![]() ![]() ![]() Measuring the consumption of electronic devices is a difficult and sensitive task. © 2017, Brazilian Institute for Information in Science and Technology. We conclude that this method contributes to leverage advanced analytics in industries and to increase the potential of new studies on top of industrial sensors data. As a result, we present MINDSense, a method that creates an ontology capable of describing the meaning of industrial sensors and its relationships. This study intends to answer the following research question: Which approach could automate the creation of a semantic middleware for industrial sensors? In order to address the objectives of this study, we performed an empirical research using sensor metadata from three different plants from a mining company. Since there are naming conventions and some other rules defined by engineers, this study takes these standards into account and analyze the metadata of sensors intending to automate the creation of a semantic middleware able to indicate the meaning of each sensor and its relationships with other sensors, equipments, areas, plants and other entities. However, this condition limits the usage of advanced analytics tools in industries, preventing the capture of potential benefits. Hence, the problem is frequently set aside by industries. Conventional approaches to create a semantic layer for industrial sensors require a rigid “term alignment” followed by a lot of manual efforts. However, the meaning and the relationships of each specific sensor is unknown to people outside the engineering context. Recently, data scientists are using these data to make predictions on industrial processes. From the results of the tests that have been carried out the data acquisition system can work well where the torque and power data of each motorcycle are obtained using the absorption and inertia test methods.įor many years, plant engineers have used data collected from industrial sensors for supporting the diagnosis of failures. The results of the data acquisition system design will be tested on five four-stroke motorcycles with different specifications. The results of the calibration of the rpm roller sensor obtained an average relative error of 1.92%, while the engine rpm obtained a relative error of 0.46% on average, and an average relative error of 0.13% for loadcell. The sensor used to measure the required quantities is calibrated first using an appropriate calibration tool. ![]() The data acquisition system created includes data on torque, power, engine rpm, roller rpm, fuel consumption, air temperature entering the combustion chamber, exhaust temperature, ambient temperature and relative humidity. The research objectives used were to design and create a data acquisition system from an eddy current dynamometer using an AVR based on ESP32 and create a software interface to show test results data in real-time using Intellij Idea with the Kotlin programming language. Retrieval of data from the processes of working on a machine or the use of a data acquisition system can simplify the data collection process so that the data can be used directly. Data acquisition system is a form of technology in the field of instrumentation with data collection and processing of a certain amount to be measured. One of the widely used scientific models is a data acquisition system. Technology has become an inseparable part of this modern era. With the rapid development of technology, there are many impacts on the pattern of human life. ![]() With the development of technology and science in the field of semiconductors and programming, all fields are digitized and automated. ![]()
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