Dashboard Monitoring Sistem Greenhouse Melon Berbasis IoT Menggunakan ESP32, MQTT, dan Firebase: Studi Kasus Rejo Farm Integrated Farming

Daffa Maulana Putra, Ardhi Wicaksono Santoso., S.Kom., M.Cs.

2026 | Tugas Akhir | D4 TEKNOLOGI JARINGAN

Pengelolaan kondisi lingkungan greenhouse secara manual memiliki keterbatasan dalam hal efisiensi, akurasi, dan kecepatan respons. Penelitian ini merancang dan mengimplementasikan sistem dashboard monitoring greenhouse berbasis Internet of Things (IoT) yang mengintegrasikan mikrokontroler ESP32, sensor lingkungan, basis data cloud Firebase Firestore, serta dashboard berbasis Next.js sebagai antarmuka pemantauan secara real-time. Parameter yang dipantau meliputi suhu udara, kelembapan udara, kelembapan tanah, dan status hujan menggunakan sensor DHT22, soil moisture sensor, dan rain sensor. Data hasil pembacaan sensor dikirimkan dari ESP32 ke Firebase Firestore melalui endpoint API berbasis Next.js menggunakan protokol HTTP POST. Sistem dilengkapi automation engine berbasis Node.js yang berjalan pada Virtual Private Server (VPS) dan berkomunikasi dengan ESP32 melalui protokol MQTT menggunakan broker Mosquitto, sehingga memungkinkan kendali aktuator secara otomatis berdasarkan threshold maupun secara manual melalui dashboard. Selain itu, sistem menyediakan fitur Decision Support System (DSS), visualisasi grafik historis, dan ekspor laporan dalam format PDF. Hasil pengujian menunjukkan latensi pembaruan data sensor rata-rata sebesar 0,391 detik, latensi kendali aktuator secara manual sebesar 0,003 detik, dan latensi otomasi sebesar 0,142 detik. Tingkat keberhasilan pengiriman data sensor dari ESP32 ke Firebase Firestore melalui endpoint API berbasis Next.js mencapai 100%, sedangkan fungsionalitas threshold otomasi juga mencapai 100%.

Manual greenhouse environmental management has limitations in terms of efficiency, accuracy, and response time. This research designs and implements an Internet of Things (IoT)-based greenhouse monitoring dashboard that integrates an ESP32 microcontroller, environmental sensors, Firebase Firestore cloud database, and a Next.js-based dashboard as a real-time monitoring interface. The monitored parameters include air temperature, air humidity, soil moisture, and rainfall status using DHT22, soil moisture, and rain sensors. Sensor data are transmitted from the ESP32 to Firebase Firestore through a Next.js-based API endpoint using the HTTP POST protocol. The system is equipped with a Node.js-based automation engine running on a Virtual Private Server (VPS) and communicating with the ESP32 through the MQTT protocol using the Mosquitto broker, enabling both threshold-based automatic control and manual actuator control via the dashboard. In addition, the system provides a Decision Support System (DSS), historical data visualization, and PDF report generation. Experimental results show an average sensor data update latency of 0.391 seconds, a manual actuator control latency of 0.003 seconds, and an automation latency of 0.142 seconds. The success rate of sensor data transmission from the ESP32 to Firebase Firestore through the Next.js-based API endpoint reached 100%, while the functionality of the threshold-based automation also achieved 100%.

Kata Kunci : Internet of Things, greenhouse, monitoring, ESP32, Firebase Firestore, Next.js, MQTT