Avian Influenza (AI) caused an annual epidemic outbreak that led to destroying tens of millions of poultry worldwide. Current gold standard AI diagnosis method is an embryonic egg-based hemagglutination assay followed by immunoblotting or PCR sequencing to confirm subtypes. It requires, however, specialized facilities to handle egg inoculation and incubation, and the subtyping methods relied on costly reagents. Here, we demonstrated the first differential sensing approach to distinguish AI subtypes using series of cell lines and fluorescent sensor. Susceptibility of AI virus differs depending on genetic backgrounds of host cells. Thus, we examined cells from different organ origin, and the infection patterns against a panel of cells were utilized for AI virus subtyping. To quantify AI infection, we designed a highly cell-permeable fluorescent superoxide sensor to visualize infection. Though many AI monitoring strategies relied on sophisticated antibody have been extensively studied, our differential sensing strategy successfully proved discriminations of AI subtypes and demonstrated as a useful primary screening platform to monitor a large number of samples.