Precision farming is aglimpse to the future of agriculture in that management of agricultural production inputs such as fertilizer, lime, herbicide; seed and so on is implemented based on local features of farm. The more precision application of inputthrough exact farming leads to reduce costs, increase farm income and reduce adverse environmental impacts. Iran, as a developing country should be able to use precision farming technologies in agricultural development programs in the future. In this regard, a study was conducted in Ardabil province to study the effective factors and barriers on the implementation of precision agriculture from the perspective of agricultural experts of this province in 2011. This research is quantitative considering paradigm and it’s applied considering research purpose. And also comparative-causative researchmethod is used in this research and since there was identification and field searching, the research was survey research. Participants of this study were experts of agriculture center of agricultural researches and center of agricultural training in Ardabil province (N=365) who had BA or MA degree in one of the branches of agricultural engineering and were employed in one of the mentioned organizations. Research results showed that Cronbach's alpha was calculated for Likes spectra questions that result was .96. With regard to the obtained results it was evident that the effectiveness amount of challenges and barriers to implement precision farming in Ardabil with the mean of 3.94 and standard deviation of .92 is "excessive".In this section the greatest impact is related to "investment costs”with the mean value of 3.92 and standard deviation of 1.05and the least impact is related to the “process’s being timeconsuming," with the mean value of 3.49 and standard deviation of 1.07 respectively. And also correlation amount of KMO equals to .70 that is indicator of fitness of existent correlations between data to factorial analysis. Using factorial analysis technique, four factors with specific values were found greater than 1. And variables as challenges and difficulties that are affecting the implementation of precision agriculture are classified based on the factorial loads and after orthogonal factorial rotation by varimax method in these factors and these factors have explained 62.75percent of the total variance and only less than 37.23 percent of rest variance were related to the factors that are not identified through factorial analysis. Number of extracted factors is given along with specific values of each one, variance value of factors and cumulative variance percent of factors. Given the specific values of extracted factors, the "insight related" factor with variance values of 88.16 played a major role in defining the variables. Then, the "agricultural" factor, "educational and promotional” factor and “financial and equipment related" factorswere respectively in the next ranks.