With　the　development　of　the　Internet　of　Things　(IoT),　the　amount　of　global　data　is　increasing　rapidly.　However,　due　to　the　increased　burden　of　the　cloud　network,　it　is　difficult　to　implement　low-latency　and　high-efficiency　video　analysis　in　the　cloud　computing　mode.　To　address　this　issue,　this　paper　proposes　an　Intelligent　Video　Analysis　System　(IVAS)　that　can　execute　deep　learning　algorithms　on　low-power　edge　IoT　devices,　such　as　face　detection　and　face　recognition　algorithms.　IVAS　enables　fast,　accurate,　and　real-time　inference　calculations　of　intelligent　video　analysis　algorithms,　providing　an　evaluation　platform　for　performance　testing,　key　parameter　selection,　and　result　analysis.　The　experiments　based　on　real-world　data　confirm　that　IVAS　can　achieve　good　performance　in　people　counting　under　an　edge　computing　environment.　©　2023　IEEE.