BibTex Citation Data :
@article{GT90338, author = {Hanifan Arya Genio and Arkhan Subari}, title = {Perancangan Alat Deteksi Kematangan Buah Alpukat Mentega Berbasis ESP32 Menggunakan Sensor TCS3200 dan Sensor MQ135 Dengan Monitoring Google Spreadsheet}, journal = {Gema Teknologi}, volume = {23}, number = {1}, year = {2024}, keywords = {Butter Avocado, ESP32, TCS3200, MQ135, Rule-Based System, Google Spreadsheet}, abstract = { Manually determining the ripeness of butter avocados based on skin color and aroma tends to be subjective, so a more objective measurement system is needed. This study designed an ESP32-based butter avocado ripeness detection device by integrating a TCS3200 color sensor and an MQ135 gas sensor. The TCS3200 was used to obtain red and green color parameters, while the MQ135 was used to detect changes in gases or volatile compounds around the fruit. Data from both sensors were processed using a rule-based system with threshold values derived from testing 50 fruit samples grouped into unripe, semi-ripe, ripe, and rotten categories. The test results showed that red and green values tended to decrease from the unripe to the rotten stages, while MQ135 values increased from 83–88 PPM in unripe fruit to 103–113 PPM in rotten fruit. The system successfully displayed the classification results on an LCD screen and automatically sent the readings to a Google Spreadsheet via Wi-Fi. These results demonstrate that the integration of color sensors, gas sensors, the ESP32, and cloud-based monitoring can be applied to support the automatic detection of butter avocado ripeness. }, issn = {2656-582X}, pages = {36--40} doi = {10.14710/gt.v23i1.90338}, url = {https://ejournal.undip.ac.id/index.php/gema_teknologi/article/view/90338} }
Refworks Citation Data :
Manually determining the ripeness of butter avocados based on skin color and aroma tends to be subjective, so a more objective measurement system is needed. This study designed an ESP32-based butter avocado ripeness detection device by integrating a TCS3200 color sensor and an MQ135 gas sensor. The TCS3200 was used to obtain red and green color parameters, while the MQ135 was used to detect changes in gases or volatile compounds around the fruit. Data from both sensors were processed using a rule-based system with threshold values derived from testing 50 fruit samples grouped into unripe, semi-ripe, ripe, and rotten categories. The test results showed that red and green values tended to decrease from the unripe to the rotten stages, while MQ135 values increased from 83–88 PPM in unripe fruit to 103–113 PPM in rotten fruit. The system successfully displayed the classification results on an LCD screen and automatically sent the readings to a Google Spreadsheet via Wi-Fi. These results demonstrate that the integration of color sensors, gas sensors, the ESP32, and cloud-based monitoring can be applied to support the automatic detection of butter avocado ripeness.
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