In this paper, the author presented the challenges for autonomous system in indoor climate-controlled environments from the point of view of system integration, monitoring and optimization of energy storage for application of autonomous environment monitoring. In first instance, we proposed the comparison of two different deep learning algorithms for fire detection in order to enable a micro-arial vehicle to automatically detect the fire areas. On the other hand, due a range of limitations (e.g., battery, power computation, etc.) based on the previous experimental analysis presented, an intelligent battery control for an integrated local renewable energy for a climate-controlled greenhouse is presented and verified. Based on the experimental results of the proposed intelligent control strategy, the feasibility and economical cost was verified for an on-grid renewable photovoltaic system with battery energy storages.