Jaloliddin Rustamov
Papers
1
Total Citations
15
H-Index
1
About
Jaloliddin Rustamov is a researcher at the forefront of intelligent automation and industrial safety, whose work bridges the gap between unmanned aerial systems and advanced computational intelligence. His primary research areas encompass computer vision, fuzzy logic systems, and automated defect detection for critical infrastructure. Rustamov’s most significant contribution is his pioneering approach to non-destructive testing, exemplified in his highly cited 2023 paper on automatic visual inspection of oil tank exteriors. In this work, he introduced a novel method that integrates UAVs with cascading fuzzy logic algorithms and image processing to autonomously detect surface defects, particularly corrosion—a pervasive threat to oil and gas storage safety. This innovation, which has already garnered 15 citations, offers a faster, safer, and more reliable alternative to manual inspections, directly impacting asset integrity management in hazardous environments. By combining real-time aerial data with robust decision-making algorithms, Rustamov is shaping the future of predictive maintenance. His research not only advances the field of intelligent inspection systems but also provides a scalable framework for monitoring aging industrial assets, marking him as a rising authority in applied artificial intelligence for engineering safety.
Research Focus
Key Achievements
Top Papers
- 1