How It Unfolded
A true-to-life account from the field, anonymised to protect our client. Scroll through the journey.
A monsoon evening, six flooded streets
The city's control room logged ninety overflow complaints in one evening. Pumping stations were overwhelmed, six low-lying streets went under water, and sewage entered two schools.
The municipal commissioner asked a simple question nobody could answer: where exactly is the network failing?
Chasing a network nobody had drawn
Large sections of the network existed only in the memory of senior linemen. Cleaning crews worked from complaint lists, always one street behind the problem. Critical manholes silted up quietly for months before failing loudly in the rain.
Every repair started with exploratory digging, because records disagreed with the ground.
Map it, sense it, schedule it
We surveyed and GIS-mapped the network, zone by zone, verifying with CCTV crawler inspections. Ultrasonic level sensors went into critical manholes and wet wells, streaming to the Environcares platform.
Cleaning shifted from complaints to a risk-ranked schedule built from silt profiles and level trends. Pumping stations got telemetry and automated alerts.
The monsoon that stayed underground
Rising level trends now flag developing blockages days early, and crews clear them before the water notices. Overflow incidents fell 75 percent in the first year. Average response time dropped from days to hours because faults are located on a map, not by digging.
The two schools stayed dry through the next monsoon.
A network that reports its own health
The city now runs sewers the way modern utilities run power grids: mapped assets, live sensing, predictive maintenance and accountable response. The model is expanding to storm water drains next.
Infrastructure you can see is infrastructure you can manage.