Global precipitation is becoming increasingly intense due to the extreme climate. Therefore, creating new technology to manage water resources is crucial. To create a sustainable urban and ecological environment, a water level and water quality control system implementing artificial intelligence is presented in this research. The proposed smart monitoring system consists of four sensors (two different liquid level sensors, a turbidity and pH sensor, and a water oxygen sensor), a control module (an MCU, a motor, a pump, and a drain), and a power and communication system (a solar panel, a battery, and a wireless communication module). The system focuses on low-cost Internet of Things (IoT) devices along with low power consumption and high precision. This proposal collects rainfall from the preceding 10 years in the application region as well as the region’s meteorological bureau’s weekly weather report and uses artificial intelligence to compute the appropriate water level. More importantly, the adoption of dynamic adjustment systems can reserve and modify water resources in the application region more efficiently. Compared to existing technologies, the measurement approach utilized in this study not only achieves cost savings exceeding 60% but also enhances water level measurement accuracy by over 15% through the successful implementation of water level calibration decisions utilizing multiple distinct sensors. Of greater significance, the dynamic adjustment systems proposed in this research offer the potential for conserving water resources by more than 15% in an effective manner. As a result, the adoption of this technology may efficiently reserve and distribute water resources for smart cities as well as reduce substantial losses caused by anomalous water resources, such as floods, droughts, and ecological concerns.

With the rapid development of e-commerce in China and the global pandemic of COVID-19, more and more sales personnel and brands have abandoned the physical retail industry and started investing in e-commerce. The consumer culture of livestream e-commerce is becoming popular in China. However, a report from Southern Finance Omnimedia Corp of China pointed out that among China's top 1,000 livestream sellers, the top 20 sellers have contributed to nearly half of the gross merchandise volume (GMV), using three major Chinese streaming platforms: Taobao, Douyin, and Kuaishou. Moreover, a novice in livestream e-commerce knows less about the important impact factors of the realm. Akin to the adage, “well aware is well prepared,” knowing more about the influencing factors of livestream e-commerce more will be the chances to promote the commercial value. A benchmark research is needed to systematically trace out the most important and influencing factors and to make possible the rising of selling with less effort, hence this study. The research intends to sort out the relevant influencing factors that affect consumers’ shopping motivation in livestream e-commerce by reviewing previous related literature. Then, through the Delphi method, eight experts constructed the 14 main influencing factors that affect consumers’ shopping motivation in livestream e-commerce. Through DEMATEL-ANP, we can not only find the key factors but also sort out the causal relationship between the main key factors, forming a preliminary evaluation model of the commercial value of livestream sellers. The importance-performance analysis (IPA) of these impact factors found that “seller popularity” is the most critical factor affecting consumers’ shopping motivation. At the same time, product discounts, product quality, and the attractiveness of the sellers are being included in effects by the “seller popularity.” The investigation followed in this study revealed that characteristics of the livestream seller are one of the most influencing factor achieving a total weight of 0.3020, whereas the streaming platform is the least influencing factor (total weight is 0.1333). The assessment made the study explore the sustainability of livestream e-commerce in China, and the proposed evaluation model can be used for the preliminary business value evaluation of people engaged in livestream sellers and related industries.