Dissolved oxygen is an important index to evaluate water quality, and its concentration is of great significance in industrial production, environmental monitoring, aquaculture, food production, and other fields. As its change is a continuous dynamic process, the dissolved oxygen concentration needs to be accurately measured in real time. In this paper, the principles, main applications, advantages, and disadvantages of iodometric titration, electrochemical detection, and optical detection, which are commonly used dissolved oxygen detection methods, are systematically analyzed and summarized. The detection mechanisms and materials of electrochemical and optical detection methods are examined and reviewed. Because external environmental factors readily cause interferences in dissolved oxygen detection, the traditional detection methods cannot adequately meet the accuracy, real-time, stability, and other measurement requirements; thus, it is urgent to use intelligent methods to make up for these deficiencies. This paper studies the application of intelligent technology in intelligent signal transfer processing, digital signal processing, and the real-time dynamic adaptive compensation and correction of dissolved oxygen sensors. The combined application of optical detection technology, new fluorescence-sensitive materials, and intelligent technology is the focus of future research on dissolved oxygen sensors.

Dissolved oxygen (DO) is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

This paper discusses the project which is one of the Beijing City College Students’ Scientific Research and Entrepreneurial Action Plan Project named "unmanned area fetching trolley", The project used infrared sensor to measure the distance between the car and the obstacle, The MCU would analyze and process this signal, and generate two different PWM signals respectively to drive motors when the distance is less than a certain value, so as to realize avoiding obstacle automatically. After Hall sensor detected the PWM wave corresponding to the actual speed of the car, the PID module would compare the PWM wave of the actual speed and the PWM wave which is generated by MCU, so as to determine whether the output is desired and achieve closed-loop control, thus can make the control of speed is more precise. The mechanical arm is composed of five steering, the upper monitor control it through the wireless module, each instruction can make the rotation angle of each actuator accurate to 1 degree, so the mechanical arm is flexible and precise. The project ultimately achieved the desired effect that avoid obstacle automatically, upper monitor control accurately. After expansion and improving, it can be used for automatic weeding, automatic cleaning, automatic patrol, automatic sowing, automatic harvesting and so on.