- Tytuł:
- A cloud-based urban monitoring system by using a quadcopter and intelligent learning techniques
- Autorzy:
-
Khanmohammadi, Sohrab
Samadi, Mohammad - Powiązania:
- https://bibliotekanauki.pl/articles/27314186.pdf
- Data publikacji:
- 2022
- Wydawca:
- Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
- Tematy:
-
urban monitoring
cloud computing
quadcopter
deep learning
fuzzy system
image processing
pattern recognition
bayesian network
intelligent techniques
learning systems - Opis:
- The application of quadcopter and intelligent learning techniques in urban monitoring systems can improve flexibility and efficiency features. This paper proposes a cloud-based urban monitoring system that uses deep learning, fuzzy system, image processing, pattern recognition, and Bayesian network. The main objectives of this system are to monitor climate status, temperature, humidity, and smoke, as well as to detect fire occurrences based on the above intelligent techniques. The quadcopter transmits sensing data of the temperature, humidity, and smoke sensors, geographical coordinates, image frames, and videos to a control station via RF communications. In the control station side, the monitoring capabilities are designed by graphical tools to show urban areas with RGB colors according to the predetermined data ranges. The evaluation process illustrates simulation results of the deep neural network applied to climate status and effects of the sensors’ data changes on climate status. An illustrative example is used to draw the simulated area using RGB colors. Furthermore, circuit of the quadcopter side is designed using electric devices.
- Źródło:
-
Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 2; 11--19
1897-8649
2080-2145 - Pojawia się w:
- Journal of Automation Mobile Robotics and Intelligent Systems
- Dostawca treści:
- Biblioteka Nauki
Artykuł