Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532573
Aldi Ramdani, S. Suyanto
Strawberry is a plant with high economic value and promising business prospects. A common problem in strawberry cultivation is that the seeds quickly get a disease. Some diseases like spot leaf, blight leaf, and scorch leaf can be detected from the leaf. Identifying strawberry diseases from its leaf can prevent damage to the fruit. We proposed a CNN Model to identifying strawberry diseases from its leaf. CNN is one of deep learning approaches that has been used in many previous studies to identifying fruit diseases. There are four different strawberry leaf types, healthy, scorch leaf, spot leaf, and leaf blight, in the proposed technique. Using ResNet-50 architecture for the model with 3600 images, the model achieves a prediction accuracy of 100% for spot leaf, 99% for blight leaf, 99% for scorch leaf, 100% for a healthy leaf. The proposed model provides a simple, reliable technique for identifying strawberry diseases.
{"title":"Strawberry Diseases Identification From Its Leaf Images Using Convolutional Neural Network","authors":"Aldi Ramdani, S. Suyanto","doi":"10.1109/IAICT52856.2021.9532573","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532573","url":null,"abstract":"Strawberry is a plant with high economic value and promising business prospects. A common problem in strawberry cultivation is that the seeds quickly get a disease. Some diseases like spot leaf, blight leaf, and scorch leaf can be detected from the leaf. Identifying strawberry diseases from its leaf can prevent damage to the fruit. We proposed a CNN Model to identifying strawberry diseases from its leaf. CNN is one of deep learning approaches that has been used in many previous studies to identifying fruit diseases. There are four different strawberry leaf types, healthy, scorch leaf, spot leaf, and leaf blight, in the proposed technique. Using ResNet-50 architecture for the model with 3600 images, the model achieves a prediction accuracy of 100% for spot leaf, 99% for blight leaf, 99% for scorch leaf, 100% for a healthy leaf. The proposed model provides a simple, reliable technique for identifying strawberry diseases.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125199797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532534
Muchammad Dicky Sanjaya, C. Setianingsih, R. E. Saputra
Global electricity consumption is increasing every year. Electricity has become a necessary need for every sector, from a household to government and industry. With today's technology, data also has become more important, including electricity data. The right tools and techniques can extract valuable information from data. Using a K-Means++ algorithm to cluster electricity data can help to determine when the usage is low, moderate, and high. In this study, there three scenarios of clustering; hourly, daily, and monthly. The silhouette score of this experiment ranges from 0.68 to 0.71, and the DB Index ranges from 0.30 to 0.51.
{"title":"Electricity Usage Clustering with K-means++ Algorithm","authors":"Muchammad Dicky Sanjaya, C. Setianingsih, R. E. Saputra","doi":"10.1109/IAICT52856.2021.9532534","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532534","url":null,"abstract":"Global electricity consumption is increasing every year. Electricity has become a necessary need for every sector, from a household to government and industry. With today's technology, data also has become more important, including electricity data. The right tools and techniques can extract valuable information from data. Using a K-Means++ algorithm to cluster electricity data can help to determine when the usage is low, moderate, and high. In this study, there three scenarios of clustering; hourly, daily, and monthly. The silhouette score of this experiment ranges from 0.68 to 0.71, and the DB Index ranges from 0.30 to 0.51.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126773843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532577
L. Kusdibyo, A. Brien, Rivan Sutrisno, D. Suhartanto
The objective of this paper is to ascertain the dimensions of virtual reality (VR) experience in tourism. Past studies on VR experience mainly focus on VR system and VR content with 29 indicators all together. They have not identified yet the underlying dimensions forming VR experience. Driven by this research gap, this study attempts to explore the dimensions of experience in VR tourism. A self-administered questionnaire was distributed online and 396 valid responses were generated from tourists who visited Australian tourism destinations through VR. An exploratory factor analysis was executed to produce new underlying dimensions of VR experience. Then, confirmatory factor analysis was performed to ensure the validity of the new dimensions. The result of the factor analysis shows that five new dimensions are formed, namely; enjoyment and learning, escape, involvement, application, and peace of mind. The result of the confirmatory factor analysis confirms the dimensionality of the VR experience construct. This study contributes to the literature on VR experience and its dimensions.
{"title":"Virtual Reality Experience in Tourism: A Factor Analysis Assessment","authors":"L. Kusdibyo, A. Brien, Rivan Sutrisno, D. Suhartanto","doi":"10.1109/IAICT52856.2021.9532577","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532577","url":null,"abstract":"The objective of this paper is to ascertain the dimensions of virtual reality (VR) experience in tourism. Past studies on VR experience mainly focus on VR system and VR content with 29 indicators all together. They have not identified yet the underlying dimensions forming VR experience. Driven by this research gap, this study attempts to explore the dimensions of experience in VR tourism. A self-administered questionnaire was distributed online and 396 valid responses were generated from tourists who visited Australian tourism destinations through VR. An exploratory factor analysis was executed to produce new underlying dimensions of VR experience. Then, confirmatory factor analysis was performed to ensure the validity of the new dimensions. The result of the factor analysis shows that five new dimensions are formed, namely; enjoyment and learning, escape, involvement, application, and peace of mind. The result of the confirmatory factor analysis confirms the dimensionality of the VR experience construct. This study contributes to the literature on VR experience and its dimensions.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115783734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532516
M. Sobirin, H. Hindersah
This paper describes a control method for the stable standing and walking of a bipedal robot based on Inertia Measurement Unit (IMU) sensor feedback. The IMU sensor was used to measure body's tilt posture of the robot on uneven terrain conditions. In this paper, indication of bipedal walking stability was determined based on the tilt posture of robot body. Fuzzy logic controller (FLC) was further designed to evaluate tilt posture of robot body to generate appropriate offset angles to be applied on the corresponding joints of the robot. The performances of the proposed methods were verified by walking experiments on a 18-DOFs biped robot, El-Pistolero. From the experimental results, it can be concluded that the proposed FLC is capable of maintaining the balance of the robot in standing and walking condition, but sometimes the sole was slipped so robot can not walk straight.
{"title":"Stability Control for Bipedal Robot in Standing and Walking using Fuzzy Logic Controller","authors":"M. Sobirin, H. Hindersah","doi":"10.1109/IAICT52856.2021.9532516","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532516","url":null,"abstract":"This paper describes a control method for the stable standing and walking of a bipedal robot based on Inertia Measurement Unit (IMU) sensor feedback. The IMU sensor was used to measure body's tilt posture of the robot on uneven terrain conditions. In this paper, indication of bipedal walking stability was determined based on the tilt posture of robot body. Fuzzy logic controller (FLC) was further designed to evaluate tilt posture of robot body to generate appropriate offset angles to be applied on the corresponding joints of the robot. The performances of the proposed methods were verified by walking experiments on a 18-DOFs biped robot, El-Pistolero. From the experimental results, it can be concluded that the proposed FLC is capable of maintaining the balance of the robot in standing and walking condition, but sometimes the sole was slipped so robot can not walk straight.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115910968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532559
Benjir Islam Alvee, Md. Tawfiq Chowdhury, Md. Golam Rabiul Alam
The goal of this work is to focus on choosing product for an enterprise using fuzzy TOPSIS model. The initial focused product here in this research is laptop brand. An appropriate laptop is a vital part in a technology based era currently, which is expected to have the ideal quality and services at a reasonable price, at the same time. It is a multi criteria decision-making problem involving several criterion on which decision makers' knowledge is collected. Thus, based on the decision makers' given weights and ratings of criterion and available alternatives respectively, final ranking of the alternatives are obtained using Fuzzy TOPSIS.
{"title":"Multi Criteria Decision Method based Enterprise Product Ranking using Fuzzy TOPSIS","authors":"Benjir Islam Alvee, Md. Tawfiq Chowdhury, Md. Golam Rabiul Alam","doi":"10.1109/IAICT52856.2021.9532559","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532559","url":null,"abstract":"The goal of this work is to focus on choosing product for an enterprise using fuzzy TOPSIS model. The initial focused product here in this research is laptop brand. An appropriate laptop is a vital part in a technology based era currently, which is expected to have the ideal quality and services at a reasonable price, at the same time. It is a multi criteria decision-making problem involving several criterion on which decision makers' knowledge is collected. Thus, based on the decision makers' given weights and ratings of criterion and available alternatives respectively, final ranking of the alternatives are obtained using Fuzzy TOPSIS.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131694557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532528
Jihen Souifi, Y. Bouslimani, M. Ghribi, A. Kaddouri
This paper focuses on designing and implementing an IoT device capable of air flow measurements. The transducer is based on a Positive Temperature Coefficient (PTC) Thermistor and intended to be used with ventilation systems. The PTC Temperature depends on the power level dissipated into the surrounding medium and the airflow velocity. A PCB design and realization are proposed for a device with LoRaWAN and Wi-Fi dual capabilities. In this device and in addition to the PTC, a negative temperature coefficient (NTC) sensor is also considered for temperature compensation. A database and IoT platform are used to collect and store the realtime data of the airflow measurements.
{"title":"LoRaWAN-WiFi device semiconductor technology-based for airflow measurements in HVAC systems","authors":"Jihen Souifi, Y. Bouslimani, M. Ghribi, A. Kaddouri","doi":"10.1109/IAICT52856.2021.9532528","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532528","url":null,"abstract":"This paper focuses on designing and implementing an IoT device capable of air flow measurements. The transducer is based on a Positive Temperature Coefficient (PTC) Thermistor and intended to be used with ventilation systems. The PTC Temperature depends on the power level dissipated into the surrounding medium and the airflow velocity. A PCB design and realization are proposed for a device with LoRaWAN and Wi-Fi dual capabilities. In this device and in addition to the PTC, a negative temperature coefficient (NTC) sensor is also considered for temperature compensation. A database and IoT platform are used to collect and store the realtime data of the airflow measurements.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125030963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532553
Hassan Vakani, S. Abdallah, I. Kamel, T. Rabie, Mohammed Baziyad
A common practice of many steganography schemes is to replace the high frequency insignificant Discrete Cosine Transform (DCT) coefficients with secret data. The replaced secret data, however, needs to be scaled appropriately before replacing the insignificant DCT coefficients. The secret is typically scaled down to closely match the replaced insignificant coefficients of the cover. State of the art techniques show that using multiple scales to adaptively scale the secret improves the stego quality without compromising the embedding capacity. Scaling can also potentially lead to degradation of the extracted image quality due to high scaling factors. Therefore, this paper proposes a novel DCT-in-DCT-Adaptive Scaling technique that achieves higher payload imperceptibility without compromise in the stego quality for a fixed embedding capacity. The proposed technique utilizes DCT transform to find the DCT magnitude of the secret before adaptively scaling the secret and replacing the scaled secret with high frequency insignificant DCT coefficients of the cover image. Results compared with Spatial-in-DCT-Adaptive Scaling show improvement of up to 20.25 dB in the extracted quality of the payload.
{"title":"DCT-in-DCT: A Novel Steganography Scheme for Enhanced Payload Extraction Quality","authors":"Hassan Vakani, S. Abdallah, I. Kamel, T. Rabie, Mohammed Baziyad","doi":"10.1109/IAICT52856.2021.9532553","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532553","url":null,"abstract":"A common practice of many steganography schemes is to replace the high frequency insignificant Discrete Cosine Transform (DCT) coefficients with secret data. The replaced secret data, however, needs to be scaled appropriately before replacing the insignificant DCT coefficients. The secret is typically scaled down to closely match the replaced insignificant coefficients of the cover. State of the art techniques show that using multiple scales to adaptively scale the secret improves the stego quality without compromising the embedding capacity. Scaling can also potentially lead to degradation of the extracted image quality due to high scaling factors. Therefore, this paper proposes a novel DCT-in-DCT-Adaptive Scaling technique that achieves higher payload imperceptibility without compromise in the stego quality for a fixed embedding capacity. The proposed technique utilizes DCT transform to find the DCT magnitude of the secret before adaptively scaling the secret and replacing the scaled secret with high frequency insignificant DCT coefficients of the cover image. Results compared with Spatial-in-DCT-Adaptive Scaling show improvement of up to 20.25 dB in the extracted quality of the payload.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128495498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532542
Clement Regis Tuyishime, Frederic Nzanywayingoma, O. Gatera
The internet of things (IoT) has been useful in different sectors and attracted more attention in researches. IoT technologies are mainly used to enable the physical objects to collect and exchange data by using wireless network protocols. Moreover, IoT technologies have been applied in different applications including energy control and monitoring. However, energy efficiency has been the main challenge in industries, when comparing the energy consumption, production and cost. Therefore, this research project develop an IoT-based Intelligent Energy Efficiency Management System to enhance energy efficiency in current industries and the Industry 4.0 by focusing on smart industries, where the results show that the data of humidity and temperature was monitored directly to the NODE-RED platform, and a notification to personal email to an operator. Thus, help an operator to act accordingly based on the change of the data prescribed on dashboard.
{"title":"IoT-based Intelligent Energy Efficiency Management System for Smart Industries (IoT-IEEMS)","authors":"Clement Regis Tuyishime, Frederic Nzanywayingoma, O. Gatera","doi":"10.1109/IAICT52856.2021.9532542","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532542","url":null,"abstract":"The internet of things (IoT) has been useful in different sectors and attracted more attention in researches. IoT technologies are mainly used to enable the physical objects to collect and exchange data by using wireless network protocols. Moreover, IoT technologies have been applied in different applications including energy control and monitoring. However, energy efficiency has been the main challenge in industries, when comparing the energy consumption, production and cost. Therefore, this research project develop an IoT-based Intelligent Energy Efficiency Management System to enhance energy efficiency in current industries and the Industry 4.0 by focusing on smart industries, where the results show that the data of humidity and temperature was monitored directly to the NODE-RED platform, and a notification to personal email to an operator. Thus, help an operator to act accordingly based on the change of the data prescribed on dashboard.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129835371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532574
Putri Rahmawati, M. I. Nashiruddin, M. Nugraha
The cellular technology development is evolving rapidly, along with its explosive increase in data traffic, leading to the development of the following technology, namely 5G. In order to predict the readiness of the 5G deployment in Indonesia, careful planning is needed. This research aims to deploy a 5G New Radio (NR) network in Indonesia with a frequency spectrum of 3.5 GHz due to its widely used globally, wherein this research selects an urban area, Bandung city, with an area of 167.31 km2 from the year 2021 to 2026. Bandung city is selected because it is one of the big cities implementing 5G based on the KOMINFO strategic plan. This research uses a planning approach based on capacity and coverage. The capacity planning approach determines the users' projection, demand traffic, and data rates for determining the number of gNodeB. While the coverage planning uses uplink and downlink scenarios from Outdoor to Outdoor (O2O) with Line of Sight (LOS) conditions based on the 3GPP 38.901 UMa (Urban Macro) propagation model. This research shows that the 5G NR network deployment in Bandung city based on capacity requires 130 gNodeB for uplink and 69 gNodeB for downlink. While for coverage, 61 gNodeB is needed for uplink and 97 gNodeB for downlink. Based on the results, the selected gNodeB number needed in Bandung city is 130 gNodeB. It also requires a traffic demand of 2.18 Gbps/km2, with a maximum data rate for the uplink of 1.875 Gbps and a downlink of 3.506 Gbps.
蜂窝技术的发展日新月异，伴随着数据流量的爆炸式增长，导致了以下技术的发展，即5G。为了预测印度尼西亚5G部署的准备情况，需要仔细规划。由于其在全球广泛使用，本研究旨在在印度尼西亚部署频谱为3.5 GHz的5G新无线电(NR)网络，其中本研究选择万隆市，从2021年到2026年，面积为167.31平方公里。万隆市之所以被选中，是因为它是根据KOMINFO战略计划实施5G的大城市之一。本研究采用了一种基于容量和覆盖的规划方法。容量规划方法确定了用于确定gndeb数量的用户预测、需求流量和数据速率。覆盖规划采用基于3GPP 38.901 UMa (Urban Macro)传播模型的基于LOS (Line of Sight)条件的O2O (Outdoor to Outdoor)上下行场景。研究表明，万隆市基于容量部署5G NR网络，上行需要130个gndeb，下行需要69个gndeb。而对于覆盖，上行需要61个gndeb，下行需要97个gndeb。根据计算结果，万隆市所需的gndeb数量为130 gndeb。其流量需求为2.18 Gbps/km2，上行最大数据速率为1.875 Gbps，下行最大数据速率为3.506 Gbps。
{"title":"Capacity and Coverage Analysis of 5G NR Mobile Network Deployment for Indonesia's Urban Market","authors":"Putri Rahmawati, M. I. Nashiruddin, M. Nugraha","doi":"10.1109/IAICT52856.2021.9532574","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532574","url":null,"abstract":"The cellular technology development is evolving rapidly, along with its explosive increase in data traffic, leading to the development of the following technology, namely 5G. In order to predict the readiness of the 5G deployment in Indonesia, careful planning is needed. This research aims to deploy a 5G New Radio (NR) network in Indonesia with a frequency spectrum of 3.5 GHz due to its widely used globally, wherein this research selects an urban area, Bandung city, with an area of 167.31 km2 from the year 2021 to 2026. Bandung city is selected because it is one of the big cities implementing 5G based on the KOMINFO strategic plan. This research uses a planning approach based on capacity and coverage. The capacity planning approach determines the users' projection, demand traffic, and data rates for determining the number of gNodeB. While the coverage planning uses uplink and downlink scenarios from Outdoor to Outdoor (O2O) with Line of Sight (LOS) conditions based on the 3GPP 38.901 UMa (Urban Macro) propagation model. This research shows that the 5G NR network deployment in Bandung city based on capacity requires 130 gNodeB for uplink and 69 gNodeB for downlink. While for coverage, 61 gNodeB is needed for uplink and 97 gNodeB for downlink. Based on the results, the selected gNodeB number needed in Bandung city is 130 gNodeB. It also requires a traffic demand of 2.18 Gbps/km2, with a maximum data rate for the uplink of 1.875 Gbps and a downlink of 3.506 Gbps.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129096829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-27DOI: 10.1109/IAICT52856.2021.9532575
Brenda, Budhi Irawan, C. Setianingsih
Pak Choy plant is a vegetable plant that can grow with soil and hydroponic media. Plant growth can be monitored by knowing the width of the plant's leaves. This research creates a tool to accurately detect plant leaf width through plant growth monitored by the people-research implementation in the form of a mobile application that can detect the width of plant leaves. Using the canny edge detection method, the results obtained system accuracy of 95.06%, the light intensity of 18.75 lux, angle of 90°, and distance of 30 cm. Pak Choy plant growth was seen for 4 weeks, the best accuracy was obtained at 2nd week with an average accuracy of 99% and an average light intensity value of 22 lux.
{"title":"Pak Choy Leaf Width Detection using Image Processing with Canny Edge Detection Extraction Method","authors":"Brenda, Budhi Irawan, C. Setianingsih","doi":"10.1109/IAICT52856.2021.9532575","DOIUrl":"https://doi.org/10.1109/IAICT52856.2021.9532575","url":null,"abstract":"Pak Choy plant is a vegetable plant that can grow with soil and hydroponic media. Plant growth can be monitored by knowing the width of the plant's leaves. This research creates a tool to accurately detect plant leaf width through plant growth monitored by the people-research implementation in the form of a mobile application that can detect the width of plant leaves. Using the canny edge detection method, the results obtained system accuracy of 95.06%, the light intensity of 18.75 lux, angle of 90°, and distance of 30 cm. Pak Choy plant growth was seen for 4 weeks, the best accuracy was obtained at 2nd week with an average accuracy of 99% and an average light intensity value of 22 lux.","PeriodicalId":416542,"journal":{"name":"2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126046365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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