Without the need for hand-coding, Machine Learning helps systems to enhance and develop dynamically from their experiences. As a result, numerous tech firms have been creating Artificial Intelligence applications in recent years. The majority of irrigation systems available today allow customers to program them to provide a specified amount of water at specific times. On the other hand, a garden frequently has a variety of plants, each of which needs a varying amount of water. This research planned an irrigation system that uses deep learning to regulate the quantity of water given to each type of plant based on plant identification to address this problem. The software and hardware are the two primary constituents of the technology. The former is linked to cameras for plant identification and uses a database to determine the appropriate amount of water; the other regulates the amount of water that can flow out. The technology is designed to predict how long to water the plants after discovering the perfect soil moisture with the applications and incorporating it with the outcome of the existing soil moisture level with the Arduino. This will allow the program to modify the software in the irrigation system controller to alter the period of time the regulator should be kept open.
In this article, the development of a technology for the production of clinkers and cements based on them using previously unexplored alternative sources of local raw materials in Karakalpakstan is studied, is an effective solution to the problem of covering the cement industry’s construction industry needs. Development of practical recommendations on the technology for obtaining Portland cement clinkers and cements based on the raw materials of Karakalpakstan. The study of the chemical and mineralogical composition of the raw materials of Karakalpakstan with the aim of their application to obtain high-quality clinkers and cements based on them. For raw mixes, which include limestone from the Dzhamansay-2 deposit, the clay component of the Berkuttau site, an iron-containing cinder from Almalyk mining-and-metallurgical integrated works, and gypsum stone from the Northern Dzhamansay deposit, the optimal firing temperature is 1450 ° C, which corresponds to the classical temperature index Portland cement clinker production. Raw mixtures based on the tested raw materials are highly reactive. When firing two-component feed mixtures using limestone of the Dzhamansay-2 deposit and basalt rock of the Berkuttau section, the optimum clinker sintering interval is 1400-1420 ° C;. Physical and mechanical tests have established that, on the basis of the tested raw materials (limestone of the Dzhamansay-2 deposit, the clay component of the Northern Dzhamansay deposit, the basaltic rock of the Berkuttau site and iron-containing additives), clinkers can be produced for general construction and sulfate-resistant cement grades of at least “400”, according to technological indicators fully meeting the requirements of State standard 10178; State standard 30515 and State standard 222 66.
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