Droplet　microfluidics　has　gained　widespread　attention　in　recent　years　due　to　its　advantages　of　high　throughput,　high　integration,　high　sensitivity　and　low　power　consumption　in　droplet-based　micro-reaction.　Meanwhile,　with　the　rapid　development　of　computer　technology　over　the　past　decade,　deep　learning　architectures　have　been　able　to　process　vast　amounts　of　data　from　various　research　fields.　Nowadays,　interdisciplinarity　plays　an　increasingly　important　role　in　modern　research,　and　deep　learning　has　contributed　greatly　to　the　advancement　of　many　professions.　Consequently,　intelligent　microfluidics　has　emerged　as　the　times　require,　and　possesses　broad　prospects　in　the　development　of　automated　and　intelligent　devices　for　integrating　the　merits　of　microfluidic　technology　and　artificial　intelligence.　In　this　article,　we　provide　a　general　review　of　the　evolution　of　intelligent　microfluidics　and　some　applications　related　to　deep　learning,　mainly　in　droplet　generation,　control,　and　analysis.　We　also　present　the　challenges　and　emerging　opportunities　in　this　field.