Development of an Automated Temperature Calibration Monitoring System Using Internet of Things for the Regional Meteorology, Climatology, and Geophysics Agency (Bmkg) in Medan

The Regional Meteorology, Climatology, and Geophysics Agency (BMKG) plays a crucial role in providing accurate and reliable services related to meteorology, climatology, and geophysics. Temperature observation is one of the important tasks carried out by the BMKG as it is essential for weather and climate forecasting, as well as for predicting natural disasters. To ensure the accuracy of the data, the thermometers used for temperature observation must be in good working condition and calibrated regularly. According to the Republic of Indonesia Law No. 31, Article 48, Year 2009 on Meteorology, Climatology, and Geophysics (MKG), all observation equipment must be in good working condition and calibrated regularly. Calibration is a crucial step in ensuring the accuracy and operational fitness of the observation equipment. The International Organization for Standardization (ISO) / International Electrotechnical Commission (IEC) 17025:2017 also emphasizes the importance of ensuring the quality and accuracy of all measurement instruments. The Calibration Laboratory at the BMKG Regional Office I in Medan is accredited with ISO/IEC 17025:2017 by the National Accreditation Committee (KAN). However, the calibration process can be time-consuming and requires constant monitoring to achieve stable data. During temperature and humidity calibration, the calibration laboratory's environment must be conditioned to maintain the performance of sensitive instruments that are susceptible to environmental changes. This study aims to design an automated temperature calibration monitoring system using the Internet of Things (IoT) to improve the efficiency of the calibration process and achieve maximum calibration results at the BMKG Regional Office I in Medan. The system will enable the calibration personnel to monitor the calibration process remotely and receive real-time data, allowing for more effective analysis and decision-making.