Sensor Network Data Fusion Technology Research And Applications In The Control Of Greenhouse

Sensor Networks(SN) as the new measurement and controlling technology, it is the smart network system which can implement the data collection, data confusion and transfer application. SN combines the logical information word and true physics world. It can achieve the"Pervasive Computing or Ubiquitous Computing"mode in deed. SN is a synthesis technology which refers a lot of knowledge, and brings out many study question of basic theory and engineering technology. Such as how wireless sensor networks to achieve greenhouse automatic monitoring system has already attracted attention in the interest of many researchers.For wireless sensor networks in a greenhouse automatic monitoring of applications, This thesis studies the wireless sensor network data fusion structure and algorithm which. are based on a large number of uncertain data. Based on the analysis of D-S evidence theory , expert system and other algorithms, this thesis presents two-level fusion model which is applicable to wireless sensor networks, proposed for wireless sensor network system integration of two models and give the hybrid algorithm based on these algorithms. This thesis detailed the design and implementation of the data fusion model and the hybrid algorithm.On this basis, this thesis designed and implemented a greenhouse automatic monitoring system model. First of all, local fusion center screen the effectiveness of data and optimize effective data at the process of data fusion; system-level fusion center use the principles of expert system to identify the formation of a systematic framework, the basic probability assignment function value of D-S evidence theory is given by expert system's knowledge. Environmental parameters optimized by the local fusion center, its results transmitted to the system-level fusion center for integration, finally the results of overall integration sent to the expert system rule matching, and give control strategy. Through collecting real-time information of the greenhouse environment parameters and fusing data, we can get precise results to regulate all kinds of parameters of greenhouse in time, and expert system intervention makes greenhouse intelligent control system has been further improve. As a result, we can improve decision-making veracity of greenhouse parameter-regulate, Experiments show that this hybrid algorithm improve the system robustness and practicality.