SMART-SIP AI: Tumbler Cerdas Berbasis Kecerdasan Buatan untuk Deteksi Real-Time Kandungan Gula dan Kalori Minuman Sebagai Strategi Pencegahan Penyakit Metabolik
Keywords:
SMART-SIP AI, Near-Infrared Spectroscopy (NIRS), penyakit metabolikAbstract
Peningkatan konsumsi sugar-sweetened beverages (SSB) berkontribusi terhadap meningkatnya prevalensi penyakit metabolik, seperti diabetes melitus tipe 2 dan obesitas, serta memperburukpencemaran lingkungan akibat penggunaan kemasan plastik sekalipakai. Keterbatasan informasi kandungan gula pada minuman nonkemasan juga menyulitkan masyarakat dalam mengontrol asupan gula harian. Penelitian ini bertujuan mengembangkan konsep SMART-SIP AI, yaitu tumbler cerdas berbasis kecerdasan buatan yang mampu mengestimasi kandungan gula dan kalori minuman secara real-time sebagai upaya promotif dan preventif terhadap penyakit metabolik. Penelitian menggunakan pendekatan studi konseptual melalui perancangan arsitektur sistem yang mengintegrasikan sensor Near-Infrared Spectroscopy (NIRS), sensor warna RGB, mikrokontroler ESP32 berbasis edge artificial intelligence, dan aplikasi mobile. Sistem memanfaatkan metode Short-Wave Near-Infrared Spectroscopy (SW-NIR) yang dipadukan dengan algoritma Machine Learning untuk menganalisis kandungan gula secara non-destruktif dan mentransmisikan hasil melalui Bluetooth Low Energy (BLE). Validasi teknis dirancang menggunakan High Performance Liquid Chromatography (HPLC) sebagai standar emas. SMART-SIP AI diharapkan dapat meningkatkan literasi gizi digital, mendorong perilaku konsumsi yang lebih sehat, mengendalikan asupan gula, serta mengurangi penggunaan plastik sekali pakai guna mendukung pencegahan penyakit metabolik dan keberlanjutan lingkungan.
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