Ryan Franki Risdianto
Universitas wisnuwardhana

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Implementation of An IoT-Based Temperature and Humidity Monitoring System with Data Logging Features in the Calibration Laboratory Ryan Franki Risdianto; Jendra Sesoca; Bayu Firmanto
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 5 No. 3 (2026): September 2026 In progress.
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v5i3.532

Abstract

ISO/IEC 17025:2017 accredited calibration laboratory, holds an absolute obligation to monitor, control, and record environmental conditions (temperature and humidity) to maintain the validity of measurement results and support budget uncertainty calculations. However, the current monitoring system is still conventional and manual (three times a day), making it vulnerable to human errors, data duplication, and an inability to record fluctuations between intervals. This study aims to design and build an automatic temperature and humidity monitoring system based on the Internet of Things (IoT) featuring a dual-logging system to ensure continuous technical records. The system design utilizes an ESP32 microcontroller as the central processing unit, a DHT11 sensor to detect ambient temperature and relative humidity, a Micro SD Card module as a local backup media (offline backup), and the ThingSpeak platform as a cloud database for remote monitoring. The sensor data is saved to the SD Card in CSV format every 5 minutes, while data transmission to ThingSpeak is scheduled every 1 minute. System testing involved functionality tests (Black Box Testing), local storage capability tests, connectivity tests, data validity tests, and stability/durability tests. The results indicate that the IoT-based monitoring device was successfully functionality test success rate. The implementation of the dual-logging feature effectively preserves the integrity and continuity of records; ThingSpeak simplifies realtime data visualization, while the Micro SD Card operates as a reliable local failsafe during network fluctuations. This system minimizes human error, increases operational oversight efficiency, and supports regulatory compliance with Clauses 6.3 and 7.5 of ISO/IEC 17025:2017.