Evaluation of Selected Algorithms for Air Pollution Source Localisation Using Drones

Suchanek, Grzegorz; Wołoszyn, Jerzy; Gołaś, Andrzej

doi:10.3390/su14053049

Cited by 5 publications

(1 citation statement)

References 29 publications

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“…The EMS was first applied to AGVs used on a production line to remotely monitor and visualize their status during operation. However, the drone is another piece of automated guided equipment (AGE) that is used in various industries, such as agriculture [7], disaster management [8], and environmental monitoring and management [9,10]. The EMS was extended to include transportation of items using a drone.…”

Section: Introductionmentioning

confidence: 99%

On the Construction of an Edge-Based Remote Sensing Framework: The Applications on Automated Guided Vehicles and Drones

2022

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To monitor the status and mission progress of automated guided vehicles (AGVs), most platforms typically obtained real-time data through a data acquisition system that is deployed on the end vehicles. The data acquired from an end vehicle are generally sparse but are required frequently, and an examination process using cloud storage cannot commence until the device’s raw data are received. To reduce communication costs, the proposed edge-based monitoring system (EMS) applies edge computation to move the data examination from the cloud to an end site. The data buffered in the end device could be pre-processed by some detectors. For example, checking the energy is adequate for returning to the base. Thus, buffering data on the end device helps to minimize the time required by the decision maker for abnormal events, e.g., shutdowns caused by exhausted energy. In addition to adopting the common methods of storing, processing, and analyzing data at the data center, the EMS moves some time-sensitive services to the end vehicle. Moreover, after obtaining real-time motion data, the edge computing architecture immediately targets abnormal actions and sends reaction commands to shorten the decision making delay caused by the communication cost between the end vehicles and cloud storage sites, thereby avoiding collisions or accidents. The EMS has been implemented to monitor AGV and unmanned aerial vehicles. The EMS primarily monitored the power and motion of the vehicles. It also combined task-oriented motion commands for monitoring unexpected vehicle motions during tasks. If an abnormal event occurred, immediate warnings were provided through a notification interface and were immediately processed by the EMS to ensure safety during task execution. After checking data consistency between the EMS and the real device, the EMS reveals the corrected status of the device with very little delay. Therefore, the EMS could help with minimizing the time taken to make decisions. Moreover, the EMS has been modified to be deployed on drones to confirm its cross-platform applicability. In the simulations of drones, the EMS also got similar results to the simulations of AGVs. Therefore, the EMS could reduce the time in examining abnormal events and has cross-platform functionality.

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Section: Introductionmentioning

confidence: 99%

On the Construction of an Edge-Based Remote Sensing Framework: The Applications on Automated Guided Vehicles and Drones

2022

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Precision co-composting of multi-source organic solid wastes provide a sustainable waste management strategy with high eco-efficiency: a life cycle assessment

Wang,

Liu,

Wang

et al. 2024

Environ Sci Pollut Res

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Design and Implementation of a Particulate Matter Measurement System for Energy-Efficient Searching of Air Pollution Sources Using a Multirotor Robot

2023

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Analyzing air pollutants is of key importance for the environmental protection goals. High concentrations of particulate matter (PM) have a particularly negative impact on human life and health. The use of an autonomous multirotor flying robot (drone) for the purposes of locating PM sources requires the design of a dedicated measurement system from scratch. The aim of this study was to make the most important design decision, which is the correct localization of the inlet of the measurement system, taking into account disturbances in the flow field caused by the rotors. To achieve this, a computational model was built with the use of a finite-volume method in Ansys Fluent software. Based on its results, a novel criterion was proposed and applied. In addition to the trivial position outside the rotors on the extended arm, it gave the second location in the space limited by the rotors below the robot. Finally, a robot prototype was built, and a series of verification experiments were carried out, first indoors and then outdoors, at different levels of ambient PM concentrations with and without a pollution source. The field results were compiled as histograms and scatter plots and clearly demonstrated the validity of the adopted criterion. The determination coefficient between measured concentrations showed a stronger relationship when the rotors were operating. Furthermore, in cases with a present pollution source, higher concentrations were observed around the internal sensor, making it more suitable for the studied application.

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Evaluation of Selected Algorithms for Air Pollution Source Localisation Using Drones

Cited by 5 publications

References 29 publications

On the Construction of an Edge-Based Remote Sensing Framework: The Applications on Automated Guided Vehicles and Drones

On the Construction of an Edge-Based Remote Sensing Framework: The Applications on Automated Guided Vehicles and Drones

Precision co-composting of multi-source organic solid wastes provide a sustainable waste management strategy with high eco-efficiency: a life cycle assessment

Design and Implementation of a Particulate Matter Measurement System for Energy-Efficient Searching of Air Pollution Sources Using a Multirotor Robot

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