The COVID-19 pandemic has exposed vulnerabilities within our healthcare structures. Healthcare facilities are often faced with staff shortages and work overloads, which can have an impact on the collection of health d...The COVID-19 pandemic has exposed vulnerabilities within our healthcare structures. Healthcare facilities are often faced with staff shortages and work overloads, which can have an impact on the collection of health data and constants essential for early diagnosis. In order to minimize the risk of error and optimize data collection, we have developed a robot incorporating artificial intelligence. This robot has been designed to automate and collect health data and constants in a contactless way, while at the same time verifying the conditions for correct measurements, such as the absence of hats and shoes. Furthermore, this health information needs to be transmitted to services for processing. Thus, this article addresses the aspect of reception and collection of health data and constants through various modules: for taking height, temperature and weight, as well as the module for entering patient identification data. The article also deals with orientation, presenting a module for selecting the patient’s destination department. This data is then routed via a wireless network and an application integrated into the doctors’ tablets. This application will enable efficient queue management by classifying patients according to their order of arrival. The system’s infrastructure is easily deployable, taking advantage of the healthcare facility’s local wireless network, and includes encryption mechanisms to reinforce the security of data circulating over the network. In short, this innovative system will offer an autonomous, contactless method for collecting vital constants such as size, mass, and temperature. What’s more, it will facilitate the flow of data, including identification information, across a network, simplifying the implementation of this solution within healthcare facilities.展开更多
A new method is proposed for the object surveillance system based on the enhanced fish-eye lens and the high speed digital signal processor （DSP）. The improved fish-eye lens images an ellipse picture on the charge-c...A new method is proposed for the object surveillance system based on the enhanced fish-eye lens and the high speed digital signal processor （DSP）. The improved fish-eye lens images an ellipse picture on the charge-coupled device （CCD） surface, which increases both the utilization rate of the 4：3 rectangular CCD and the imaging resolution, and remains the view angle of 183° The algorithm of auto-adapted renewal background subtraction （ARBS） is also explored to extract the object from the monitoring image. The experimental result shows that the ARBS algorithm has high anti-jamming ability and high resolution, leading to excellent object detecting ability from the enhanced elliptical fish-eye image under varies environments. This system has potential applications in different security monitoring fields due to its wide monitoring space, simple structure, working stability, and reliability.展开更多
文摘The COVID-19 pandemic has exposed vulnerabilities within our healthcare structures. Healthcare facilities are often faced with staff shortages and work overloads, which can have an impact on the collection of health data and constants essential for early diagnosis. In order to minimize the risk of error and optimize data collection, we have developed a robot incorporating artificial intelligence. This robot has been designed to automate and collect health data and constants in a contactless way, while at the same time verifying the conditions for correct measurements, such as the absence of hats and shoes. Furthermore, this health information needs to be transmitted to services for processing. Thus, this article addresses the aspect of reception and collection of health data and constants through various modules: for taking height, temperature and weight, as well as the module for entering patient identification data. The article also deals with orientation, presenting a module for selecting the patient’s destination department. This data is then routed via a wireless network and an application integrated into the doctors’ tablets. This application will enable efficient queue management by classifying patients according to their order of arrival. The system’s infrastructure is easily deployable, taking advantage of the healthcare facility’s local wireless network, and includes encryption mechanisms to reinforce the security of data circulating over the network. In short, this innovative system will offer an autonomous, contactless method for collecting vital constants such as size, mass, and temperature. What’s more, it will facilitate the flow of data, including identification information, across a network, simplifying the implementation of this solution within healthcare facilities.
文摘A new method is proposed for the object surveillance system based on the enhanced fish-eye lens and the high speed digital signal processor （DSP）. The improved fish-eye lens images an ellipse picture on the charge-coupled device （CCD） surface, which increases both the utilization rate of the 4：3 rectangular CCD and the imaging resolution, and remains the view angle of 183° The algorithm of auto-adapted renewal background subtraction （ARBS） is also explored to extract the object from the monitoring image. The experimental result shows that the ARBS algorithm has high anti-jamming ability and high resolution, leading to excellent object detecting ability from the enhanced elliptical fish-eye image under varies environments. This system has potential applications in different security monitoring fields due to its wide monitoring space, simple structure, working stability, and reliability.
