As the growth rate of the internet-of-things (IoT) sensor market is expected to exceed 30%, a technology that can easily collect and processing a large number of various types of sensor data is gradually required. However, conventional multilink IoT sensor communication based on Bluetooth low energy (BLE) enables only the processing of up to 19 peripheral nodes per central device. This study suggested an alternative to increasing the number of IoT sensor nodes while minimizing the addition of a central processor by expanding the number of peripheral nodes that can be processed per central device through a new group-switching algorithm based on Bluetooth low energy (BLE). Furthermore, this involves verifying the relevancy of application to the industry field. This device environment lowered the possibility of data errors and equipment troubles due to communication interference between central processors, which is a critical advantage when applying it to industry. The scalability and various benefits of a group-switching algorithm are expected to help accelerate various services via the application of BLE 5 wireless communication by innovatively improving the constraint of accessing up to 19 nodes per central device in the conventional multilink IoT sensor communication.

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When introducing a robotic process automation (RPA) solution for business automation, selecting an RPA solution that is suitable for the automation target and goals is extremely difficult for customers. One reason for this difficulty is that standardised evaluation items and indicators that can support the evaluation of RPA have not been defined. The broad extension of RPA is still in its infancy and only a few studies have been conducted on this subject. In this study, an evaluation breakdown structure for RPA selection was developed by deriving evaluation items from prior studies related to RPA selection and a feasibility study was conducted. Consequently, a questionnaire was administered three times, and the coefficients of variation, content validity, consensus, and convergence of factors and criteria were measured from the survey results. All of these measurement results are reflected in the final suitability value that was calculated to verify the stability of the evaluation system and evaluation criteria indicators. This study is the first to develop an RPA solution selection evaluation standard and the proposed evaluation breakdown structure provides useful evaluation criteria and a checklist for successful RPA application and introduction.

Inhalation and exhaust fans are installed inside a distribution panel for cooling. However, in the event of fire inside the panel, these fans change the flow of smoke, which interferes with quick detection by fire sensors installed on the panel ceiling, thereby increasing fire damage. The purpose of this study is to develop a smoke detector that can be installed inside distribution panels and to propose an optimal smoke detector position based on the influence of the position on detection performance. To this end, an experimental distribution panel was fabricated and four smoke detector samples were installed near the fans. The smoke detection performance experiment was repeated on ignition source positions corresponding to widths of 15, 30, 45, and 50 cm, a depth of 55 cm, and heights of 0, 30, and 60 cm. The results indicated that the smoke detection performance and CO absorption concentration were higher when the smoke detector was positioned closer to the left or right side of the exhaust fan. In particular, compared with current designs in which smoke detectors are installed on distribution panel ceilings, the elapsed time until smoke detection decreased by 75%, whereas the CO absorption concentration increased by more than 100%. This study presents a theoretical ground for the installation of built-in smoke detectors near exhaust fans for closed power industry equipment that includes airflow-changing devices. Additionally, this study raises awareness on the importance of fire sensors and the need to improve policies and standards for fire prevention.

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