Integration of gas and dust detection sensors with human detection and LORA communication on drones for smart campus surveillance patrols at UNHAN RI - Adama, Audirialy Naufal; Nurjaman, Ahmad Idlof; Faariz H, Naufal; Ariateja, Dananjaya; Sunarta, Sunarta (Jurnal Mandiri IT, 2025)
To improve the effectiveness of environmental monitoring and security activities in open areas or the UNHAN RI Smart Campus, this study provides solutions and recommendations, namely the integration of gas and dust detection sensors with a human detection system based on drones and LoRa as the communication protocol. Drones equipped with gas sensors such as the MQ-135 and dust particle sensors like the Nova PM SDS011 can monitor air quality in real-time. Additionally, a camera-based human detection system combined with an Artificial Intelligence algorithm such as YOLOv8, along with LoRa SX1278 as the communication protocol, can detect the presence of humans or intruders in the patrol area. The integration of these two systems can facilitate campus security personnel in using drones for automatic patrols, monitoring and assessing air pollution levels, and identifying individual movements in the monitored area simultaneously. Test results indicate that the combination of sensors and data processing systems based on the ESP8266 microcontroller on the drone device, along with communication protocols using LoRa SX1278, can provide sufficiently accurate visual and numerical information to support rapid response decisions in emergency situations such as theft, fires, and illegal activities within the UNHAN RI smart campus zone. This research can serve as an initial step toward developing an autonomous multi-sensor drone system based on Artificial Intelligence for integrated surveillance patrol tasks in the future.