Modeling unmanned aerial vehicle system for identifying foci of arboviral disease with monitoring system

2021 ◽  
Author(s):  
John David S. Belém ◽  
Hidalyn Theodory C. M. Souza ◽  
Álvaro Sobrinho ◽  
Lenardo Chaves E. Silva ◽  
Helder Fernando De Araujo Oliveira
Keyword(s):  
Monitoring System ◽  
Unmanned Aerial Vehicle ◽  
Low Income ◽  
Colored Petri Nets ◽  
Formal Modeling ◽  
Software Components ◽  
Aerial Vehicle ◽  
Arboviral Diseases ◽  
Potential Risks ◽  
Arboviral Disease

People who live in low-income and hard-to-reach regions are usually the most affected ones by high incidences of arboviral diseases, increasing morbidity and mortality rates, and public health costs. We present the modeling of hardware and software components of an unmanned aerial vehicle (UAV) system by mathematical tools, focusing on monitoring foci of arboviral diseases transmitted by Aedes aegypti mosquito, e.g., Zika, Chikungunya, and Dengue. We used restriction equations and the colored Petri nets formal modeling language to represent the flight dynamics and the software components of the system, respectively. We evaluated the specification of desired behaviors of the monitoring system using simulations and the model checking technique. The results showed the completeness and correctness of the specification. The design of such a system is challenging due to the potential risks to people and the environment. Therefore, this study provides insights into the development of an UAV system for such an application scenario. The monitoring system has the potential of improving the efficiency in identifying foci of arboviral diseases.

scholarly journals Smart Environment Monitoring System using Unmanned Aerial Vehicle in Bangladesh

2018 ◽  
pp. 165995
Author(s):  
Md. Al-Farabi ◽  
Muntasir Chowdhury ◽  
Md. Readuzzaman ◽  
Md. Hossain ◽  
Saifur Sabuj ◽  
...  
Keyword(s):  
Monitoring System ◽  
Unmanned Aerial Vehicle ◽  
Smart Environment ◽  
Environment Monitoring ◽  
Aerial Vehicle

scholarly journals Analysis of an Unmanned Aerial Vehicle Monitoring System for Resurveying of Shipping Routes

2016 ◽  
Vol 3 (1) ◽  
pp. 102-111
Author(s):  
Aleksandrs Urbahs ◽  
Rima Mickevičienė ◽  
Vasilij Djačkov ◽  
Kristīne Carjova ◽  
Valdas Jankūnas ◽  
...  
Keyword(s):  
Monitoring System ◽  
Unmanned Aerial Vehicle ◽  
Survey Methods ◽  
Environment Monitoring ◽  
Vehicle Monitoring ◽  
Hydrographic Survey ◽  
Survey System ◽  
Aerial Vehicle ◽  
Security Operations ◽  
Marine Safety

Abstract The paper gives brief description of the conventional and innovative hydrography survey methods and constraints connected with the realization. Proposed hydrographic survey system based on the use of Unmanned Aerial and Maritime systems provides functionality to conduct hydrographic measurements and environment monitoring. System can be easily adapted to fulfil marine safety and security operations, e.g. intrusion threat monitoring, hazardous pollutions monitoring and prevention operations, icing conditions monitoring.

scholarly journals Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System

Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 502 ◽  
Author(s):  
Jun Ni ◽  
Lili Yao ◽  
Jingchao Zhang ◽  
Weixing Cao ◽  
Yan Zhu ◽  
...  
Keyword(s):  
Monitoring System ◽  
Unmanned Aerial Vehicle ◽  
Crop Growth ◽  
Growth Monitoring ◽  
Aerial Vehicle

scholarly journals Computer vision-based techniques and path planning strategy in a slope monitoring system using unmanned aerial vehicle

2020 ◽  
Vol 17 (2) ◽  
pp. 172988142090430 ◽  
Author(s):  
Qing Li ◽  
Gaochen Min ◽  
Peng Chen ◽  
Yukun Liu ◽  
Siyu Tian ◽  
...  
Keyword(s):  
Monitoring System ◽  
Unmanned Aerial Vehicle ◽  
Semantic Segmentation ◽  
Histogram Equalization ◽  
Visual Features ◽  
Planning Strategy ◽  
Unstructured Environments ◽  
Aerial Vehicle ◽  
Slope Monitoring ◽  
Better Than

Unmanned aerial vehicle is a typical field robot which can work in many unstructured environments like mines, forests, and even radiation areas. In our mine monitoring system built in a northeast province of China, special designed unmanned aerial vehicle is applied to take photos and perceive the environment. We select a series of image-based techniques to process aerial pictures to monitor the slope. The visual features are initially refined by histogram equalization. Then, the rocks and cracks can be detected by different digital image processing operators, like Canny, so as to assess displacements. Advanced semantic segmentation model, U-Net, is also selected to process the problem. Experimental results show that both Canny and U-Net can perceive the edges in pictures effectively, better than other operators. In addition, we model the inspection mission for mine slopes into a traveling salesman problem, then plan the path for unmanned aerial vehicle by swarm intelligence-based optimization.

scholarly journals Unmanned Aerial Vehicle-Borne Sensor System for Atmosphere-Particulate-Matter Measurements: Design and Experiments

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 57 ◽  
Author(s):  
Tonghua Wang ◽  
Wenting Han ◽  
Mengfei Zhang ◽  
Xiaomin Yao ◽  
Liyuan Zhang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Monitoring System ◽  
Data Storage ◽  
Unmanned Aerial Vehicle ◽  
Three Dimensional ◽  
Correction Method ◽  
Wireless Data Transmission ◽  
Aerial Vehicle ◽  
Highly Correlated ◽  
Pm2.5 And Pm10

An unmanned aerial vehicle (UAV) particulate-matter (PM) monitoring system was developed that can perform three-dimensional stereoscopic observation of PM2.5 and PM10 in the atmosphere. The UAV monitoring system was mainly integrated by modules of data acquisition and processing, wireless data transmission, and global positioning system (GPS). Particularly, in this study, a ground measurement-control subsystem was added that can display and store collected data in real time and set up measurement scenarios, data-storage modes, and system sampling frequency as needed. The UAV PM monitoring system was calibrated via comparison with a national air-quality monitoring station; the data of both systems were highly correlated. Since rotation of the UAV propeller affects measured PM concentration, this study specifically tested this effect by setting up another identical monitoring system fixed at a tower as reference. The UAV systems worked simultaneously to collect data for comparison. A correction method for the propeller disturbance was proposed. Averaged relative errors for the PM2.5 and PM10 concentrations measured by the two systems were 6.2% and 6.6%, respectively, implying that the UAV system could be used for monitoring PM in an atmosphere environment.

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