Smart Sensing Network for Urban Air Quality Monitoring
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Solution Overview
Problem
Current air pollution monitoring systems are limited by the high cost and bulkiness of lab instruments, which restrict the number and location of monitoring stations, resulting in inadequate spatial air quality monitoring, especially in urban areas.
Innovation Solution
A smart sensing network comprising low-cost, fixed or mobile sensor nodes and sensor bases, where sensor nodes provide real-time air quality monitoring data and sensor bases serve as data references for correction, enabling a high-density sensing network for spatial air quality monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive and bulky lab instruments are used for air pollution monitoring, then measurement precision is improved, but device complexity and installation cost increase
Solution Approach 1:
The system divides the monitoring network into two segments: sensor bases with high-precision lab instruments for reference measurements, and sensor nodes with low-cost sensors for widespread deployment. This segmentation allows each component to have optimized functionality - sensor bases ensure accuracy while sensor nodes reduce complexity and cost.
Solution Approach 2:
Sensor bases act as intermediaries that provide reference measurements to correct and calibrate sensor node data. The sensor bases serve as mediator points between the complex lab instruments and the simple sensor nodes, transferring calibration information to improve overall network accuracy without requiring every node to have complex equipment.
2Measurement precision
If expensive lab instruments are deployed, then measurement precision is improved, but the number of monitoring stations decreases
Solution Approach 1:
The monitoring system is segmented into sensor bases (few in number, high precision) and sensor nodes (many in number, low cost). This segmentation enables a hierarchical structure where a small number of expensive instruments support a large network of inexpensive sensors, achieving both precision and quantity.
Solution Approach 2:
Instead of deploying multiple expensive lab instruments, the system uses one or few sensor bases as reference copies that calibrate numerous sensor nodes. The reference measurements from sensor bases are copied and applied to correct sensor node data, enabling many monitoring points without multiplying the expensive equipment.
3Measurement precision
If traditional monitoring stations are installed, then measurement precision is improved, but spatial coverage decreases
Solution Approach 1:
The system segments monitoring functions between sensor bases (providing reference accuracy) and sensor nodes (providing spatial coverage). Sensor nodes can be deployed in dense urban areas with limited space, while sensor bases are installed in locations suitable for lab instruments, achieving both precision and widespread coverage.
Solution Approach 2:
Different locations in the monitoring network have different qualities: sensor bases are placed where reference measurements are needed, while sensor nodes are distributed throughout the city including urban areas. Each location's monitoring point has the appropriate instrument type for its specific needs, optimizing both accuracy and coverage.
4Area of stationary object
If low-cost sensors are used to increase spatial coverage, then area coverage is improved, but measurement precision deteriorates
Solution Approach 1:
Sensor bases provide feedback reference measurements to sensor nodes for data correction. The high-precision sensor base data feeds back into the network to calibrate and correct the lower-precision sensor node measurements, maintaining accuracy across the expanded spatial coverage.
Solution Approach 2:
Sensor bases serve as intermediaries that mediate between the low-cost sensor nodes and the true air quality conditions. By providing reference measurements and correction factors, sensor bases enable sensor nodes to achieve better accuracy than they would alone, bridging the gap between low cost and high precision.
Data Source
AI summary
Embodiments are described of a sensing network including one or more sensor nodes, wherein each of the one or more sensor nodes includes a gas sensor that can measure the presence, concentration, or both, of one or more airborne pollutants in a nodal coverage area surrounding the sensor node. A sensor base that can measure the presence, concentration, or both, of one or more airborne pollutants is positioned in the nodal coverage area of each of the one or more sensor nodes, wherein the sensor base includes a gas sensor with higher accuracy, higher sensitivity, or both, than the gas sensors of the one or more sensor nodes. One or more servers communicatively coupled to the sensor base and the one or more sensors nodes. The sensor base and the sensor nodes can communicate their measurements to the server and the measurements of the sensor base are used by the server as a reference to correct the measurements of the one or more sensor nodes.