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Potato Leaf Disease Detection by Means of Vision Transformer and CoAtNet Architecture 5

Potato Leaf Disease Detection by Means of Vision Transformer...

引用

5th IEEE International Conference on Technology, Informatics, Management, engineering and Environment, TIME-E 2024

作者： Kenan Sergio, Mesa Anugerah Stevano Siallagan, Ariel Brandon Joelianto, Endra Institut Teknologi Bandung Engineering Physics Study Program Bandung Indonesia Institut Teknologi Bandung Instrumentation Control and Automation Research Group Bandung Indonesia

ISBN: (纸本)9798350364743

Potatoes are a food source that is beneficial for humans in various aspects, such as having nutritional and economic value. However, potato plants are susceptible to many diseases. To address this issue, various researchers have suggested methods utilizing machine learning and image processing for automatic disease type detection. This paper introduces a disease detection model for potato leaf images, employing two computer vision techniques: Vision Transformer (ViT) and CoAtNet. The dataset used in this paper consisted of 30,760 augmented images divided into seven classes. The ViT model had a test accuracy of 99.32% and a validation accuracy of99.12%. Meanwhile, the CoAtNEt model had a test accuracy of 99.58 % and a validation accuracy of 99.48 %. These results show that both models can be used in the detection of potato leaf diseases. © 2024 IEEE.

关键词： CoAtNet image processing leaf disease potato vision transformer

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Optimizing Indoor Vertical Farming with DDPG Reinforcement Learning: Enhancing Control of Nutrient Levels, Climate Conditions, and Plant Health 5

Optimizing Indoor Vertical Farming with DDPG Reinforcement L...

引用

5th IEEE International Conference on Technology, Informatics, Management, engineering and Environment, TIME-E 2024

作者： Albert Panggabean, Good Fried Romadhon, Rahmat Lubis, Ramot Joelianto, Endra Institut Teknologi Bandung Doctoral Program in Engineering Physics Bandung Indonesia Institut Teknologi Del Faculty of Informatics and Electrical Engineering Toba Indonesia Institut Teknologi Bandung Engineering Physics Study Program Bandung Indonesia Institut Teknologi Bandung Instrumentation Control and Automation Research Group Bandung Indonesia

ISBN: (纸本)9798350364743

In indoor vertical farming systems, managing dynamic and complex environments poses significant challenges. Traditional control strategies often fall short in adapting to rapid changes in critical parameters such as nutrient levels, climate conditions, and plant health indicators. To address these challenges, this paper presents a novel approach for optimizing indoor vertical farming using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm well-suited for environments with continuous action spaces. Our study focused on the control and monitoring of key parameters, including nutrient levels (pH and EC), climate conditions (temperature, humidity, light, and CO2 levels), and plant health indicators (biomass accumulation and leaf size structure). By defining a comprehensive state and action space, we simulated an indoor farming environment and trained the DDPG model to maximize crop yield and health. © 2024 IEEE.

关键词： DDPG indoor vertical farming precision agriculture reinforcement learning smart farming

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Human Following Robot Based on Object Detection for Aerospace Application 1

Human Following Robot Based on Object Detection for Aerospac...

引用

1st International Conference of Adisutjipto on Aerospace Electrical engineering and Informatics, ICAAEEI 2024

作者： Sumari, Arwin Datumava Wahvudi Aryandika, Ahnaf Bagus Purnami, Ndaru Atmi Dermawan, Denny Syamsiana, Ika Noer State Polytechnic of Malang Cognitive Artificial Intelligence Research Group Department of Electrical Engineering Malang Indonesia Adisutjipto Institute of Aerospace Technology Electrical Engineering Study Program Yogyakarta Indonesia Adisutjipto Institute of Aerospace Technology Aerospace Navigation Instrumentation Control Automation and Robotics System Research Group Electrical Engineering Study Program Yogyakarta Indonesia Adisutjipto Institute of Aerospace Technology Electrical Engineering Study Program Aerosp. Digit. Syst. Microprocessor Microcontroller and Programmable Logic Devices Research Group Yogyakarta Indonesia

ISBN: (纸本)9798331507930

In this research, the Human Following Robot (HFR) prototype has been designed and implemented using YOLO v3-Tiny and Tensor Flow Lite on Raspberry Pi hardware named Rewang. The HFR Rewang is designed to assist aircraft technicians by bringing maintenance tool kits to aircraft shelters. Rewang's movement is based on a camera as a vision sensor following the movement of human entities. Image input is processed by YOLO v3-Tiny through the determination of the bounding box, the calculation of Euclidean Distance, and the determination of the pixel value of the camera as the basis of Rewang's movement which is regulated by an L298N driver motor that controls two Direct Current (DC) motors for the left and right wheels. The test results show that Rewang can move at an average speed of 0.18 m/s at 2 m with a travel time of 11 seconds with a light intensity of more than 250 lux. The minimum and maximum distance of object detection is as far as 120 cm and 400 cm, with an object detection accuracy of 95.8%. Rewang allows the HFR to have a larger carrying capacity to bring more complete aircraft maintenance tools and is prospective for other aerospace and general applications. © 2024 IEEE.

关键词： Travel time

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Computational fluid dynamics analysis of the natural circulation system in vertical heater horizontal cooler (VHHC) molten salt loop 9

Computational fluid dynamics analysis of the natural circula...

引用

9th Asian Physics Symposium 2021, APS 2021

作者： Hariyanto, Duwi Waris, Abdul Suprijadi Nuclear Physics and Biophysics Research Division Physics Department Institut Teknologi Bandung Indonesia Nuclear Science and Engineering Department Institut Teknologi Bandung Indonesia Theoretical High Energy Physics and Instrumentation Research Division Physics Department Institut Teknologi Bandung Indonesia Instrumentation and Automation Engineering Study Program Production and Industrial Technology Department Institut Teknologi Sumatera Indonesia

Molten salt has attracted the attention of researchers, especially as a coolant because of its characteristics. This study aimed to analyse the transient and steady-state of the natural circulation system in the molten salt loop with vertical heater and horizontal cooler using computational fluid dynamics. The computational fluid dynamics module in the COMSOL Multiphysics software was used to solve governing equations. Experimental data from several references were used as input data in modelling. The loop was modelled as a rectangular loop with Inconel 625 as the pipe material and molten salt (NaNO3+KNO3) as the working fluid. The variation of heater power was also carried out in modelling. The modelling results showed a good agreement with the experimental results. The results provided that the molten salt natural circulation loop with vertical heater and horizontal cooler showed good flow stability without reversal of flow direction. © Published under licence by IOP Publishing Ltd.

关键词： Computational fluid dynamics

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Potato Leaf Disease Detection by Means of Vision Transformer and CoAtNet Architecture

Potato Leaf Disease Detection by Means of Vision Transformer...

引用

International Conference on Technology, Informatics, Management, engineering, and Environment (TIME-E)

作者： Mesa Anugerah Kenan Sergio Ariel Brandon Stevano Siallagan Endra Joelianto Engineering Physics Study Program Institut Teknologi Bandung Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798350364750

ISBN: (纸本)9798350364767

关键词： Productivity Computer vision Accuracy Computational modeling Image processing Machine learning Transformers Informatics Monitoring Diseases

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Optimizing Indoor Vertical Farming with DDPG Reinforcement Learning: Enhancing Control of Nutrient Levels, Climate Conditions, and Plant Health

Optimizing Indoor Vertical Farming with DDPG Reinforcement L...

引用

International Conference on Technology, Informatics, Management, engineering, and Environment (TIME-E)

作者： Albert Good Fried Panggabean Rahmat Romadhon Ramot Lubis Endra Joelianto Doctoral Program in Engineering Physics Institut Teknologi Bandung Bandung Indonesia Faculty of Informatics and Electrical Engineering Institut Teknologi Del Toba Indonesia Engineering Physics Study Program Institut Teknologi Bandung Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798350364750

ISBN: (纸本)9798350364767

关键词： Smart agriculture Precision agriculture Reinforcement learning Humidity Aerospace electronics Nutrients Temperature control Informatics Monitoring Farming

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Human Following Robot Based on Object Detection for Aerospace Application

Human Following Robot Based on Object Detection for Aerospac...

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Aerospace Electrical engineering and Informatics (ICAAEEI), International Conference of Adisutjipto on

作者： Arwin Datumava Wahvudi Sumari Ahnaf Bagus Aryandika Ndaru Atmi Purnami Denny Dermawan Ika Noer Syamsiana Department of Electrical Engineering Cognitive Artificial Intelligence Research Group State Polytechnic of Malang Malang Indonesia Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Aerospace Navigation Instrumentation Control Automation and Robotics System Research Group Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia Aerospace Digital System Microprocessor Microcontroller and Programmable Logic Devices Research Group Electrical Engineering Study Program Adisutjipto Institute of Aerospace Technology Yogyakarta Indonesia

ISBN: (数字)9798331507930

ISBN: (纸本)9798331507947

关键词： YOLO Tensors Accuracy Prototypes Wheels Cameras Hardware Maintenance Aircraft Aerospace industry

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