Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293716
F. Cruz, Jeremiah A. Ordiales, Malvin Angelo C. Reyes, Pinky T. Salvanera
Municipal fishermen experience collisions and being rammed by larger marine vessels. Automatic identification system (AIS) can be a solution for them, if not for its high cost. Likewise, in emergency situations, due to limited cellular coverage at sea, fishermen do not have the means to communicate with each other and request for assistance. Therefore, this design addresses these concerns with a low-cost AIS receiver embedded with intercommunication using microcomputer and software-defined radio.
{"title":"Automatic Identification System Receiver for Small Fishing Vessels","authors":"F. Cruz, Jeremiah A. Ordiales, Malvin Angelo C. Reyes, Pinky T. Salvanera","doi":"10.1109/TENCON50793.2020.9293716","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293716","url":null,"abstract":"Municipal fishermen experience collisions and being rammed by larger marine vessels. Automatic identification system (AIS) can be a solution for them, if not for its high cost. Likewise, in emergency situations, due to limited cellular coverage at sea, fishermen do not have the means to communicate with each other and request for assistance. Therefore, this design addresses these concerns with a low-cost AIS receiver embedded with intercommunication using microcomputer and software-defined radio.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122540782","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293868
Ma. Jenica M. Autos, Samantha Kaye S. Falculan, J. Fortin, June F. Mendoza, Anna-liza F. Sigue, M. G. Beaño, Oliver A. Medina, Don Juan M. Tuazon
This paper introduces the development of monitoring and maintaining optimal water quality in an aquaponics system. The design is based on the hydroponics system’s Nutrient Film Technique (NFT) in which plant roots are being exposed to a thin layer of nutrient water in a long narrow channel. The design used a developmental and experimental type with the use of microprocessors and sensors for enhanced monitoring and error-correcting within the aquaponics system where standard data was obtained from different reliable sources. Various sensors are calibrated for different measurements to provide accurate and reliable readings of water temperature, pH level, dissolved oxygen, total dissolved solids, water flow, and temperature and humidity. The Arduino Mega reads and analyzes data collected by various sensors, and instructs actuators such as aquarium heater, cooling fan, aerator, grow light, and water pump. The data gathered appears on the built-in LCD screen and will be sent to the owner's mobile phone regarding the condition of the system. Also, the system has a fish feeder that automatically dispenses food at a given time. The device can be controlled wirelessly using a mobile phone and manually using a 4x4 keypad. Also, the owner can monitor the way each actuator was controlled.
{"title":"Automated Aquaponics System and Water Quality Monitoring with SMS Notification for Tilapia Industry","authors":"Ma. Jenica M. Autos, Samantha Kaye S. Falculan, J. Fortin, June F. Mendoza, Anna-liza F. Sigue, M. G. Beaño, Oliver A. Medina, Don Juan M. Tuazon","doi":"10.1109/TENCON50793.2020.9293868","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293868","url":null,"abstract":"This paper introduces the development of monitoring and maintaining optimal water quality in an aquaponics system. The design is based on the hydroponics system’s Nutrient Film Technique (NFT) in which plant roots are being exposed to a thin layer of nutrient water in a long narrow channel. The design used a developmental and experimental type with the use of microprocessors and sensors for enhanced monitoring and error-correcting within the aquaponics system where standard data was obtained from different reliable sources. Various sensors are calibrated for different measurements to provide accurate and reliable readings of water temperature, pH level, dissolved oxygen, total dissolved solids, water flow, and temperature and humidity. The Arduino Mega reads and analyzes data collected by various sensors, and instructs actuators such as aquarium heater, cooling fan, aerator, grow light, and water pump. The data gathered appears on the built-in LCD screen and will be sent to the owner's mobile phone regarding the condition of the system. Also, the system has a fish feeder that automatically dispenses food at a given time. The device can be controlled wirelessly using a mobile phone and manually using a 4x4 keypad. Also, the owner can monitor the way each actuator was controlled.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131783359","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293720
D. Dassanayake, S. Wijesinghe, T.L.C Jayasiri, K.A.S.T. Keenawinna, W. Rankothge, N. Gamage
It is widely recognized that a nation with minimum problems relating to areas such as health, environment, infrastructure, and technology is a developed country [1]. However, the developing/ lower-middle income countries need many improvements in the above-mentioned areas, as they are still lacking in those areas [1]. Apart from the risk associated with these problems, the main challenge faced by developing countries is, making the public aware of these problems. In this paper, we are proposing a mobile game-based learning platform: "AwareME" which focuses on following problems: (1) health awareness (dengue fever), (2) environmental awareness (garbage disposal), (3) cyber security awareness (social media) and (4) safety awareness (road safety). The "AwareME" platform includes quizzes, 2D/3D puzzle games, and 3D action games with activities to improve the cognitive skills and awareness of the public. We have provided the results of an initial performance evaluation of "AwareME" platform.
{"title":"AwareME: Public Awareness through Game-Based Learning","authors":"D. Dassanayake, S. Wijesinghe, T.L.C Jayasiri, K.A.S.T. Keenawinna, W. Rankothge, N. Gamage","doi":"10.1109/TENCON50793.2020.9293720","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293720","url":null,"abstract":"It is widely recognized that a nation with minimum problems relating to areas such as health, environment, infrastructure, and technology is a developed country [1]. However, the developing/ lower-middle income countries need many improvements in the above-mentioned areas, as they are still lacking in those areas [1]. Apart from the risk associated with these problems, the main challenge faced by developing countries is, making the public aware of these problems. In this paper, we are proposing a mobile game-based learning platform: \"AwareME\" which focuses on following problems: (1) health awareness (dengue fever), (2) environmental awareness (garbage disposal), (3) cyber security awareness (social media) and (4) safety awareness (road safety). The \"AwareME\" platform includes quizzes, 2D/3D puzzle games, and 3D action games with activities to improve the cognitive skills and awareness of the public. We have provided the results of an initial performance evaluation of \"AwareME\" platform.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134572786","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293707
Sayan Sarkar, W. Ki
This research studies the effect of a starving resistor in various pre-driver schemes for shoot-through loss reduction in the buffer of an integrated DC-DC converter and explores how the efficiency is affected. The starving resistor (Bidirectional delay element) reduces the short circuit current of an inverter by developing time skewed gate driving signals for the driven stage NMOS and PMOS inside a buffer. The starving resistor scheme enhances the efficiency if it is inside the buffer of a switch, but is not as efficient if it is inside the buffer of an active diode. The efficiency of the buffer can be further enhanced by adding delay generator schemes within a buffer. Results are validated via extensive SPICE simulations.
{"title":"A Study on Shoot-Through Reduction of DC-DC Converter Pre-Driver using Starving Resistor","authors":"Sayan Sarkar, W. Ki","doi":"10.1109/TENCON50793.2020.9293707","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293707","url":null,"abstract":"This research studies the effect of a starving resistor in various pre-driver schemes for shoot-through loss reduction in the buffer of an integrated DC-DC converter and explores how the efficiency is affected. The starving resistor (Bidirectional delay element) reduces the short circuit current of an inverter by developing time skewed gate driving signals for the driven stage NMOS and PMOS inside a buffer. The starving resistor scheme enhances the efficiency if it is inside the buffer of a switch, but is not as efficient if it is inside the buffer of an active diode. The efficiency of the buffer can be further enhanced by adding delay generator schemes within a buffer. Results are validated via extensive SPICE simulations.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133176019","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293839
M. Aqib, A. Ukil
Agent-based models (ABM) are a kind of micro scale model that imitate the simultaneous operations and interactions of multiple agents in an attempt to re-create and predict the appearance of complex process. Netlogo is a real time simulation software tool to design this model with the help of programming and coding. This paper identifies decision variables based on electric vehicles (EVs) charging statistics and the heuristic decisions in EVs charging at public charging stations, commercial place and offices are converted into constraints of (ABM). This unique model is the version of real time charging scenario at the charging stations. With the help of programmed model in Netlogo, the behaviour of EVs user under different real life scenarios are observed and recorded. The proposed system is implemented and designed in Netlogo to test the results.
{"title":"Modelling of Electric Vehicle Charging and Discharging Profile to Mimic Real life Scenario at Charging Stations","authors":"M. Aqib, A. Ukil","doi":"10.1109/TENCON50793.2020.9293839","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293839","url":null,"abstract":"Agent-based models (ABM) are a kind of micro scale model that imitate the simultaneous operations and interactions of multiple agents in an attempt to re-create and predict the appearance of complex process. Netlogo is a real time simulation software tool to design this model with the help of programming and coding. This paper identifies decision variables based on electric vehicles (EVs) charging statistics and the heuristic decisions in EVs charging at public charging stations, commercial place and offices are converted into constraints of (ABM). This unique model is the version of real time charging scenario at the charging stations. With the help of programmed model in Netlogo, the behaviour of EVs user under different real life scenarios are observed and recorded. The proposed system is implemented and designed in Netlogo to test the results.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115813043","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293769
Jehriel Joseph S. Casunuran, Christine Rose C. Quiambao, Matthew E. Fordan, Aldrin J. Soriano, M. G. Beaño, Ericson A. Mandayo, Bernie B. Domingo
Over the years, the manual checking of attendance has been carried across most of the educational institutions. Manual attendance monitoring results in a lot of time consumed. To overcome the problem for manual attendance, the researchers proposed a Quick Response (QR) Code Attendance System with SMS Location Tracker that can provide information about the student’s arrival and departure time in school. The main purpose of the study is to design a QR Code Attendance System to improve the manual/traditional attendance and to provide a Global Positioning System (GPS) that can track the location of the students. The researchers used an Incremental Methodology to approach the study. It is a method in which the product is incrementally designed, implemented, and evaluated until the product is complete. The design project was tested and evaluated by 50 users and 10 experts. Based on the series of testing the system can provide an easier and more convenient recording and checking of attendance using the QR Code Scanner, it is also capable of providing the information about attendance by sending a text message and can provide location by requesting on the Android Application.
{"title":"Quick Response Code Attendance System with SMS Location Tracker","authors":"Jehriel Joseph S. Casunuran, Christine Rose C. Quiambao, Matthew E. Fordan, Aldrin J. Soriano, M. G. Beaño, Ericson A. Mandayo, Bernie B. Domingo","doi":"10.1109/TENCON50793.2020.9293769","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293769","url":null,"abstract":"Over the years, the manual checking of attendance has been carried across most of the educational institutions. Manual attendance monitoring results in a lot of time consumed. To overcome the problem for manual attendance, the researchers proposed a Quick Response (QR) Code Attendance System with SMS Location Tracker that can provide information about the student’s arrival and departure time in school. The main purpose of the study is to design a QR Code Attendance System to improve the manual/traditional attendance and to provide a Global Positioning System (GPS) that can track the location of the students. The researchers used an Incremental Methodology to approach the study. It is a method in which the product is incrementally designed, implemented, and evaluated until the product is complete. The design project was tested and evaluated by 50 users and 10 experts. Based on the series of testing the system can provide an easier and more convenient recording and checking of attendance using the QR Code Scanner, it is also capable of providing the information about attendance by sending a text message and can provide location by requesting on the Android Application.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134083331","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293943
Josh Angelo Escalona, Benjamin Manalo, Wilbert Jethro R. Limjoco, Carl C. Dizon
Ride sharing is one of the several transportation alternatives used to ease and skip traffic problems worldwide. A platform of interest is GrabShare, where its ride sharing algorithm was empirically found to be simple. However, the algorithm has several limitations, such as it being not truly optimal due to catering to user experiences, and only able to handle up to two bookings. Hence, there is a need to develop a ride sharing system that is scalable, fast, and efficient especially in terms of finding matches and recommending routes. A Modified Search-based Ride Sharing algorithm, which uses an expansion-based method, was developed as a response to these requirements. Results showed that the Modified Search-based Ride Sharing algorithm generally outperforms the empirically-derived GrabShare algorithm in terms of route length, shared route percentage, and processing time. However, GrabShare performs better when there are few passengers in the area while the Modified Search-based Ride Sharing algorithm runs relatively slower when the sources and destinations are far from each other.
{"title":"A Ride Sharing System based on An Expansive Search-Based Algorithm","authors":"Josh Angelo Escalona, Benjamin Manalo, Wilbert Jethro R. Limjoco, Carl C. Dizon","doi":"10.1109/TENCON50793.2020.9293943","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293943","url":null,"abstract":"Ride sharing is one of the several transportation alternatives used to ease and skip traffic problems worldwide. A platform of interest is GrabShare, where its ride sharing algorithm was empirically found to be simple. However, the algorithm has several limitations, such as it being not truly optimal due to catering to user experiences, and only able to handle up to two bookings. Hence, there is a need to develop a ride sharing system that is scalable, fast, and efficient especially in terms of finding matches and recommending routes. A Modified Search-based Ride Sharing algorithm, which uses an expansion-based method, was developed as a response to these requirements. Results showed that the Modified Search-based Ride Sharing algorithm generally outperforms the empirically-derived GrabShare algorithm in terms of route length, shared route percentage, and processing time. However, GrabShare performs better when there are few passengers in the area while the Modified Search-based Ride Sharing algorithm runs relatively slower when the sources and destinations are far from each other.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133625264","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293736
Nafisa Azad Tultul, Subrin Farha, S. S. Hossain, Md. Akbar Hossain, S. R. Sabuj
The increasing demand for higher data rates pushes the boundaries of the currently used radio spectrum. The terahertz (THz) frequency band (0.1-10 THz) is widely considered by scientific community to address spectrum scarcity. In this paper we developed a theoretical model for device-to-device (D2D) communication operating in THz band. We also derived a close form formula of data rates, outage probability, and energy efficiency. Our simulation results show an improvement of data rates and energy efficiency while decreasing the outage probability of D2D communication in THz. For instance, there is 86% of increase in energy efficiency when the transmission power is 19dBm. Finally, the improvement of energy efficiency is 87% using optimal transmission power due to 50 resource blocks.
{"title":"Device-to-Device Communication in Terahertz Frequency Band: Enhancement of Energy Efficiency","authors":"Nafisa Azad Tultul, Subrin Farha, S. S. Hossain, Md. Akbar Hossain, S. R. Sabuj","doi":"10.1109/TENCON50793.2020.9293736","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293736","url":null,"abstract":"The increasing demand for higher data rates pushes the boundaries of the currently used radio spectrum. The terahertz (THz) frequency band (0.1-10 THz) is widely considered by scientific community to address spectrum scarcity. In this paper we developed a theoretical model for device-to-device (D2D) communication operating in THz band. We also derived a close form formula of data rates, outage probability, and energy efficiency. Our simulation results show an improvement of data rates and energy efficiency while decreasing the outage probability of D2D communication in THz. For instance, there is 86% of increase in energy efficiency when the transmission power is 19dBm. Finally, the improvement of energy efficiency is 87% using optimal transmission power due to 50 resource blocks.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132802598","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293693
Marcia Coleen N. Marcial, J. R. Santillan
Mapping tree species is essential for monitoring, planning, and better managing industrial tree plantations (ITP). Due to the intensive procedure of field sampling and multi-class manual training data collection for image classification, an approach that allows fewer data would be efficient. This study evaluated the performance of a one-class classifier called Maximum Entropy (MaxEnt) for mapping Falcata (Paraserianthes falcataria) in Sentinel-2 imagery. Two MaxEnt parameters were tested, namely sample size and binary threshold. Using a default threshold of 0.5, MaxEnt can provide classification accuracies ranging from 89.41-92.84% using sample sizes as small as 30 and as high as 500. A 0.3 binary threshold applied to MaxEnt logistic output with 500 samples were the best parameter values for classifying Falcata using Sentinel-2 imagery.
{"title":"A Maximum Entropy Approach for Mapping Falcata Plantations in Sentinel-2 Imagery","authors":"Marcia Coleen N. Marcial, J. R. Santillan","doi":"10.1109/TENCON50793.2020.9293693","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293693","url":null,"abstract":"Mapping tree species is essential for monitoring, planning, and better managing industrial tree plantations (ITP). Due to the intensive procedure of field sampling and multi-class manual training data collection for image classification, an approach that allows fewer data would be efficient. This study evaluated the performance of a one-class classifier called Maximum Entropy (MaxEnt) for mapping Falcata (Paraserianthes falcataria) in Sentinel-2 imagery. Two MaxEnt parameters were tested, namely sample size and binary threshold. Using a default threshold of 0.5, MaxEnt can provide classification accuracies ranging from 89.41-92.84% using sample sizes as small as 30 and as high as 500. A 0.3 binary threshold applied to MaxEnt logistic output with 500 samples were the best parameter values for classifying Falcata using Sentinel-2 imagery.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122332261","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 : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293866
Sandy C. Lauguico, Ronnie S. Concepcion, Rogelio Ruzcko Tobias, A. Bandala, R. R. Vicerra, E. Dadios
Identifying variant diseases in leaves is a significant method for optimizing food production. As the global population continues to arise and agricultural space continues to decline, every possible way of increasing the supply of food in any given condition and limited resources will address the above-mentioned problems. This study proposes a way for detecting three different diseases from grape leaves apart from the healthy leaves and considers the confidence value of the system in correctly identifying the classes. The diseases are namely: Black Rot, Black Measles, and Isariopsis. The system conducted a comparative analysis to determine which among the three pre-trained networks, AlexNet, GoogLeNet, and ResNet-18 will be the most suitable network to be integrated with Regions with Convolutional Neural Networks (RCNN) in performing multiple object detection in a given image. The data used in training the models comprised of annotated image data represented as a ground truth table with image files and their corresponding bounding boxes coordinates. The models evaluated resulted to AlexNet being the best pre-trained network to be working on the RCNN with an accuracy of 95.65%. The other two models from GoogLeNet and ResNet-18 only obtained accuracies of 92.29% and 89.49% respectively.
{"title":"Grape Leaf Multi-disease Detection with Confidence Value Using Transfer Learning Integrated to Regions with Convolutional Neural Networks","authors":"Sandy C. Lauguico, Ronnie S. Concepcion, Rogelio Ruzcko Tobias, A. Bandala, R. R. Vicerra, E. Dadios","doi":"10.1109/TENCON50793.2020.9293866","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293866","url":null,"abstract":"Identifying variant diseases in leaves is a significant method for optimizing food production. As the global population continues to arise and agricultural space continues to decline, every possible way of increasing the supply of food in any given condition and limited resources will address the above-mentioned problems. This study proposes a way for detecting three different diseases from grape leaves apart from the healthy leaves and considers the confidence value of the system in correctly identifying the classes. The diseases are namely: Black Rot, Black Measles, and Isariopsis. The system conducted a comparative analysis to determine which among the three pre-trained networks, AlexNet, GoogLeNet, and ResNet-18 will be the most suitable network to be integrated with Regions with Convolutional Neural Networks (RCNN) in performing multiple object detection in a given image. The data used in training the models comprised of annotated image data represented as a ground truth table with image files and their corresponding bounding boxes coordinates. The models evaluated resulted to AlexNet being the best pre-trained network to be working on the RCNN with an accuracy of 95.65%. The other two models from GoogLeNet and ResNet-18 only obtained accuracies of 92.29% and 89.49% respectively.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121802469","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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