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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics
Anugrayani Bustamin
Hasanuddin University
Computer Science & IT Electrical & Electronics Engineering Engineering

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A real-time data association of internet of things based for expert weather station system Indrabayu Indrabayu; Intan Sari Areni; Anugrayani Bustamin; Rizka Irianty
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp432-439

Abstract

The wind carries moisture into an atmosphere and hot or cold air into a climate, affecting weather patterns. Knowing where the wind is coming from gives essential insight into what kind of temperatures are to be expected. However, the wind is affected by spatial and temporal variabilities, thus making it difficult to predict. This study focuses on finding data associations from the weather station installed at Hasanuddin University Campus based on internet of things (IoT) using Raspberry Pi as a gateway that associated all the meteorological data from sensors. The generation of association rules compares the Apriori and FP-growth algorithms to determine relations among itemsets. The results show that high humidity and warm temperature tend to associate with a westerly wind and occur at night. In contrast, conditions with less humid and moderate temperatures tend to have southerly and southeasterly wind.
Blob adaptation through frames analysis for dynamic fire detection Indrabayu Indrabayu; Rahmat Hardian Putra; Ingrid Nurtanio; Intan Sari Areni; Anugrayani Bustamin
Bulletin of Electrical Engineering and Informatics Vol 9, No 5: October 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (642.639 KB) | DOI: 10.11591/eei.v9i5.2622

Abstract

This study was aiming at helping visually impaired people to detect and estimate the fire distance. Blind people had difficulty knowing the existence of fire at a safe distance; hence the possibility of burning could occur. The color models and blob analysis methods were used to detect the presence of fire in the blind path. Before the fire detection stage, the cascade of the HSV and RGB color models was applied to segment the reddish fire color. The size and shape of a dynamic fire were the parameters used in this paper to distinguish fire from non-fire objects. Changes in the area of the fire object obtained at the Blob analysis stage per 10 frames were the main contributions and novelty in this paper. After the fire is detected, the calculation of the fire distance to a blind person was completed using a pinhole model. This research used 35 data videos with a resolution of 480x640 pixels. The results showed that the fire detection system and the distance estimation achieved an accuracy of 88.86% and the MSE of 0.0358, respectively.
Co-Authors Indrabayu Indrabayu Ingrid Nurtanio Intan Sari Areni Rahmat Hardian Putra Rizka Irianty