احسان عظیمی راد

Agricultural industries with other important industries in the country require to the use of sensors, detectors and gas analyzers. The main task of these analyzers is to detect of the different gases types and environmental pollutants and analyze the information obtained from it, to determine the physiological quality of plant growth, measure the shelf life of harvested organs, such as flowers, fruits and suchlike. Saffron is one of the strategic products of the southern and central regions of greater Khorasan, which has unique characteristics in various aspects, from the effect on employment, the economy of these regions and productivity in the consumption of agricultural inputs, such as water. Production of saffron at current costs will be cost-effective only if its growth is modeled in the climatic conditions of different regions of Khorasan and by carefully examining gas exchanges and recommending the use of inputs based solely on precise agricultural principles. On the other hand, the short life of saffron flowers, which makes the processing mechanism difficult (harvesting, separating and drying the flower components), can be increased by carefully studying gas exchanges. In this paper, an electronic system based on electrochemical sensors is presented, which, by simulating the interaction of gases, detects the gases types in the environment around the saffron plant and displays them on the screen. Analysis of the information obtained from the amount of gases detected around of the plant (in terms of PPM and VOL (%)), can provide solutions by agricultural and saffron researchers to improve the quality of growth, maintain flowers longer in the post-harvest period and the possibility of provide saffron production with controlled gas conditions in the greenhouse environment.

By integrating data into multi-sensor networks, the uncertainty and ambiguity in C4I systems is reduced and in these systems, the complexity and execution time of operational computations based on the operating environment is reduced. This successful combination of data and information is accomplished by a variety of models and architectures that have been proposed for implementation in a variety of military and civilian applications. A robust and organized strategy in the operation environment is needed to facilitate the solution of the problem before performing the process of integrating the data received from the sensors. Due to differences in military and civilian applications of data fusion, it is not possible to create a single hardware and software platform for data fusion in the C4I system. In this system, due to the high volume and importance of processing and information exchange speed, the use of data fusion technology to increase the accuracy and reliability of output results due to the operational cycle of each of the data integration models and architectures, is necessary. This paper, reviews the types of different models and architectures integrated to assess the threat in the C4I system, and introduces their features and applications, and examines the challenges associated with each. Recognition these models and architectures is the way for proper planning to select an optimal and efficient model for assessing the threat of different targets in multi-sensor integrated networks in C4I systems.