Rancang Bangun Alat Pengering Bahan Makanan Berbasis Wings Drying System Dengan Dua Sumber Panas

Puswadi, Hendri Aldi; Sunyoto, Sunyoto

doi:10.26877/jitek.v7i1/mei.8298

Cited by 2 publications

(3 citation statements)

References 0 publications

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“…(2) d=ΔpixeldΔpixely×y,y=y22=1.6 m2≈1.13 m,where d is social distance estimation (meters), Δpixeld is the number of pixels between two humans that are d apart (pixels), Δpixely is the number of pixels that represent the human height from the UAV camera (pixels), and y = human height projection (meters). The height of humans captured by the UAV camera is set at 1.6 m, representing the average height of adults in Indonesia 44 , 45 . However, this value can be adjusted to accommodate different standard heights across the world.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…The height of humans captured by the UAV camera is set at 1.6 m, representing the average height of adults in Indonesia. 44,45 However, this value can be adjusted to accommodate different standard heights across the world. Thus, the human height captured by the camera will be approximated as high as 1.13 m to the projection of the camera angle on the UAV by 45 deg [as shown in Eq.…”

Section: Ratio Of Social Distance To Human Heightmentioning

confidence: 99%

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Convolutional neural network-based crowd detection for COVID-19 social distancing protocol from unmanned aerial vehicles onboard camera

Wastupranata,

Munir

2023

J. Appl. Rem. Sens.

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.Social distancing is a feasible solution to break the chain of the spread of coronavirus disease 2019 (COVID-19). A human crowd detection model was trained with a computational load that can be handled by a companion computer on the unmanned aerial vehicle (UAV) to minimize the spread of COVID-19. The model is designed to be able to measure social distance between people, whether it exceeds predetermined safe limits (1.5 m). The convolutional neural network model was trained using a dataset of 9600 images featuring humans, cyclists, and motorcyclists, with an allocation of 200 images each for testing and hyperparameter tuning. The image dataset was extracted from videos recorded above the UAV in the Institut Teknologi Bandung area, capturing diverse crowd scenarios throughout the day. The pre-trained model for transfer learning method is a single shot detector with MobileNet, ResNet50, and ResNet101 architectures. The measurement of the estimated social distance uses the Euclidian distance with the average Indonesian human as a reference, which is 1.6 m. MobileNet V2 was chosen as a crowd detection model with a lightweight size, which is only 19 MB and the average detection runtime for a single image is only 0.606s, in accordance with the load for the onboard companion computer. MobileNet V2 is also able to detect crowds of people well with the precision value reaching 84.9% and the recall value reaching 87.8%.

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Section: Proposed Methodsmentioning

confidence: 99%

Section: Ratio Of Social Distance To Human Heightmentioning

confidence: 99%

Convolutional neural network-based crowd detection for COVID-19 social distancing protocol from unmanned aerial vehicles onboard camera

Wastupranata,

Munir

2023

J. Appl. Rem. Sens.

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show abstract

“…Proses pengeringan juga dapat dilakukan dengan mengalirkan udara panas pada bahan di dalam ruangan tertutup (close drying) yang kita kenal dengan istilah mesin/alat pengering [3][4][5][6][7][8]. Salah satu metode pengeringan sistem tertutup yang banyak digunakan untuk mengeringkan produk pertanian adalah sistem dehumidifikasi, dimana proses tersebut Sudirman dkk /Jurnal Rekayasa Mesin p-ISSN: 1411-6863, e-ISSN: 2540-7678…”

Section: Pendahuluanunclassified

Aplikasi Cooling Dehumidification pada Mesin Pengering untuk Mengeringkan Hasil Panen Tanaman Herbal

Sudirman¹,

Baliarta²,

Sudana³

et al. 2023

j.rekayasa.mesin.

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<p>Pengeringan merupakan alternatif yang cocok untuk pengelolaan pasca panen, terutama di negara seperti Indonesia yang fasilitas distribusi dan penanganan pasca panennya kurang baik. Produk pertanian berupa tanaman herbal memerlukan penanganan pasca panen khusus, agar produk dapat disimpan dalam waktu yang lama tanpa mengurangi aroma. Salah satu produk pertanian tanaman herbal adalah jahe. Dalam proses pengolahan pasca panen, untuk mendapatkan jahe kering, dibutuhkan teknik pengeringan dengan temperatur yang rendah agar tekstur dari produk akhir yang dihasilkan tidak banyak berubah. Tujuan dari penelitian ini adalah mengaplikasikan sistem dehumidifikasi pada mesin pengering jahe untuk mendapatkan temperatur pengeringan jahe yang sesuai namun efisien. Metode yang digunakan di dalam penelitian ini adalah metode eksperimental, dimana temperatur pengeringan dikontrol pada suhu 40°C dengan waktu pengeringan selama 7 jam. Hasilnya, jahe segar yang dikeringkan dengan pengering sistem dehumidifikasi menghasilkan penurunan berat rata-rata 80,66% dengan kandungan kadar air rata-rata sebesar 9,2%.</p>

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Rancang Bangun Alat Pengering Bahan Makanan Berbasis Wings Drying System Dengan Dua Sumber Panas

Cited by 2 publications

References 0 publications

Convolutional neural network-based crowd detection for COVID-19 social distancing protocol from unmanned aerial vehicles onboard camera

Convolutional neural network-based crowd detection for COVID-19 social distancing protocol from unmanned aerial vehicles onboard camera

Aplikasi Cooling Dehumidification pada Mesin Pengering untuk Mengeringkan Hasil Panen Tanaman Herbal

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