This paper concerns stopping-time management of smart sensing nodes, a kind of very large scale integration system, based on the tradeoffs between sensing accuracy and power consumption, which are foundations of Internet of Things systems and cyber-physical systems. In practice, smart sensing nodes work periodically, and more samples leads to higher accuracy but more energy cost, so when to stop sampling in a periodic cycle to achieve the optimal tradeoff is an interesting issue. This paper formulates this issue as a partially observable Markov decision process (POMDP) and develops a POMDP-based Optimal Stopping-time Algorithm to make the above tradeoff. Field experiments demonstrate its performance.