<p>The importance of Internet of Things (IoT) based irrigation systems in modern agriculture and landscaping is significant and multifaceted, addressing various challenges and bringing numerous benefits. It is crucial to evaluate the suitability of different smart irrigation system based on multiple criteria, including water efficiency, cost, ease of integration, durability, scalability and various other factors. Various approaches can be utilized to determine the best option based on different parameters. The ambiguity and uncertainty around phenomena are handled by fuzzy sets. Several fuzzy set extensions are proposed by different researchers. Intuitionistic fuzzy (IF) set is an extension of fuzzy set used for managing uncertainty in more complex situations when fuzzy sets are unable to produce reliable results. Picture Fuzzy (PF) sets, an extension of IF sets, incorporate an additional degree of freedom by considering positive, neutral, and negative membership degrees, thus providing a more nuanced representation of uncertainty. This paper outlines a technique in PF environment to solve the problem of selection of IoT based smart Irrigation system relative to different factors. A new PF knowledge measure is proposed to measure the amount of knowledge linked to PF sets. Reliability and utility of introduced knowledge measure is tested using some numerical examples. A new score function is proposed to compare the PF numbers which can get around the drawbacks of the current scoring functions. Besides this, a new multi criteria decision making technique is provided to select the best alternative by using the suggested scoring function and the PF knowledge measure.</p>