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All Journal Jurnal Telkommil
Rio Prabowo, Choirul
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Computer Science & IT Control & Systems Engineering Engineering

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Teknologi Automatic Spraying System for Plants based on Leaf Image Detection by Using Raspberry Pi Camera Model V2: Telekomunikasi Barokah, Ade; Rio Prabowo, Choirul
Jurnal Telkommil Vol. 6 No. 2 (2025): Jurnal Telkommil
Publisher : Pustaka Poltekad

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Abstract

The utilization of automated systems to increase crop maintenance efficiency, especially in fertilizer and pesticide application, has been prompted by advancements in precision agriculture technology. Using a camera module as an automated spraying controller to detect leaf images is one creative method. The integration of the Raspberry Pi v2 Camera Module with digital image processing methods in automated spraying systems is the subject of a comprehensive review of earlier research presented in this article. Actuator control in the system, analysis of leaf detection techniques, and a review of recent journal literature are some of the techniques employed. The study's findings show that real-time implementation of this technique which includes color thresholding and texture analysis for leaf detection can be accomplished with good accuracy. The Raspberry Pi v2 Camera Module offers advantages in color image and easy integration with microcontroller. In conclusion, an automated spraying system based on leaf image detection shows great potential in reducing chemical waste and improving spraying precision, although challenges remain related to lighting conditions and crop types. Further research is needed to improve system performance under various field conditions.
Tecnology FPV Camera Gimbal Controller Design Synchronized with the SS2 Weapons Platform on an IMU-Based Quadcopter Drone : Telkommil Supadmana Muda , Nur Rachman; Rio Prabowo, Choirul
Jurnal Telkommil Vol. 6 No. 2 (2025): Jurnal Telkommil
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/kom.v6i2.635

Abstract

The development of drone technology has driven innovation in the integration of surveillance and weapons systems. This research designs and builds a First Person View (FPV) camera gimbal controller system that can be synchronized directly with the movement of the NR version of the SS2 weapon platform on a quadcopter drone. This system utilizes an Inertial Measurement Unit (IMU) sensor to read the drone's orientation and adjust the gimbal position in real-time to maintain alignment with the target. Tests were conducted at various maneuver angles to verify the gimbal's accuracy, stability, and response to drone movements. The results show accurate synchronization with minimal latency. This controller system uses an STM32 microcontroller and an MPU-6050 IMU sensor as its main components, combined with precision servo motors for gimbal axis drive. The FPV camera is calibrated to remain focused on the SS2 weapon barrel in all orientation conditions. This system integration allows operators to monitor and accurately direct targets remotely via FPV video. Test data shows that the system's stability is maintained even under high vibration conditions and extreme movements. The implementation of this system has great potential for application in tactical military drone applications and security surveillance.
Co-Authors Barokah, Ade Supadmana Muda , Nur Rachman