  Tweaking citizen participation is vital in promoting Smart City services.
However, conventional practices deficit sufficient realization of personal
traits despite socio-economic promise. The recent trend of IoT-enabled
smart-objects/things and personalized services pave the way for context-aware
services. Eventually, the aim of this paper is to develop a context-aware model
in predicting participation of smart city service. Hence, major requirements
are identified for citizen participation, namely (a) unwrapping of contexts,
which are relevant, (b) scaling up (over time) of participation. However,
paramount challenges are imposed on this stipulation, such as,
un-observability, independence and composite relationship of contexts.
Therefore, a Non-parametric Bayesian model is proposed to address scalability
of contexts and its relationship with participation.
