Industry Insights 19 min read

Smart Water Management: Pain Points, Scenarios & 13K Pump Station Case Study

This article analyzes pain points in the water industry, details four smart water management application scenarios—smart production, pipeline network, management, and service—and presents a case study where Jiangsu Zhongfa Water used FineBI's mobile platform to build a 10-day inspection system for 13,000 sewage pump stations, achieving automated data collection, GPS tracking, water quality analysis, and PDF reporting.

Data Practical Notes
Data Practical Notes
Data Practical Notes
Smart Water Management: Pain Points, Scenarios & 13K Pump Station Case Study

Industry Pain Points

The article opens by noting that "smart water management" has become a buzzword but warns that some vendors chase trends instead of solving real problems, risking misaligned solutions.

Business Problems

Data asset management difficulty : Offline statistics persist; business systems don't cover all production links; data across systems cannot be linked, leading to poor quality, slow reporting, errors, and low efficiency.

Slow business response : Water pollution incidents need rapid response, but traditional emergency modes waste time, increasing losses and threatening resident water safety.

Inspection management challenges : Inspections suffer from untimely handling, non-compliance, missed checks, and poor maintenance; managing field staff is hard, and small issues can escalate into major safety events.

Operational Management Problems

High marketing costs : "Use water first, pay later" model drives up costs; non-resident bankruptcy risk, dispersed residents, low default penalties, long collection cycles result in high labor cost and low efficiency.

Unreasonable resource allocation : Rapid urban expansion leaves pipe networks uncovered; old districts have complex, intersecting pipes; aging infrastructure corrodes and leaks, preventing rational allocation of network and inspection resources.

Lack of decision support : Enterprises lack systems to detect main issues early; predicting peak/off-peak demand and sewage load changes is critical for resource scheduling and environmental compliance.

Smart Water Management Application Scenarios

1. Smart Production

Common Analysis Approaches

Includes production cost analysis, production data analysis, and data reporting across water supply, sewage, equipment, and energy modules.

Production analysis framework covering supply, sewage, equipment, energy
Production analysis framework covering supply, sewage, equipment, energy

Key Modules

Data Reporting : Captures water, electricity, consumption, pressure for each process segment; calculates unit consumption (electricity, alum, chlorine) for asset management.

Water Supply System : Water supply analysis (volume, consumption, projects, equipment) and water quality management (by plant, time, substance).

Sewage : Analyzes treatment volume and water quality (COD, BOD, ammonia nitrogen, total phosphorus, heavy metals) to select targeted processes and monitor trends for early risk detection.

Equipment Module : Maintenance management (work order count, execution), early-warning platform (temperature alerts), and repair analysis (repair records, personnel, costs).

Energy Module : Analyzes electricity, water, gasoline, diesel costs by department, monthly distribution, consumption share, month-on-month/year-on-year trends, multi-year comparison; auto-generates monthly energy reports.

2. Smart Pipeline Network

Pipeline Network Modules

GIS-based visualization of total pipe length, pressure gauges, water quality points.

Real-time updates of monitoring point data, regional leakage rankings, night minimum flow indicators.

Real-time alerts for unreasonable network configuration to enable rational asset allocation.

DMA (District Metered Area) Special Analysis

Leakage rate : Precise calculation per zone via flow monitoring and data analysis.

Night minimum flow analysis : Identifies hidden leakage points because night flow mainly reflects background leakage and illegal use; monitoring pinpoints potential loss areas.

Production-sales difference statistics : Monthly cumulative supply, sales, and difference trends reveal loss patterns.

New meters, unread meters, write-offs : Ensures new user demand met, improves meter reading coverage, reduces statistical errors, optimizes resource allocation.

3. Smart Management

HR Module : Talent management including age structure, education, core indicators, high-level talent, titles/skills, training, model workers.

Finance Module : Real-time alerts on revenue, cost, total assets, net assets, profit, total liabilities.

KPI Module : Under dual-carbon goals, monitors water core KPIs (equipment assets, business, others).

Project Management Module : Tracks key project construction and inspection completion (monthly reports, annual milestone rates, regional commercial operation, inspection status, project completion rates).

4. Smart Service

Common Modules : Customer service hotline, marketing account analysis, inspection reporting approval.

Customer Service Hotline : Visual dashboard shows source distribution, work order handling methods, yearly acceptance trends to guide targeted improvements.

Marketing Account Analysis : Focuses on revenue indicators; drills into arrears and recovery rates; sends one-click reminders to risky users to lower marketing costs.

Inspection Reporting Approval : FineBI-built workflow solves supervision difficulty and slow response; enables intelligent control of inspection process (work order duration, online route management), improving service capability and resource allocation.

Case Study: Jiangsu Zhongfa Water – 13,000 Sewage Pump Stations

Project Background

Changshu city has 13,000+ dispersed sewage pump stations managed by three parties (construction/maintenance, government supervision, third-party supervision). Jiangsu Zhongfa Water acts as third-party supervisor, responsible for equipment status checks, overseeing daily maintenance, and reporting to government. Tight schedule ruled out outsourcing; they chose FineBI mobile platform for in-house development.

Project background overview
Project background overview

FineBI Mobile Platform Advantages

Integrates diverse business apps, enables rapid agile development, fits smart water trends, solves schedule pressure and cuts development cost.

System Functional Modules

Inspection Planning : Admin randomly selects station IDs one day ahead, assigns tasks to inspection teams for orderly execution.

Navigation : Calls Baidu/Gaode maps for quick, accurate routing to target stations.

Mobile Inspection Data Reporting : Inspectors follow task list; system auto-records GPS, generates random water quality sample IDs, supports photo upload of non-conformities, achieving automated, precise data collection.

Water Quality Data Aggregation & Analysis : Complex pass/fail criteria; system auto-judges water quality after manual import, then aggregates and analyzes.

PDF Report Export : Daily aggregates non-conforming equipment info with photos and causes into PDF for timely government reporting.

Platform Monitoring : Real-time monitoring of equipment summary, water quality test data, inspection completion rates for decision support.

Application Scenarios & Effects

The system covers equipment management, task execution, water quality sampling, comprehensive evaluation, reporting, and large-screen display. It delivers QR code scanning, reporting, photo capture, GPS positioning, navigation, report analysis—all on mobile—completing the entire inspection supervision workflow, greatly saving labor, material, and time costs.

Project Insights

Development cycle ~10 days, rapid delivery, significant cost savings. Demonstrates feasibility of FineBI for lightweight business systems in smart water. Also addresses multi-app switching, high development/maintenance costs as business systems grow.

Original Source

Signed-in readers can open the original source through BestHub's protected redirect.

Sign in to view source
Republication Notice

This article has been distilled and summarized from source material, then republished for learning and reference. If you believe it infringes your rights, please contactadmin@besthub.devand we will review it promptly.

case studydata visualizationFineBIsmart water managementwater industryDMA analysisindustry pain pointsmobile inspection
Data Practical Notes
Written by

Data Practical Notes

Focuses on data visualization, providing practical data visualization insights, introductions to data visualization tools, and the application status of data visualization across industries.

0 followers
Reader feedback

How this landed with the community

Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.