It is a major challenge to transfer target sensing data efficiently to sink in Internet of things. The low-efficiency data transmission can cause low quality of service. To realize the emergent detection and periodic data gathering, the sensed data should be transferred to the sink efficiently and quickly. Recently, there are many related studies. However, there are few researches taking energy efficiency, transport delay, and network reliability into comprehensive consideration. In this article, a novel adaptive green and reliable routing scheme based on a fuzzy logic system is proposed in consideration of energy efficiency, end-to-end transport delay, and network transmission reliability. The key idea of the proposed scheme is to generate different number of renewed packet copies after certain steps according to the fuzzy inference. The fuzzy inference reflects the knowledge that the nodes in the region far to the sink and with more remaining energy initiate and transmit more packet copies concurrently by multiple routing paths to ensure the success rate of data transmission, whereas less. Thus, the high energy efficiency and low latency are obtained for data collection. Our analysis and simulation results show that adaptive green and reliable routing is more superior than the existing scheme.