Author: Xolmanov, Rustam Uktam o’g’li
Annotation: This article is devoted to the study of the impact and application of semiconductor-based sensors in various fields such as medicine, automotive, and environmental monitoring. Semiconductor sensors are known for their high accuracy, sensitivity and reliability, and these sensors play an important role in decision-making processes in various fields by providing accurate and fast information. In the field of medicine, these sensors continuously monitor patients' vital signs, improve treatment efficiency, and provide doctors with real-time information. These sensors measure important parameters such as heart rate, blood pressure, body temperature, and provide doctors with the opportunity to constantly monitor the condition of patients. This, in turn, helps to apply quick and effective treatment measures. In the automotive industry, semiconductor sensors increase the safety and performance of vehicles. For example, it plays a major role in ensuring road safety and improving fuel efficiency. They provide drivers with information about surrounding objects, measure distances and avoid potential collisions. It is also used to optimize the performance of the car's internal systems, which reduces fuel consumption and emissions. In environmental monitoring, these sensors are crucial in detecting pollutants and providing information necessary for environmental protection. These sensors detect pollutants in the air, water quality and soil composition. This information is the main source of information in the development of environmental protection strategies and plays an important role in predicting natural disasters in advance.
Keywords: Semiconductor Sensors, Medical Sensors, Automotive Sensors, Environmental Monitoring, Sensor Technology, Sensor Accuracy, Sensitivity, Reliability, Medical Diagnostics, Automotive Safety, Pollutants, Fuel Efficiency, Environmental Monitoring, Technological Advances, R&D , innovation, sensor integration, real-time monitoring, natural disaster prediction, energy efficiency
Pages in journal: 930 - 937
