The use of agricultural harvesting robots has progressively emerged as a new trend in intelligent agriculture as a result of advancements in agricultural production methods and vision technology. Automatic detection and identification of crops through machine vision technology has become one of the key technologies of harvesting robot design, which determines the effectiveness of the robots' harvesting and the economic viability of farms. The automatic picking robot using a single chip computer is currently the most popular picking robot on the market. The identification approach based on a large number of picture data training through the formation of neural networks, however, has become an essential requirement for the development of a new generation of intelligent agriculture due to the rapid development of artificial intelligence.

In recent years, with the development of the field of automatic control, the technology of camera lenses and visual recognition algorithms have become increasingly perfect. Based on this foundation, unmanned aerial vehicle (UAV) visual tracking technology has become a hot research field. What is UAV visual tracking technology? Firstly, the UAV collects video through a camera, stores the collected information, and identifies the set tracking target through algorithms to perform preset tasks. At present, UAV visual tracking technology has been widely used in fields such as agricultural production, military research, logistics and transportation.

Fire-fighting equipment is the main facility to ensure fire safety in large industrial and civil buildings, as well as those in densely populated areas, and it is indispensable in building safety design. To ensure the fire safety of buildings, a large number of firefighting systems are installed, including automatic fire alarm systems, automatic sprinkler systems, smoke exhaust systems, electrical fire monitoring systems, gas fire extinguishing systems, emergency lighting systems and so on.

In response to the need for efficient and long-term stable measurement in the water quality monitoring industry, a water quality monitoring system is required. This system should have online automatic analyzers as its core, utilizing modern sensing technology, automatic measurement technology, automatic control technology, computer application technology, and related specialized analysis software and communication networks to form a comprehensive online automatic monitoring system. It can detect abnormal changes in water quality early, make rapid warnings to prevent downstream water pollution, and achieve a combination of automatic observation, remote control, and wireless transmission. It can track pollution sources in a timely manner, thereby serving management decisions.

The natural gas alarm system is mainly designed for detecting the concentration of natural gas (i.e. methane), displaying the concentration, and providing audible and visual alerts when the concentration exceeds the safe levels. It can be linked to the gas solenoid valve to promptly cut off the gas supply in case of a leak. The natural gas detection system realizes the automation of gas network leakage detection, offering real-time monitoring and higher reliability compared to manual inspections. It enhances early warning capabilities of the city’s gas pipeline network, reducing the harm caused by gas leaks. Natural gas detection system are commonly used in places such as gas stations, hotel kitchens, and school dining halls, and other areas where natural gas is present. They can also interface with solenoid valves and exhaust fans through signal outputs to help enterprises minimize safety risks.

The self-service ticketing solution based on MYIR’s MYC-YT507H System-On-Module (SOM) and MEasy HMI 2.0 system integrates functions such as ticketing terminals, background management, data analysis, and report output through the Internet. It can realize the functions of online booking and offline ticket pickup, inquiry and printing, allows for real-time monitoring of ticketing sales, and use collected data for analysis.

With the rapid development of digital economy, the industrial Internet of Things (IoT) has achieved leapfrog development in recent years. Smart industrial technologies have been widely applied in the field of intelligent production. By applying sensing, communication, transmission, data processing, and control technologies to all stages of production, including batching and warehousing, the digitalization, intelligence and networking of production and control processes are realized. This enhances manufacturing efficiency, improves product quality, reduces product costs and resource consumption, thereby realizing industrial intelligence.