Implementasi Fog Computing Pada Aplikasi Smart Home Berbasis Internet of Things

Zainudin, Ahmad; Anisah, Ida; Gulo, Melki Mario

doi:10.24114/cess.v6i1.20658

Cited by 6 publications

(5 citation statements)

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“…Oleh karena itu dapat membagi tugas pemrosesan data dan penyaluran data memanfaatkan fog computing. Adanya purwarupa perangkat teknologi ini dapat mengurangi ketergantungan dengan pemanfaatan cloud [7].…”

Section: Pendahuluanunclassified

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Purwarupa Perangkat Pelindung Jemuran pada Rumah Pintar Berbasis IoT Memanfaatkan MQTT dan Fog Computing

Widianto

Albert

Karteja

2022

JuLIET

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– The industrial revolution has changed the world a lot, one of which is the internet of things (IoT) role. This technology needs the role of protocols for communication and etc. Most studies use message queue telemetry transport (MQTT) because it is lightweight and easy to apply. MQTT has been widely used in smart homes, farms, and smart cities. But in practice, MQTT also requires the internet to work. One suggestion that can be used with fog computing is when there is a sensor error, or the internet is unstable. Many studies on IoT use MQTT as a protocol, but its use is still rarely combined with fog computing. This study aims to make a prototype of a clothesline protection device using the MQTT and fog computing protocols. The test results using BlackBox show that all devices have worked well. The MQTT communication protocol is very light for communication and then assisted by fog computing which can perform remotely correctly when a sensor error occurs. Fog computing can also help when the internet connection is not good. The weakness of this research is a delay in the movement of the DC motor. This happens because of low-cost devices and interference from signals or objects around it. Another weakness is that there is no validation of environmental results such as humidity and temperature.Keywords: fog computing, internet of things (IoT), message queue telemetry transport (MQTT)Intisari – Revolusi industri telah banyak mengubah dunia, salah satunya peran dari internet of things (IoT). Teknologi ini perlu peran serta protokol untuk komunikasi dll. Kebanyakan penelitian menggunakan message queue telemetry transport (MQTT) karena sifatnya yang ringan dan mudah diaplikasikan. Pemanfaatan MQTT sudah banyak digunakan seperti pada rumah pintar, pertanian pintar dan kota pintar. Tetapi pada penerapannya MQTT juga membutuhkan internet untuk bekerja, salah satu saran yang dapat digunakan dengan fog computing ketika terdapat kesalahan pada sensor atau internet tidak stabil. Terdapat banyak penelitian mengenai IoT yang memanfaatkan MQTT sebagai protokolnya, tetapi pemanfaatannya masih jarang menggabungkan keduanya dengan fog computing. Pada penelitian ini bertujuan untuk membuat purwarupa perangkat pelindung jemuran dengan memanfaatkan protokol MQTT dan fog computing. Hasil pengujian dengan memanfaatkan BlackBox menunjukkan jika semua perangkat telah bekerja dengan baik. Pada protokol komunikasi MQTT terbukti sangat ringan untuk komunikasi lalu dibantu dengan fog computing yang dapat melakukan remote dengan tepat ketika terjadi kesalahan pada sensor. Fog computing pun dapat membantu ketika koneksi internet yang kurang baik. Kelemahan penelitian ini adalah terjadi delay pada pergerakan motor DC, hal ini terjadi karena penggunaan perangkat berbiaya rendah, dan terjadi interferensi dari sinyal atau benda di sekitarnya. Kelemahan lainnya adalah belum adanya validasi hasil lingkungan seperti kelembaban dan suhu.Kata kunci: fog computing, internet of things (IoT), message queue telemetry transport (MQTT)

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Section: Pendahuluanunclassified

“…Pada [7], di tahun 2021. Penelitian mengembangkan sebuah perangkat yang berbasis pada fog computing yang digunakan pada IoT yang diaplikasikan di rumah pintar.…”

Section: B Ulasan Literasiunclassified

Purwarupa Perangkat Pelindung Jemuran pada Rumah Pintar Berbasis IoT Memanfaatkan MQTT dan Fog Computing

Widianto

Albert

Karteja

2022

JuLIET

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“…These small units work together to handle data pre-processing, short-term storage, and rule-based real-time monitoring. Fog computing architecture reduces the amount of data transported through the system and improves overall efficiency [11]. An overview of the fog computing architecture is shown in Fig.…”

Section: Fog Computingmentioning

confidence: 99%

Distributed News Crawler Using Fog Cloud Approach

Prismana¹

2022

Proceedings of the International Joint Conference on Science and Engineering 2022 (IJCSE 2022)

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Technology advanced quickly during the Industrial Revolution. 4.0, makes the internet network also develop rapidly and become larger. So website technology that is constantly changing becomes a big challenge in using large and complex data information on the global Internet. Stand-alone web crawlers have traditionally been difficult to overcome the challenges of rapid information growth, therefore it's challenging to extract a lot of data in a short period. The research will use distributed technology to build a more effective web-distributed news system, to search for news. Crawler systems can work efficiently with Multi-Threads working together, and each node can work efficiently with Multithreading. This study applies a new web crawler fog cloud approach that is considered to be more efficient in navigating URLs by setting according to the domain used and dividing URL limitations into various priority URL queues so that URLs can be dispersed across concurrent crawler operations to get rid of the new building. In particular, the proposed model can effectively utilize resources optimally in the cloud-fog layer by deploying a crawler distribution in the cloud-fog infrastructure to detect news. With the fog cloud, analysis is dynamically distributed across the fog and cloud layers enabling real-time distribution. The research phase of the distributed news crawler starts from URL collection, URL filtering, scheduling, accessing URLs, and extracting news data. This research is focused on developing web crawlers to process distributed news crawlers..

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“…The measured water quality parameters included temperature, pH, and DO levels. Concerning the implementation of fog computing, a study by (Zainudin et al, 2021) attempted to apply fog computing in a smarthome application. Based on their research, the computation process time for monitoring temperature and humidity reached 0.152 seconds, adjusting the brightness of the lamp took 0.339 seconds, and face recognition computation took 6.602 seconds.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Multi-Node QoS in Shrimp Pond Monitoring System with Fog Computing

Anisah,

Munadi,

Away

et al. 2024

SinkrOn

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Most of Indonesia’s territory consists of oceans, presenting a significant potential for developing the fisheries sector. Shrimp is among Indonesia’s flagship commodities with substantial export potential. Internationally, Indonesia holds the fourth position as the largest exporter of frozen shrimp globally. However, shrimp cultivation faces various challenges, including declining water quality due to factors such as water sources and weather, which can adversely affect harvest yields. To preempt potential failures, employing smart devices and technology in shrimp cultivation offers an effective and efficient solution for monitoring and management. This study aims to analyze water quality monitoring in ponds considering the speed of data transmission from end devices to fog using Quality of Service (QoS) parameters like delay/latency, throughput, and packet loss. Data transmission tests were conducted at data rates of 5 Mbps and 10 Mbps, with a bandwidth of 1500 Mbps. The study involves three sensors—water temperature, pH, and salinity—placed in shrimp ponds. Test results showed a decrease in throughput by 1.54% at the sensor node and 2.99% at the sink node when packet data delivery encountered barriers like obstacles. There was a 74.13% increase in latency when the delivery distance extended to 35 meters. The achievable delivery range with low latency was up to 10 meters with barriers and 25 meters without. Thus, latency and throughput values vary depending on the presence of barriers and transmission distance. Barriers tend to increase latency and decrease throughput.

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Implementasi Fog Computing Pada Aplikasi Smart Home Berbasis Internet of Things

Cited by 6 publications

References 0 publications

Purwarupa Perangkat Pelindung Jemuran pada Rumah Pintar Berbasis IoT Memanfaatkan MQTT dan Fog Computing

Purwarupa Perangkat Pelindung Jemuran pada Rumah Pintar Berbasis IoT Memanfaatkan MQTT dan Fog Computing

Distributed News Crawler Using Fog Cloud Approach

Analysis of Multi-Node QoS in Shrimp Pond Monitoring System with Fog Computing

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