CNN-LSTM based deep learning application on Jetson Nano: Estimating electrical energy consumption for future smart homes
Yazarlar (3)
Dr. Öğr. Üyesi Abdulkadir GÖZÜOĞLU Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Okan Özgönenel
Ondokuz Mayıs Üniversitesi, Türkiye
Ondokuz Mayıs Üniversitesi, Türkiye
Cenk Gezegin Ondokuz Mayıs Üniversitesi, Türkiye
| Makale Türü | Diğer (Teknik, not, yorum, vaka takdimi, editöre mektup, özet, kitap krıtiği, araştırma notu, bilirkişi raporu ve benzeri) (SCI, SSCI, AHCI, SCI-Exp dergilerinde yayınlanan teknik not, editöre mektup, tartışma, vaka takdimi ve özet türünden makale) | ||
| Dergi Adı | INTERNET OF THINGS (Q1) | ||
| Dergi ISSN | 2543-1536 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 03-2024 |
| Kabul Tarihi | 12-04-2026 | Yayınlanma Tarihi | 01-07-2024 |
| Cilt / Sayı / Sayfa | 26 / 1 / 17–0 | DOI | 10.1016/j.iot.2024.101148 |
| Makale Linki | https://doi.org/10.1016/j.iot.2024.101148 | ||
| Özet |
| Smart home applications have witnessed significant advancements, expanding beyond lighting control or remote monitoring to more sophisticated functionalities. Our study delves into pioneering an advanced energy management system tailored for forthcoming smart homes and grids. This system harnesses deep learning methodologies to predict consumer energy consumption. Leveraging a Wireless Fidelity (Wi-Fi) connection, we established an Internet of Things (IoT) network supported by Message Queuing Telemetry Transport (MQTT) for efficient data transfer. Our approach integrated the Jetson Nano Developer Kit for deep learning tasks, utilized Raspberry Pi as a home management server (HMS), and employed Espressif Systems' microcontrollers (ESP-01, NodeMCU, ESP32) to impart intelligence to household devices. Actual house measurements were collected and rigorously analyzed, demonstrating … |
| Anahtar Kelimeler |
| Cnn-lstm method | Deep learning | Demand-side management | Energy consumption estimation | Esp-01 | Esp32 | Future smart grids | Future smart homes | Home automation | home management server | Nodemcu | Wi-Fi |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 62 |
| Web of Science | 31 |