Research on developing a smart security system is based on Artificial Intelligence with an unmanned aerial vehicle (UAV) to detect and monitor alert situations, such as fire accidents and theft/intruders in the building or factory, which is based on the Internet of Things (IoT) network. The system includes a Passive Pyroelectric Infrared Detector for human detection and an analog flame sensor to sense the appearance of the concerned objects and then transmit the signal to the workstation via Wi-Fi based on the microcontroller Espressif32 (Esp32). The computer vision models YOLOv8 (You Only Look Once version 8) and Cascade Classifier are trained and implemented into the workstation, which is able to identify people, some potentially dangerous objects, and fire. The drone is also controlled by three algorithms-distance maintenance, automatic yaw rotation, and potentially dangerous object avoidance-with the support of a proportional-integral-derivative (PID) controller. The Smart Drone Surveillance System has good commands for automatic tracking and streaming of the video of these specific circumstances and then transferring the data to the involved parties such as security or staff.

Smart Drone Surveillance System Based on AI and on IoT Communication in Case of Intrusion and Fire Accident / Hoang, Ml. - In: DRONES. - ISSN 2504-446X. - 7:12(2023). [10.3390/drones7120694]

Smart Drone Surveillance System Based on AI and on IoT Communication in Case of Intrusion and Fire Accident

Hoang, ML
2023-01-01

Abstract

Research on developing a smart security system is based on Artificial Intelligence with an unmanned aerial vehicle (UAV) to detect and monitor alert situations, such as fire accidents and theft/intruders in the building or factory, which is based on the Internet of Things (IoT) network. The system includes a Passive Pyroelectric Infrared Detector for human detection and an analog flame sensor to sense the appearance of the concerned objects and then transmit the signal to the workstation via Wi-Fi based on the microcontroller Espressif32 (Esp32). The computer vision models YOLOv8 (You Only Look Once version 8) and Cascade Classifier are trained and implemented into the workstation, which is able to identify people, some potentially dangerous objects, and fire. The drone is also controlled by three algorithms-distance maintenance, automatic yaw rotation, and potentially dangerous object avoidance-with the support of a proportional-integral-derivative (PID) controller. The Smart Drone Surveillance System has good commands for automatic tracking and streaming of the video of these specific circumstances and then transferring the data to the involved parties such as security or staff.
2023
Smart Drone Surveillance System Based on AI and on IoT Communication in Case of Intrusion and Fire Accident / Hoang, Ml. - In: DRONES. - ISSN 2504-446X. - 7:12(2023). [10.3390/drones7120694]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2968859
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