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Remarkable number of healthcare data produced on day to day basis. Cloud computing has seen exponential growth over a short period of time in various sectors. Cloud computing is advantageous in providing economical services to its customers, for data storage, data collection, efficient data analysis of large patient's population. A survey of three hundred twenty hospitals in Indian, of rural and urban areas has shown the interest of hospitals for adopting cloud technology. In order to deal with the brisk improvement in IT and usage of cloud based services, numerous attempts should be applied to change healthcare data from traditional paper based towards the electronic form. To regulate and control the usage of healthcare data many regional legislation and policies should be enacted. [ABSTRACT FROM AUTHOR]

The aim of the paper is to bring new knowledge from ongoing specific university research. As part of this project, optical data collect locally and historically significant states of the chapel in Horní Nivy were collected using aerial and ground digital photogrammetry. The obtained data are subsequently analyzed for the needs of creating a virtual model. Data are generated from individual photographs as a point cloud. With regard to the parameters of the object, the data are captured partly from the ground using a camera and partly from the air using a camera mounted on a drone. By combining the exterior and interior model and removing unwanted points (noise), a model - a digital twin building - ai develop. The created model serves as a basis for the processing of construction technical and construction historical research. [ABSTRACT FROM AUTHOR]

The aim of the paper is to bring new knowledge from ongoing specific university research. As part of this project, optical data collect locally and historically significant states of the chapel in Horní Nivy were collected using aerial and ground digital photogrammetry. The obtained data are subsequently analyzed for the needs of creating a virtual model. Data are generated from individual photographs as a point cloud. With regard to the parameters of the object, the data are captured partly from the ground using a camera and partly from the air using a camera mounted on a drone. By combining the exterior and interior model and removing unwanted points (noise), a model - a digital twin building - ai develop. The created model serves as a basis for the processing of construction technical and construction historical research. [ABSTRACT FROM AUTHOR]

Automated Data Collection (ADC) challenges the traditional methods of raw data collection (RDC). As we progress towards Industry 4.0, the amount of data is increasing at a rapid pace. Various IoT devices and other such applications are responsible for the production of the huge amount of data that becomes part of the Big Data that is happening in real-time. As our dependency on data is increasing, so is the need to have a more sophisticated approach towards collecting, cleaning, and processing the data. This paper focuses on data collection, which is literally the first step towards any data analysis process. We will discuss how automated data collection in Industry 4.0 impacts the work balance of the users, who are primarily students and employees, in contrast to the conventional methods of collecting data. ADC uses Artificial Intelligence (AI) to identify, extract and store relevant data in the system. As the technique becomes more sophisticated, much better, accurate, and reliable outcomes are expected. We will see how automating the data collection process has an impact on user experience and productivity. Then we will try to identify the correlation between them. In the end, we will analyze all the factors that affect the users who deal with raw data on a daily basis and understand the impact generated by implementing ADC. [ABSTRACT FROM AUTHOR]