IoT Enabled Smart Water ATM Analytics and Monitoring using AWS IoT Core

Customer Background 

The customer is a social-impact-driven technology startup based in Central India, focused on building smart water dispensing (Water ATM) solutions. 
Their mission is to ensure clean, affordable, and accessible drinking water through digitally managed Water ATMs equipped with IoT sensors. 

Each Water ATM is embedded with pH, TDS, and temperature sensors to continuously monitor water quality and operational health. 
The customer aims to leverage AWS Cloud and IoT technologies to build a real-time water quality monitoring and analytics platform for rural and urban areas, enabling proactive maintenance, transparency, and better service delivery. 

Customer Challenge 

The customer faced several operational challenges with their existing on-premise system: 

• Lack of real-time visibility into sensor data from distributed Water ATMs. 
• Difficulty in analyzing trends in pH, TDS, and temperature for predictive maintenance. 
• Manual data collection leading to inconsistent and delayed reporting. 
• Need for scalable, secure, and cost-efficient cloud infrastructure to process large volumes of IoT data. 

The primary objectives were to: 

• Collect and analyze sensor data from Water ATMs in real-time. 
• Generate alerts for abnormal readings (e.g., high TDS or unsafe pH). 
• Provide centralized dashboards and analytics for maintenance and water quality insights. 
• Enable a secure and automated cloud platform to store, process, and visualize IoT data. 

Assessment 

The AnCrew Global team assessed multiple IoT and database management architectures and identified AWS IoT Core as the most suitable service due to its managed, secure, and scalable nature. 

By integrating IoT Core with Amazon Timestream, AWS Lambda, and Amazon RDS, the solution could enable real-time data ingestion, storage, and analytics with minimal management overhead. 

The architecture ensures end-to-end visibility across Water ATMs, allowing administrators to monitor performance, detect anomalies, and trigger alerts automatically. 

Business Objectives 

1. Enable real-time IoT data collection and analytics for all Water ATM sensors. 
2. Provide centralized cloud monitoring and alerting for operational efficiency. 
3. Ensure secure, scalable, and cost-optimized architecture with minimal manual intervention. 
4. Deliver actionable insights for water quality, system health, and predictive maintenance. 

Proposed Solution 

AnCrew Global designed and implemented a serverless and event-driven IoT data analytics platform using AWS services. 

The architecture provides secure ingestion, automated processing, and real-time analytics of sensor data, along with alert notifications and centralized monitoring. 

Key Features 

• AWS IoT Core securely connects and ingests data from pH, TDS, and temperature sensors. 
• AWS Lambda processes incoming data and performs validation, transformation, and routing. 
• Amazon Timestream stores time-series IoT data for historical trend analysis and reporting. 
• Amazon RDS (PostgreSQL) stores metadata, customer information, and device registry details. 
• Amazon EC2 hosts the centralized dashboard and application interface. 
• Elastic Load Balancer (ALB) distributes web traffic across EC2 instances for high availability. 
• AWS WAF protects the application layer against malicious requests and common exploits. 
• Amazon CloudWatch monitors device data trends, Lambda execution metrics, and API latency. 
• Amazon SNS sends real-time alerts and notifications for abnormal sensor readings. 
• AWS CloudTrail records all API activity for auditing and compliance. 
• Amazon Route 53 manages domain routing for the web dashboard and API endpoints. 

Third-Party Applications or Solutions Used 

No external or third-party tools were used — the solution was built entirely using AWS native services for seamless integration, security, and scalability. 

AWS Services Used 

Design Factors 

1. Real-Time Data Ingestion 
AWS IoT Core enables secure MQTT-based data ingestion from thousands of sensors simultaneously. 

2. Serverless and Scalable Processing 
Lambda automatically scales to process sensor messages without manual provisioning. 

3. Data Management 
Timestream handles time-series data efficiently, while RDS maintains relational data integrity. 

4. Security 
IAM roles enforce least privilege access; AWS WAF and CloudTrail ensure protection and auditability. 

5. Monitoring and Alerts 
CloudWatch and SNS enable continuous monitoring with automated notifications. 

6. Cost Efficiency 
Timestream’s pay-per-use model and Lambda’s serverless execution ensure low operational costs. 

Workflow Summary 

1. Sensor Data Transmission – pH, TDS, and temperature sensors send real-time data to AWS IoT Core. 
2. IoT Core → Lambda (Function 1) – Processes and validates data packets. 
3. Lambda → Timestream & RDS – Stores time-series readings in Timestream and device info in RDS. 
4. CloudWatch & SNS – Triggers alerts for abnormal readings or device inactivity. 
5. Dashboard (EC2 + ALB) – Displays analytics, trends, and alerts to users via web interface. 
6. CloudTrail – Logs all API interactions for audit and governance. 
7. Route 53 + WAF – Secure access to the application domain with global availability. 

Outcomes & Metrics 

✅   90% improvement in real-time monitoring capability across all deployed Water ATMs. 
✅   Elimination of manual data collection, improving operational efficiency by 70%. 
✅   Faster response times to water quality issues due to automated alerts. 
✅   Scalable and secure IoT infrastructure ready for multi-region deployment. 
✅   Cost reduction by 40% due to serverless and managed AWS services. 
✅   Centralized analytics and reporting, improving decision-making and system reliability. 

Architectural Overview 

Core Strengths: 
The architecture is modular, event-driven, and serverless, ensuring high availability, minimal latency, and robust security. 
It enables continuous IoT data ingestion, AI-assisted analysis (future-ready), and automated alerting — forming the backbone of a Smart Water Management Ecosystem. 

Conclusion 

By implementing a serverless IoT-based Water ATM monitoring platform, AnCrew Global helped the customer transform their water distribution network into a smart, data-driven system. 

The solution provides real-time insights into water quality and system performance, ensures proactive maintenance, and enhances public trust through transparency. 

This engagement highlights the power of AWS IoT Core and associated services in enabling smart city and sustainability initiatives, demonstrating how AWS can revolutionize infrastructure monitoring with automation, intelligence, and scalability.