Real-Time IoT Water Quality Monitoring System for Environmental Management

The client faces difficulties in continuously monitoring water quality parameters and reflecting probing results in real-time for immediate response and decision-making, leading to potential delays in detecting pollutants or anomalies in water bodies.

A mid-sized utility company specializing in environmental resource management seeking to enhance water quality monitoring and reporting capabilities.

• Develop an IoT-based water quality monitoring system capable of capturing data from multiple sensors in real-time.
• Implement a platform that reflects probing results instantly to enable quick response to water quality issues.
• Enhance data accuracy, reliability, and timeliness to support environmental safety compliance.
• Achieve scalable architecture to accommodate expanding sensor networks and data volume.
• Ensure secure data transmission and storage to protect sensitive environmental information.

• Real-time sensor data collection and transmission via IoT devices
• Dashboard displaying live water quality parameters such as pH, turbidity, temperature, and dissolved oxygen
• Automated alerts triggered by threshold violations or abnormal readings
• Historical data storage for trend analysis and reporting
• Secure login and user management system
• Remote configuration and calibration of sensors

• Sensor network integrations for continuous data collection
• Environmental data standards APIs for contextual information
• Notification services for alert dissemination
• Secure data storage and backup solutions

• System must support data ingestion from at least 100 sensors concurrently
• System should reflect data updates within 2 seconds of sensor transmission
• Uptime availability target of 99.9%
• Data encryption both in transit and at rest
• Compliance with environmental data security standards

The new IoT water quality monitoring system is expected to provide real-time insights, enabling faster response to water quality issues, reducing environmental risks, and improving regulatory compliance. It aims to support the management of extensive sensor deployments, improve data accuracy, and ensure data security, thereby enhancing operational efficiency and environmental safety.