In　wastewater　treatment　process　(WWTP),　the　accurate　and　real-time　monitoring　values　of　key　variables　are　crucial　for　the　operational　strategies.　However,　most　of　the　existing　methods　have　difficulty　in　obtaining　the　real-time　values　of　some　key　variables　in　the　process.　In　order　to　handle　this　issue,　a　data-driven　intelligent　monitoring　system,　using　the　soft　sensor　technique　and　data　distribution　service,　is　developed　to　monitor　the　concentrations　of　effluent　total　phosphorous　(TP)　and　ammonia　nitrogen　(NH4-N).　In　this　intelligent　monitoring　system,　a　fuzzy　neural　network　(FNN)　is　applied　for　designing　the　soft　sensor　model,　and　a　principal　component　analysis　(PCA)　method　is　used　to　select　the　input　variables　of　the　soft　sensor　model.　Moreover,　data　transfer　software　is　exploited　to　insert　the　soft　sensor　technique　to　the　supervisory　control　and　data　acquisition　(SCADA)　system.　Finally,　this　proposed　intelligent　monitoring　system　is　tested　in　several　real　plants　to　demonstrate　the　reliability　and　effectiveness　of　the　monitoring　performance.　(C)　2018　The　Chemical　Industry　and　Engineering　Society　of　China,　and　Chemical　Industry　Press.　All　rights　reserved.