i-Dris integrates 5G mmWave base station and reconfigurable intelligent surface (RIS) for improving signal coverage/throughput. We design multi-time scaled temporal reinforcement learning for RIS deployment equipped on auto-guided vehicle, which determines future actions from both historical and current rates observed from the edge server. Under blockages and non-line-of-sight, i-Dris can achieve 800~900 Mbps rate (1.2~3.6x more compared to non-RIS). i-Dris only requires 10-min of deployment time (1 hr for other methods). Compared to existing prototypes in academia/industry, i-Dris does not need fiber, huge human resources, re-measurement and offline training. It learns from historical data guaranteering robustness to changing environments.