Today, spatial crowdsourcing concept has been widely applied in various fields. The increasing of mobile user and adoption of social network has catalyst spatial crowdsourcing growth. It has made various types of data to be easily collected and transmitted from different geographical location. However, the massive amounts of task in spatial area bring challenges for the online system to manage especially when the task is heterogeneous, and the interactions are dynamic. Such scenario has alerted the researchers to understand different types of information in order to make task assignment reliable and efficient. This study investigates current state of task assignment for spatial crowdsourcing. It basically, aims to identify several issues like trend in publication and crowd computing areas that studies task assignment in crowdsourcing. We used Systematic Literature Review (SLR) method for analysing the trends and significance of task classification for better dynamic crowd-computing.