Real-time IoT Air Quality Monitoring Dashboard Development

The client requires an integrated system capable of collecting, processing, and visualizing data from distributed IoT air quality sensors in real-time. Current limitations include lag during data visualization, inefficient cluster management on interactive maps, and lack of customization options for end-users potentially affecting user engagement and operational efficiency.

A global telecommunications company deploying IoT sensors for indoor and outdoor air quality monitoring, aiming to provide real-time data visualization and analytics for their users and management teams.

• Implement a real-time data collection and processing pipeline for IoT air quality sensors worldwide.
• Develop an intuitive web dashboard that visualizes sensor data geographically with interactive features.
• Optimize map rendering performance for large sets of sensors using clustering and server-side solutions.
• Enable user customization of dashboard tiles, including adding, removing, dragging, and resizing components.
• Provide data export capabilities in CSV format for further analysis.
• Set up alert and monitoring systems to notify users of poor air quality conditions.
• Ensure system scalability, responsiveness, and security to handle growth and sensitive data.

• Real-time data ingestion from distributed IoT air quality sensors.
• An interactive, geolocated map displaying device locations using clustering for performance optimization.
• Customizable dashboard tiles allowing users to add, remove, drag, and resize data visualizations.
• Multiple device data tiles summarizing overall sensor metrics and individual sensor tiles for detailed data.
• Automated monitoring and alert system for detecting poor air quality levels and notifying users.
• CSV data export functionality for external analysis.
• Optimized server-side rendering and map image management for fast loading and transition performance.

• IoT sensors data streaming services or APIs
• Notification and alerting services (e.g., email, SMS)
• External data sources for supplementary environmental data if applicable

• System capable of supporting a large number of IoT devices with no significant lag during map transitions
• Map rendering optimized via clustering, server-side rendering, and raster image preloading
• High availability and reliable real-time data processing
• Robust security for user data and sensor information
• Scalable architecture to accommodate future growth in device numbers and users

The developed system will enable the client to facilitate global air quality monitoring, enhance user engagement through a customizable dashboard, and open opportunities to attract new markets. The platform is expected to support real-time insights and proactive alerts, significantly improving operational decision-making and environmental analysis, ultimately leading to increased user satisfaction and potential revenue growth.