Blood glucose monitoring is a valuable tool for managing diabetes. In recent years, with the increase of diabetics in the world, continuous glucose monitoring (CGM) of blood sugar changes has attracted more and more researchers' attention. Among the current technologies for measuring glucose, optical and electrochemical glucose sensors are the mainstream. Here, we introduce the history of optical, electrochemical, and other sensors such as field effect transistor sensors and their advantages and disadvantages, respectively. This review summarizes the research progress and main challenges of continuous glucose monitoring technology. We found that different optical techniques have different limitations which restricts the development of optical CGM. In contrast, electrochemical glucose sensors are more feasible and reliable in implementing CGM. Therefore, this review focuses on the development and shortcomings of electrochemical sensors, especially the promising direct electron transfer and the current commercial CGM. Hopefully, it will help readers sort out the future of CGM's development.

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The booming personalized and customized demands of customers in Industry 4.0 pose great challenges for manufacturing enterprises in terms of flexibility and responsiveness. Nowadays, many effective dynamic scheduling approaches have been proposed for manufacturing systems to quickly respond to changes in customer demands, where, however, the implementation of an automatic programming method with high control accuracy and low control delay is still challenging. The above unaddressed issue brings about a lot of labor-intensive and time-consuming manual offline programming work when adjusting the scheduling scheme to meet dynamic customer demands, resulting in limited flexibility and responsiveness in current manufacturing systems. To bridge this gap, a bi-level adaptive control architecture enabled by an automatic programming method is proposed and embedded into a digital twin manufacturing cell (DTMC). The bi-level architecture aims to automatically map an input task scheduling scheme with a batch of jobs into a group of control programs through a behavior model network and a set of event models embedded in DTMC. It also provides an adaptive program modification mechanism to quickly adapt to the dynamic adjustment of the scheduling scheme caused by the changing of customer demands or production conditions, thus equipping DTMC with strong flexibility and responsiveness. Based on the bi-level architecture, a DTMC prototype system is developed, where its application and evaluation results demonstrate the feasibility and effectiveness of the proposed approach.

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