FLUIDANALYTICS.AI
Deployments — Proven Intelligence Across Urban Water Systems
Across cities and catchments worldwide, Fluid Analytics delivers real-world deployments that translate data into action. From large-scale sewer network assessments to river, lake, and public-health monitoring, our deployments demonstrate how AI, robotics, and multi-sensor intelligence enable faster decisions, measurable environmental outcomes, and resilient urban water systems. Each case study highlights a practical application of AquaGrid—showing how integrated monitoring helps cities prevent pollution, reduce flood risk, and safeguard public health at scale.
01
Singapore — Network-Scale Sewer Condition Intelligence
Fluid Analytics deployed AI-based CCTV analysis across Singapore’s sewer network to support PUB’s zero-discharge and water-reuse goals. The platform analyzed inspections covering hundreds of miles, automatically classifying defects such as fractures, cracks, root intrusions, and offset joints across VCP, CIPP, and DI pipes. AI review improved inspection accuracy to ~98% while increasing productivity by 2–3× versus manual methods. Utility gained faster defect prioritization, reduced review latency, and data-driven rehabilitation planning to support climate resilience and long-term water security.
02
Santiago, Chile — Large-Scale Wastewater Network Modernization
In Santiago, Fluid Analytics supported condition assessment across the entire city's wastewater network serving a rapidly growing, water-stressed city. AI analysis of CCTV inspections identified deposits, surface damage, fractures, and joint defects—over 39% rated high severity (LoF ≥5). Concrete pipes accounted for ~92% of inspected assets. By automating defect detection and severity scoring, utilities accelerated rehabilitation planning and reduced environmental discharge risks, enabling proactive management of aging infrastructure under climate and urbanization pressures.
03
United States (CA, TX, AZ) — Multi-City Sewer Risk Analytics
Fluid Analytics analyzed sewer inspections across 20 U.S. cities, covering diverse pipe materials and operating conditions. AI identified common failure modes including deposits (30%), fractures, cracks, and joint defects, with one-third of assets rated high risk. Compared to manual review, AI improved accuracy to ~96% and tripled inspection throughput. Municipalities used these insights to address SSOs, infiltration/inflow, and consent decree compliance while prioritizing limited capital budgets toward the highest-risk assets.
04
Delhi, IN — AI-Based Sewer CCTV & Sonar Assessment
In Delhi, Fluid Analytics deployed robotics, sonar, and AI to assess severely aging, surcharged sewers responsible for frequent overflows. The platform processed CCTV and sonar data across ~100 km, detecting structural defects, obstructions, and silt accumulation that were often missed manually. AI increased inspection accuracy by ~50% and improved daily productivity by 2.5×. Rehabilitation planning cycles were reduced from ~30 days to 2–3 days, enabling faster intervention to mitigate pollution and overflow risks.
05
Mumbai Catchment — Integrated Lake & River Pollution and Flood Mitigation
Fluid Analytics delivered a catchment-scale monitoring and intervention program for the Powai Lake–Mithi River basin in Mumbai for the Municipal Corporation of Greater Mumbai (MCGM). The project integrated GIS, AI-driven sewer condition assessment, and multi-sensor flow and effluent-quality monitoring across the lake, river, coastline along with trunk sewers. Monitoring covered 18 km of river, 25 km² of lake catchment, 200+ outfalls discharging ~460 MLD, and 30 km of sewer networks including 1,800 mm trunk mains. Data-driven interceptor and diversion planning enabled up to 90% reduction in lake pollution and ~60% reduction in river sewage discharge, while identifying tidal backflow and flood-prone zones for resilience planning.
06
Pune, IN — Robotics and Wastewater Based Epidemiology for Public Health
Fluid Analytics deployed a wastewater-based epidemiology (WBE) program in Pune to deliver early, population-scale surveillance of infectious disease dynamics. Funded by the Rockefeller Foundation, the project integrated systematic sewer sampling with molecular analysis to track SARS-CoV-2 prevalence and variant evolution across the urban catchment. Notably, wastewater analysis detected the Omicron variant prior to the first reported clinical case globally, marking the earliest known identification worldwide. These signals provided advance warning ahead of clinical surges, enabling public-health agencies to assess transmission trends, guide targeted interventions, and optimize response strategies—demonstrating wastewater networks as real-time public-health observatories for large metropolitan regions.
07
Jodhpur, IN — Robotics and WBE for Monitoring Water Borne Pathogens
Fluid Analytics implemented a wastewater-based epidemiology (WBE) program in Jodhpur to monitor public-health trends across a population of approximately 1.75 million. Supported by funding from the Skoll Foundation, the project combined routine sewer sampling with laboratory analysis to detect pathogens including SARS-CoV-2, HAV, HEV, Influenza, and Norovirus. The system enabled early identification of localized outbreaks and contaminated drinking-water sources, supporting targeted hospital alerts and municipal disinfection actions. The project demonstrated how wastewater infrastructure can function as a city-scale public-health observatory, delivering actionable intelligence for rapid, preventive response.