Fadhilah, Anisah Farah (2024) Perancangan dan Implementasi Sistem Smart Home Berbasis IoT dengan Edge Computing. Other thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 5027201023-Undergraduate_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5027201023-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2026. Download (8MB) | Request a copy |
Abstract
Dalam era di mana internet menjadi bagian penting dari komunikasi sehari-hari, teknologi rumah pintar memungkinkan kita untuk membuat tempat tinggal yang interaktif dan terhubung. Internet of Things (IoT) merupakan jaringan perangkat fisik yang dilengkapi dengan sensor, perangkat lunak, dan teknologi lainnya untuk tujuan menghubungkan dan bertukar data dengan perangkat dan sistem lain melalui internet. Adanya edge computing pada sistem smart home memiliki sejumlah keunggulan, seperti kemudahan, kenyamanan, fleksibilitas, dan skalabilitas. Sistem ini menggunakan Raspberry Pi sebagai edge gateway, ESP32 sebagai IoT nodes, Firebase sebagai cloud database, dan Node-RED sebagai platform manajemen data. Tujuan utama penelitian adalah memahami cara merancang dan mengimplementasikan komponen-komponen tersebut untuk mengelola perangkat IoT dengan baik. Hasil penelitian menunjukkan bahwa sistem berhasil dirancang dan diimplementasikan dengan menggunakan Raspberry Pi 4 Model B, Node-RED, dan Firebase Realtime Database. Sistem manajemen perangkat IoT yang diimplementasikan menggunakan Node-RED dan Python berfungsi dengan baik, dengan tingkat keberhasilan rata-rata 100% dan waktu eksekusi rata-rata 2,149 detik. Namun, fungsionalitas pembaruan status MQTT hanya mencapai keberhasilan berkisar 60-70% dan waktu eksekusi antara 6-10 detik. Akurasi perangkat pengontrol AC untuk pengukuran suhu ±0.79°C, kelembapan ±11.2% RH, tegangan baterai ±0.012V, dan persentase baterai ±13%. Akurasi perangkat pemantau daya listrik sebesar ±0.08V, ±0.074A, dan ±1.58W.
======================================================================================================================================
In an era where the internet is becoming an essential part of everyday communication, smart home technology allows us to create interactive and connected living spaces. The Internet of Things (IoT) is a network of physical devices equipped with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems via the internet. The existence of edge computing in a smart home system has a number of advantages, such as ease, convenience, flexibility, and scalability. This system uses Raspberry Pi as the edge gateway, ESP32 as the IoT nodes, Firebase as the cloud database, and Node-RED as the data management platform. The main objective of the research is to understand how to design and implement these components to properly manage IoT devices. The results showed that the system was successfully designed and implemented using Raspberry Pi 4 Model B, Node-RED, and Firebase Realtime Database. The IoT device management system implemented using Node-RED and Python works well, with an average success rate of 100% and an average execution time of 2.149 seconds. However, the MQTT status update functionality only achieved success rates ranging from 60-70% and execution times between 6-10 seconds. The accuracy of the AC controller device for temperature measurement is ±0.79°C, humidity is ±11.2% RH, battery voltage is ±0.012V, and battery percentage is ±13%. The accuracy of the electric power monitoring device is ±0.08V, ±0.074A, and ±1.58W.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Edge Computing, ESP32, Internet of Things, Raspberry Pi, Smart Home |
| Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T57.5 Data Processing T Technology > T Technology (General) > T58.5 Information technology. IT--Auditing T Technology > T Technology (General) > T58.6 Management information systems T Technology > T Technology (General) > T58.8 Productivity. Efficiency |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information Technology > 59201-(S1) Undergraduate Thesis |
| Depositing User: | Anisah Farah Fadhilah |
| Date Deposited: | 19 Jul 2024 07:10 |
| Last Modified: | 19 Jul 2024 07:10 |
| URI: | http://repository.its.ac.id/id/eprint/108510 |
Actions (login required)
 |
View Item |