Monitoring media broadcast content has deserved a lot of attention lately from both academy and industry due to the technical challenge involved and its economic importance (e.g. in advertising). The problem pose a unique challenge from the pattern recognition point of view because a very high recognition rate is needed under non ideal conditions. The problem consist in comparing a small audio sequence with a large audio stream (the broadcast) searching for matches. In this paper we present a solution with the multi band spectral entropy audio fingerprint (MBSES) which is very robust to degradations commonly found on amplitude modulated (AM) radio. Using the MBSES we obtained perfect recall (all audio ads occurrences were accurately found with no false positives) in 95 hours of audio from five different am radio broadcasts. Our system is able to scan one hour of audio in 40 seconds if the audio is already fingerprinted (with e.g. a separated slave computer), and it totaled five mi...