Ahmad Farhan Aristo
Papers
1
Total Citations
3
H-Index
1
About
Ahmad Farhan Aristo is a researcher focused on advancing intelligent systems for safety and automation, with key contributions in multi-robot coordination and fire detection using computer vision. His most cited work, "SISTEM DETEKSI MULTI-ROBOT DAN API MENGGUNAKAN IMAGE PROCESSING BERBASIS ALGORITMA YOLO" (2020), addresses the critical need for efficient fire detection in high-risk environments like office buildings, residential areas, and forests. By integrating the YOLO algorithm with image processing, Aristo developed a system that enables robots to autonomously detect and respond to fires, reducing reliance on human monitoring. This work, with 3 citations, demonstrates his ability to apply deep learning to real-world safety challenges. Aristo’s research sits at the intersection of robotics, artificial intelligence, and disaster mitigation, offering scalable solutions for early fire warning and multi-agent coordination. His contributions are particularly valuable for students and researchers exploring autonomous systems, object detection, and human-robot interaction in hazardous settings. Through his innovative use of YOLO-based detection, Aristo continues to push the boundaries of how intelligent machines can safeguard lives and property.
Research Focus
Key Achievements
Top Papers
- 1