. Infrastructure Inefficiency - Approximately 50% of water in India is wasted due to unchecked pipeline leaks, known as Non-Revenue Water (NRW). 3. Household Impact - About 75% of Indian households lack access to on-premise drinking water. 4. Management Gaps - Traditional systems lack real-time data and predictability, making it impossible to identify and locate leaks as they happen.

Impact story details

LivNSense™ is an Industrial AI venture based out of India and US that is helping large enterprises to drive their Safety, Sustainability & Efficiency goals with AI & Digital Twins technology. LivNSense™ has pioneered GreenOps™, an innovative Industrial AI "Co-Pilot" designed to transform aging water infrastructure into a sustainable, intelligent network. While traditional systems suffer from "leakage blind spots," GreenOps™ provides an Operating System for Water Efficiency that learns autonomously to bridge the gap between water source and consumption. In a country with only 4% of global water resources, efficiency is not just a goal—it is a necessity. To address these challenges in India, LivNSense™ has come up with an innovative AI based product (GreenOps™), which provides data driven real-time insights for potential water losses/leakages and predictive analytics, leveraging its unique Process AI Modelling techniques. GreenOps™ utilizes unique, hardware-agnostic algorithms to tackle the Non-Revenue Water (NRW) crisis. By integrating real-time data from 4G/5G-enabled sensors, the platform detects and localizes leaks with 99% accuracy, reducing wastage by 15–20%.

AI Technology Used

IoT & Sensor Analytics

Key Outcomes

Efficiency

Productivity, Access

Reach, Resource Efficiency

Narrative Outcome

Water leakage in India's public distribution systems results in significant losses, with 35-40% of water wasted before reaching households. Traditional detection methods are slow and imprecise. LivNSense uses AI-based real-time localisation to identify leakages and help municipal authorities manage scarce water resources. Based on pilots, the states of Haryana and Madhya Pradesh in India have achieved 20% reduction in water losses.

Impact Metrics

Reduction in water wastage/ leakage through real-time AI-based localization

Baseline Value

Before AI implementation, 35-40% water was wasted Percentage of water wasted Reported Period: 01/03/2023 - 26/06/2023

Post-Implementation

After AI implementation, there was 20% reduction in water leakages Percentage of water wasted Reported Period: 01/03/2023 - 26/06/2023

Project Acceptance Certificate from Jind Municipal Authority for completion of the Pilot at Jind PHED, Haryana, and Project Award Letter from Madhya Pradesh Jal Nigam for carrying out a pilot at Indore

Implementation Context

Pilot

Haryana (Jind-PHED), Tamil Nadu, Madhya Pradesh (Indore)

Target population in Jind, Haryana, is over 20,000 community members. At the Panchayat level in Tamil Nadu, the target population includes households across the Kathaikinaru and Kodikulam regions.

Key Partnerships

Jind Municipality Council, Tamil Nadu Gram Panchayats, Indore Municipality, and Madhya Pradesh Jal Nigam

Replicability & Adaptation

High

1. Edge hardware 2. Flow sensors 3. Connectivity gateways 4. 4G/5G cellular connectivity 5. Computing infrastructure 6. Data acquisition layer (GreenEdgeTM) 7. Technical specialists and domain experts 8. Field operations 9. Government liaison/nodal officers

* The data presented is self-reported by the respective organisations. Readers should consult the original sources for further details.