The City
A municipality of approximately 65,000 residents in north-central Kansas. Like most mid-size cities, it operates water distribution, wastewater treatment, fleet operations (public works vehicles, utility trucks, parks equipment), and public works infrastructure maintenance.
The city had made incremental technology investments over several years — a GPS fleet tracking system, an AMI deployment for water meters, and a work order system for public works. None of these systems talked to each other. The information they contained wasn’t combined into a unified operational picture anywhere.
The Situation Before Deployment
Water Utility
The water utility served 22,000 service connections from a distribution system with 180 miles of mains ranging from cast iron installed in the 1950s to newer PVC. Annual NRW rate: 18.4% — higher than the national AWWA average and a persistent concern for the utility director.
The AMI system provided consumption data for billing. The utility had no continuous pressure monitoring in the distribution system. Leaks were discovered through customer reports (visible street-level breaks) or through the annual water audit NRW calculation. Detection of slow leaks — the kind that run underground for months before causing visible surface damage — was essentially absent.
Fleet Operations
The city operated 87 vehicles across departments — public works, water utility, parks, and administration. GPS tracking was deployed on all vehicles. The fleet manager’s primary use of the GPS system was confirming vehicle locations when supervisors called to ask where crews were.
Fleet utilization data wasn’t analyzed systematically. The fleet manager estimated idle time was high — “probably 35–40% based on what I see when I drive by” — but had no data to confirm or act on the estimate.
Vehicle maintenance was managed on a combination of mileage-based PM (for light vehicles) and time-based PM (for heavy equipment) using a spreadsheet that the fleet manager updated manually. PM compliance was approximately 71% by the fleet manager’s own assessment.
Public Works
Public works managed infrastructure maintenance — street repairs, storm drainage, parks maintenance, facility repairs — using a commercial work order system. The work order system tracked reactive maintenance (responses to reports or inspections) but PM scheduling was handled outside the work order system.
The public works director’s biggest complaint: “We fix what breaks. We don’t have a good picture of what’s about to break so we can get ahead of it.”
The Deployment
The city’s IT director proposed the ArgusIQ pilot after seeing a presentation at a regional public works conference. The pilot was structured to cover all three operational domains — water, fleet, public works — with a 6-month deployment timeline and an 8-month evaluation period before the city council decision on full deployment.
Water utility deployment: 24 LoRaWAN pressure loggers installed at DMA boundary points and strategic distribution locations. AMI data integrated via the AMI vendor’s API. Existing SCADA at pump stations integrated via Modbus.
Fleet deployment: The existing GPS tracking platform integrated via API — no hardware changes. ArgusIQ became the operational layer on top of the existing GPS data, adding CMMS work orders, PM scheduling from odometer data, and utilization analytics.
Public works deployment: Existing work order system integrated with ArgusIQ — service requests and reactive work orders flowed into ArgusIQ CMMS alongside the PM schedules and fleet maintenance. The integration created the unified view without requiring the public works team to abandon their existing work order tool.
Shared dashboard: A city operations dashboard combining all three domains — available to the city manager, department directors, and the city council — with the key metrics from each area in one view.
The Results
Water Utility: NRW Reduction
The pressure monitoring network enabled the minimum night flow analysis that the utility had never been able to run before. Within 6 weeks of deployment, the analysis flagged three DMAs with night flow significantly above expected minimum:
District 4 (northeast quadrant): Night flow 22% above expected minimum. Investigation: a 1.5" cast iron main with a slow leak at a joint. Estimated loss: 8,000 gallons per day. The main had no visible surface evidence; it had been running underground for an estimated 60+ days. Repaired at a cost of $12,000.
District 7 (industrial area): Night flow 14% above expected minimum. Investigation: a leaking fire hydrant isolation valve. Loss: approximately 3,500 gallons per day. Repair cost: $2,200.
District 11 (residential): Night flow 18% above expected minimum. Investigation: two service line leaks at meter pits — small but persistent. Combined loss: approximately 5,000 gallons per day. Both repaired at routine cost.
A fourth leak was found at the 8-month mark — a main in District 2 that had been running approximately 65 days based on the pressure trend data.
NRW at pilot start: 18.4% NRW at 8-month evaluation: 15.2% Annual water loss reduction: approximately 50 million gallons Annual operating cost reduction: approximately $82,000 (treatment, pumping, water loss)
Fleet Operations
The utilization analysis from ArgusIQ revealed that fleet-wide idle time was 34% of engine-on hours — higher than the fleet manager’s estimate, confirming the concern. The top 15 vehicles by idle time were identified; all were public works vehicles assigned to crews doing stop-and-go inspection and small repair work.
The fleet manager used the data to restructure two crew routing patterns, moving from a single-vehicle-per-crew model to shared vehicle assignments for work that didn’t require individual vehicle presence. Idle time at the 8-month mark: 16%.
PM compliance improved from 71% to 94% — ArgusIQ’s CMMS generated PM work orders automatically as vehicles reached mileage triggers, giving the fleet shop advance notice rather than requiring the fleet manager to manually track service intervals.
Annual fleet cost reduction estimate: $47,000 (fuel savings from idle reduction + deferred capital cost from improved PM compliance reducing emergency repairs).
Public Works
The integration of reactive work orders, PM schedules, and fleet maintenance into a single ArgusIQ CMMS view gave the public works director the unified operational picture he’d described wanting:
- Infrastructure PM schedules visible alongside reactive work orders — planners could see when PM was due for assets they were also scheduling reactive work on
- Equipment health monitoring for heavy equipment (backhoes, dump trucks) with condition-based PM work orders from telematics data
- City-wide asset registry that let public works, water utility, and fleet share asset records for shared infrastructure (utility trucks used by both public works and water utility, lift stations maintained by both wastewater and public works)
PM compliance for public works equipment: 94% at 8 months (up from an estimated 71%).
The Unified Operations View
The city manager’s morning briefing shifted from “call three department heads and wait for reports” to a 10-minute review of the ArgusIQ city operations dashboard:
- Water: current NRW status, active alerts from pressure monitoring, work orders in progress for leak repairs
- Fleet: current vehicle status, vehicles in maintenance, daily utilization for the previous day
- Public Works: open work orders, PM due this week, crew assignment
The City Council Decision
At the 8-month evaluation, the city council reviewed the pilot results:
- Quantified operational savings: $129,000 annually (water + fleet)
- Qualitative improvements: NRW trend reversing, fleet efficiency improving, PM compliance at target
- One-time deployment cost for full city implementation: proposal submitted
- Ongoing platform cost: included in the proposal
The council voted to proceed with full deployment, expanding coverage to the wastewater utility, parks maintenance, and the remainder of public infrastructure assets.
The full deployment is underway.
Talk to our team about ArgusIQ for your city’s infrastructure operations.