Fast-Tracking Air Quality Insights for an IIT Madras Incubator Initiative with Dopplr™
How a premier educational and research institution in India leveraged data to identify pollution hotspots for targeted interventions.
Real-time insights on the air quality across various parts of the country to enable exposure assessment and advancing environmental research.
Integration of Dopplr™ to create an optimized routing and personalized exposure assessments and real-time air quality monitoring.
One of India’s premier educational and research institutions were working on a framework to evaluate the air quality index using a combination of distributed IoT devices, remotely sensed data, and advanced ML models. By partnering with Systech, the institution leveraged Dopplr, Systech’s data analytics platform, to achieve faster time-to-insights on exposure levels, road status data, identify pollution hotspots and more.
Data integration emerged as a pivotal concern due to the influx of a substantial amount of data from various IoT devices, intensifying the demand for swift data processing. Additionally, the project faced a significant challenge in equipping data scientists with tools rooted in advanced predictive analytics. The pursuit of rapid innovation and iterative development further compounded the project’s complexity.
THE DETAILED SOLUTION PROCESS:
Dopplr™, Systech’s automated data analytics platform became the pivotal tool to expedite Project Kaatru‘s objectives. Dopplr™s full stack of accelerators with modularity, open APIs and governance to expedite the analytics
- With real-time data harmonization capabilities, DopplrTM seamlessly integrated and standardized data from diverse IoT sources, ensuring a unified data format and structure.
- The dynamic dashboards enabled live monitoring, real-time air quality updates, and hotspot visualization, making the data easily accessible and actionable for stakeholders.
- Dopplr’s ML Studio Integration enabled advanced model training and deployment for predictive air quality analytics, ensuring the delivery of highly accurate predictions.
- The significant reduction in production time accelerated the generation of valuable insights and decision-making.
- Optimized Routing: Utilizing real-time air quality data, users can make informed choices for the cleanest and least polluted routes from Point A to Point B, reducing exposure to air pollutants.
- Exposure Insights: With a customized PM2.5 exposure assessment, users gain insights into their air pollution exposure during travel, enabling well-informed decision-making.
- Road Status Visualization: Dopplr seamlessly combines road condition data with air quality information, allowing users to consider both air quality and road conditions when planning their trips.
- Air Quality Mapping: Dopplr goes a step further by offering a comprehensive Air Quality Map. This map utilizes a Heat map to vividly represent air pollution levels across the user’s route. Users can plan their trips with a clear understanding of the air quality they can expect at each point along their journey.
- Spatio-temporal Hotspot Identification: Dopplr’s data analytics capabilities enable the identification of pollution hotspots across the country. This feature is invaluable for both individual users and policymakers as it helps in understanding areas with consistently high pollution levels, thereby facilitating targeted interventions and initiatives to improve air quality.
THE ADDED VALUE
By seamlessly addressed data integration challenges, Dopplr™ significantly reduced production time, contributing to quick decision-making. Additionally, Dopplr™’s data analytics capabilities enabled optimized routing, personalized exposure assessments, and identification of pollution hotspots. This supported both individual users and policymakers in understanding nationwide pollution areas and facilitating targeted interventions for air quality improvement initiatives. Through a comprehensive and impactful outlook, Dopplr™ reinforced its position as a key player in driving innovation and positive societal impact.
To conclude, Systech’s Dopplr™ solution not only addressed the challenges faced by the partner, but also significantly enhanced their capabilities, resulting in a comprehensive and impactful solution, supporting informed decision-making and advancing environmental research and policy formulation. Dopplr™’s active involvement in cutting-edge AI and machine learning initiatives further solidified its position as a key player driving innovation and positive environmental impact in the ecosystem.
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