High-Resolution Ground-Level AQ Monitoring System Using Hyper-local Low-cost Sensor Nodes and AI Forecasting

PROJECT SUMMARY/ABSTRACT This grant application directly addresses the mission objectives of NIEHS, specifically “Sensors and Other Exposure Assessment Tools”, providing innovative pollutant sensor and AI modelling technologies integrated into wearable devices. We propose demonstrating a truly low-cost sensor node to monitor TPRH, CO, VOCs, and OX (NO2+O3) in the base unit. This node will contain a climate (TPRH) sensor plus revolutionary printed amperometric gas sensors (AGS) developed under prior work. PM, NO2, O3 and SO2 will be available low-cost options. To compensate for environmental effects, aging/drift and cross-sensitivity exhibited by all amperometric gas sensors, the data will be analyzed by an on-board µ-processor using smart algorithms and machine learning (edge-computing). The data transmitted by these nodes will be analyzed in real-time, integrated with data from all other sensors connected to the data platform, and presented on the dashboard. Not only will the resulting technology provide much more accurate data from these very low-cost nodes, but with all sensor data processed and consolidated at the source, much more efficient transfer to data platform with greatly reduced bandwidth requirement is possible. This will allow more comprehensive data analysis, creating the opportunity for real-time chemical modelling to predictively map AQI and pollutant levels in advance to allow people to respond and prepare any needed mitigative measures.