Proposing an Appropriate Soil Water Content Estimation Technique for Iran

Limitation of water resources is one of the major factors in the agricultural development of Iran. In recent years. Iran suffers from increases water consumption and drought conditions, This is why efficient water management in agriculture production becomes an inevitable requirement. One of the main aspects of water management in agriculture production is operating any type of irrigation system efficiently. A good on-farm irrigation water management requires a routine monitoring of soil water content (SWC). Recently a substantial number of different experimental methods in categories of direct, indirect, ground based and remote sensing have been developed to determine the SWC, and a large body of knowledge is now available on theory and applications. The need for indirect ground-based automatic methods for obtaining water content or indices of water content is evident when the time and labor involved in direct sampling is considered. In view of Iran conditions, selecting the best soil water measurement technology for the optimal management of irrigation system is a challenge for managers and the decision makers. This research aims to (i) compile the available ground based SWC measurement methods and discuses along with their advantages and their limitations, (ii) propose a technique that will be most useful for Iran condition. Considering regional parameters of Iran, these researchers found tensiometers as a proper technique for good water management. This technique with lower price in addition with other advantages could be more effective in development of Iran Agricultural Mechanization

Proceedings of the 10th international conference on disability, virtual reality and associated technologies (ICDVRAT 2014)

The proceedings of the conferenc

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems