## 10 Conclusions  
As an important part of IoT, WSNs have been widely used in fields such as wildlife protection, intelligent transportation, cultural relic protection and military investigation, etc. However, sensor nodes [26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40] more easily fail to work than traditional network nodes due to being battery-powered. Therefore, it is a challenge to maintain high quality and low energy consumption in WSN applications. To improve the hardware is a way to deal with the problem, but the cost is higher and the existing technology is a further limitation. Another way is to improve the software, in a wireless network environment, network coding is often used to reduce the number of radio-frequency emission of nodes, save the energy consumption of nodes and increase network throughput, etc. At present, however,most of the researches on network coding are based on the following two hypotheses: One is that all the links in the network have the same transmission success rate. The other is that each link has the same transmission success rate in its two directions. However, in an actual network, due to the unstable communication channels, the transmission power of nodes limited by battery voltages and so on, the two hypotheses could not be fully met. Thus, the current network coding technology hardly gets coding opportunities in a practical application, which makes them incapable of enhancing the network performance and saving the energy of nodes.  
This paper proposes an adaptive network coding routing scheme--a routing decision model which can automatically sense network coding opportunities. This model applies the network coding to an actual network where there are various transmission success rates on the links and different transmission success rates in two directions of a link. By optimizing routing decisions, the model can get more coding opportunities to decrease the number of broadcast transmission in the network, reduce the network delay and energy consumption, and improve the network throughput. In this paper, we firstly established the network topological graph and the data stream model on the network. Then we established a routing path with the traditional NCR and applied the neighborhood search algorithm to adjust the path(s) to reduce the total number of broadcast transmission in the network. The simulation results showed that, compared with NCR, ANCR could reduce the network delay by about 50% and increase the network throughput by 66.67%. The energy consumption of nodes could decrease with the increase of data streams in the network.  
Although ANCR mainly deals with the problem in WSN applications, it can also be a good reference in other wireless networks.  
This work was supported in part by the National Natural Science Foundation of China (no. 61572402, no. 61672428, no. 61602382, no. 61501372, no. 61272286) and the Science Foundation of Northwest University (no. 15 NW32 and no. 15 NW31)and Natural Science Basic Research Plan in Shaanxi Province of China (no. 2012)Q8049). [PERSON], [PERSON] and [PERSON] conceived and designed the experiments; [PERSON], [PERSON] and [PERSON] performed the experiments and analyzed the data; [PERSON], [PERSON] and [PERSON] wrote the paper; [PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] participated in paper revision and made many suggestions. All authors read and approved the final manuscript.  
The authors declare that there is no conflict of interests regarding the publication of this paper.