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In the project of total station network monitoring, the accuracy of the control network determines the monitoring accuracy. To address the issue of poor accuracy in the control network of total station network monitoring, an in-depth study was conducted on the assembly structure and measurement principles of the double-sided prism used for transmitting control coordinates. An effective solution by calibrating the constants was proposed on the left and right sides of the double-sided prism to ensure the uniqueness of the center of the double-sided prism, thereby reducing coordinate transmission errors and improving the overall accuracy of the monitoring control network. Furthermore, due to the poor manufacturing precision of the double-sided prism, theoretical research on the angle and distance errors of the double-sided prism in total station measurements was conducted. A method that utilizes the total station to perform on-site calibration and calibration of the measurement constants of the double-sided prism was presented. This method has advantages including low requirements for external measurement environments, simple operation, and significantly improvement of the accuracy of the on-site calibrated constants. The method was validated in a certain subway monitoring project, resulting in an improvement of approximately 1 mm in the accuracy of the total station network monitoring, which demonstrates its high practical value. [ABSTRACT FROM AUTHOR]

A portable environmental sensor for agricultural applications is proposed that addresses key challenges in power supply, data transmission, and monitoring efficiency. The sensor features a photovoltaic power supply and a PID-based dynamic active–sleep scheme for sustainable energy management, maintaining optimal battery levels under varying solar conditions. Its compact, waterproof, and dustproof design (90 mm × 90 mm × 150 mm, 844 g) ensures robust and reliable operation in diverse agricultural environments. High-precision digital sensors monitor temperature, humidity, light intensity, and CO2 concentration. Equipped with low-power NB-IoT technology, the sensor supports real-time remote environmental monitoring. Our experimental results show effective continuous operation, accurate environmental measurements, and performance comparable to established data loggers. The advanced power management and precise sensing capabilities make this sensor a competitive solution for improving smart agriculture practices, particularly in resource-limited or off-grid settings. [ABSTRACT FROM AUTHOR]