The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter

Abstract

This study presents a detailed analysis of an air monitoring development system using quadcopters. The data collecting method is based on gas dispersion investigation to pinpoint the gas source location and determine the gas concentration level. Due to its flexibility and low cost, a quadcopter was integrated with air monitoring sensors to collect the required data. The analysis started with the sensor placement on the quadcopter and their correlation with the generated vortex. The reliability and response time of the sensor used determine the duration of the data collection process. The dynamic nature of the environment makes the technique of air monitoring of topmost concern. The pattern method has been adapted to the data collection process in which area scanning was marked using a point of interest or grid point. The experiments were done by manipulating a carbon monoxide (CO) source, with data readings being made in two ways: point source with eight sampling points arranged in a square pattern, and non-point source with 24 sampling points in a grid pattern. The quadcopter collected data while in a hover state with 10 s sampling times at each point. The analysis of variance method (ANOVA) was also used as the statistical algorithm to analyze the vector of gas dispersion. In order to tackle the uncertainty of wind, a bivariate Gaussian kernel analysis was used to get an estimation of the gas source area. The result showed that the grid pattern measurement was useful in obtaining more accurate data of the gas source location and the gas concentration. The vortex field generated by the propeller was used to speed up the accumulation of the gas particles to the sensor. The dynamic nature of the wind caused the gas flow vector to change constantly. Thus, more sampling points were preferred, to improve the accuracy of the gas source location prediction.

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

“…Given the quite limited payload that needs to be shared among multiple sensors, some research efforts have been devoted to the design of lightweight gases sensing units for UAV nodes [144,145]. Finding the optimal placement of air monitoring sensors on UAV platforms is another challenging issue, given that the sampling and estimation processes are strongly affected by the dynamic nature of the wind and by the vortex fields generated by the propellers [146,147]. The high spatial and temporal sensing capabilities of UAV nodes have been also employed to build fine-grained air quality index (AQI) maps.…”

Advanced Intelligent Control through Versatile Intelligent Portable Platforms

“…A portable air scanning system was developed using a quadcopter, equipped with an air scanning sensor to perform air quality measurements. Using the Computational Fluid Dynamic (CFD) simulation, the vortex field generated by the propeller was analyzed to determine the best place for sensor mounting in order to increase the response and the accuracy of the sensor-collected data [ 8 ]. The grid pattern, with a point source and non-point source, and a wind algorithm were integrated into the gas measurement process.…”

Multi-sensor optimal deployment based efficient and synchronous data acquisition in large three-dimensional physical similarity simulation

“…The effective modal mass participation ratio was introduced to ensure the validity of the initial data for optimal sensor deployment (Gao et al, 2021). Moreover, some scholars used a bivariate Gaussian kernel analysis method to address the uncertainty of the external environment and estimate the zone of a gas source (Kuantama et al, 2019). In conclusion, many scholars have addressed the sensor arrangement optimization problem by calculating the measurement weights of each location through the probability distribution of event occurrence, and finally, they obtained the OSP locations in each measurement zone.…”