Pub Date : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268415
D. Kim, Junhui Lee, Hyeon-Woo Na, Chan Park, P. Park
This paper presents a novel active noise control (ANC) based on a robust filtered-x normalized least mean square sign (R-FxNLMSS) algorithm against the large measurement noises and impulsive noises. The R-FxNLMSS algorithm updates the filter using the Euclidean norm of the sum from the previous weight vectors to the present weight vectors, which has robustness not only against the large measurement noises but also against the impulsive noises. Simulation results show that the proposed ANC based on the R-FxNLMSS algorithm has lower steady-state errors and faster convergence rate than the ANC based on the existing algorithms in extreme environments where the measurement noises are very large and the impulsive noises are generated randomly.
{"title":"Novel active noise control based on a robust filtered-x normalized least mean square sign algorithm against large measurement and impulsive noises","authors":"D. Kim, Junhui Lee, Hyeon-Woo Na, Chan Park, P. Park","doi":"10.23919/ICCAS50221.2020.9268415","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268415","url":null,"abstract":"This paper presents a novel active noise control (ANC) based on a robust filtered-x normalized least mean square sign (R-FxNLMSS) algorithm against the large measurement noises and impulsive noises. The R-FxNLMSS algorithm updates the filter using the Euclidean norm of the sum from the previous weight vectors to the present weight vectors, which has robustness not only against the large measurement noises but also against the impulsive noises. Simulation results show that the proposed ANC based on the R-FxNLMSS algorithm has lower steady-state errors and faster convergence rate than the ANC based on the existing algorithms in extreme environments where the measurement noises are very large and the impulsive noises are generated randomly.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"39 1","pages":"617-621"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76592222","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268398
Yoo. DongHa, Min. InJoon, Ahn. MinSung, Han. Jeakweon
In this paper, we propose an effective localization method with only a stereo camera that has obstacles using particle filter. When localization with flow planning rather than robot scanned map, the error of localization increases when there is an obstacle. To solve this problem, First, we propose two types of obstacle recognition method: "Image Split Obstacle" and "Obstacle In Image" through image processing using the Opencv contour function. Afterwards, we solve the problems caused by the particle filter weight calculation process through a new sensing model using interval angle. In addition, we propose two probability models that can solve the problem of inconsistency between the number of landmarks of robots and particles. After that, we suggest an effective robot localization method by presenting a probability model that considers obstacles. As a result, the probability model considering obstacles showed an error rate reduction of about 45% compared to the existing model that does not considering obstacles.
{"title":"Improving Localization Performance of Robot Using Obstacle Recognition and Probability Model through Image Processing","authors":"Yoo. DongHa, Min. InJoon, Ahn. MinSung, Han. Jeakweon","doi":"10.23919/ICCAS50221.2020.9268398","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268398","url":null,"abstract":"In this paper, we propose an effective localization method with only a stereo camera that has obstacles using particle filter. When localization with flow planning rather than robot scanned map, the error of localization increases when there is an obstacle. To solve this problem, First, we propose two types of obstacle recognition method: \"Image Split Obstacle\" and \"Obstacle In Image\" through image processing using the Opencv contour function. Afterwards, we solve the problems caused by the particle filter weight calculation process through a new sensing model using interval angle. In addition, we propose two probability models that can solve the problem of inconsistency between the number of landmarks of robots and particles. After that, we suggest an effective robot localization method by presenting a probability model that considers obstacles. As a result, the probability model considering obstacles showed an error rate reduction of about 45% compared to the existing model that does not considering obstacles.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"18 1","pages":"1056-1061"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89499218","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268385
Tomas Docekal, S. Ozana
The paper deals with the control design of nonlinear systems. It presents the application of the presented methodology on a swing-up of a single inverted pendulum. It is aimed at planning the reference state trajectories and the appropriate feedforward control signal and formulated by a two-point boundary value problem. One of the complications during the solution tackles the problem of providing a good initial guess for state trajectories. The additional optimization procedure for dealing with this issue is described in this paper. There is an emphasis on the universality of the described solution of the boundary value problem because it can be applied for a variety of different nonlinear systems.
{"title":"Application of two-point boundary problem with optimization of a candidate function","authors":"Tomas Docekal, S. Ozana","doi":"10.23919/ICCAS50221.2020.9268385","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268385","url":null,"abstract":"The paper deals with the control design of nonlinear systems. It presents the application of the presented methodology on a swing-up of a single inverted pendulum. It is aimed at planning the reference state trajectories and the appropriate feedforward control signal and formulated by a two-point boundary value problem. One of the complications during the solution tackles the problem of providing a good initial guess for state trajectories. The additional optimization procedure for dealing with this issue is described in this paper. There is an emphasis on the universality of the described solution of the boundary value problem because it can be applied for a variety of different nonlinear systems.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"1 1","pages":"912-915"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89908375","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268413
Yao Mu, Baiyu Peng, Ziqing Gu, S. Li, Chang Liu, Bingbing Nie, Jianfeng Zheng, Bo Zhang
Reinforcement learning has the potential to control stochastic nonlinear systems in optimal manners successfully. We propose a mixed reinforcement learning (mixed RL) algorithm by simultaneously using dual representations of environmental dynamics to search the optimal policy. The dual representation includes an empirical dynamic model and a set of state-action data. The former can embed the designer’s knowledge and reduce the difficulty of learning, and the latter can be used to compensate the model inaccuracy since it reflects the real system dynamics accurately. Such a design has the capability of improving both learning accuracy and training speed. In the mixed RL framework, the additive uncertainty of stochastic model is compensated by using explored state-action data via iterative Bayesian estimator (IBE). The optimal policy is then computed in an iterative way by alternating between policy evaluation (PEV) and policy improvement (PIM). The effectiveness of mixed RL is demonstrated by a typical optimal control problem of stochastic non-affine nonlinear systems (i.e., double lane change task with an automated vehicle).
{"title":"Mixed Reinforcement Learning for Efficient Policy Optimization in Stochastic Environments","authors":"Yao Mu, Baiyu Peng, Ziqing Gu, S. Li, Chang Liu, Bingbing Nie, Jianfeng Zheng, Bo Zhang","doi":"10.23919/ICCAS50221.2020.9268413","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268413","url":null,"abstract":"Reinforcement learning has the potential to control stochastic nonlinear systems in optimal manners successfully. We propose a mixed reinforcement learning (mixed RL) algorithm by simultaneously using dual representations of environmental dynamics to search the optimal policy. The dual representation includes an empirical dynamic model and a set of state-action data. The former can embed the designer’s knowledge and reduce the difficulty of learning, and the latter can be used to compensate the model inaccuracy since it reflects the real system dynamics accurately. Such a design has the capability of improving both learning accuracy and training speed. In the mixed RL framework, the additive uncertainty of stochastic model is compensated by using explored state-action data via iterative Bayesian estimator (IBE). The optimal policy is then computed in an iterative way by alternating between policy evaluation (PEV) and policy improvement (PIM). The effectiveness of mixed RL is demonstrated by a typical optimal control problem of stochastic non-affine nonlinear systems (i.e., double lane change task with an automated vehicle).","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"59 1","pages":"1212-1219"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79540430","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268389
Seungyun Han, Changki Choi, Sanguk Kwon, Seongjun Lee, Jonghoon Kim
Safety is critical issue for using lithium-ion battery. There are many causes and effects of faults in lithium-ion battery. Thermal runaway is the most hazardous safety problem. It leads to the dangerous result such as fire or explosion of the battery. If thermal runaway is occurred in application, its application like electrical vehicle or energy storage system would be a catastrophe. For preventing thermal runaway, diagnosis and prognosis of main causes are significant. One of the main causes of thermal runaway is internal short circuit. In this work, change of voltage and temperature from internal short circuit are analyzed. Usually, it is hard to detect internal short circuit in normal electrical equivalent circuit model (EECM). Thus, lots of papers apply a parallel resistor in EECM to catch internal short circuit. In this paper, this model is used to show effects from internal short circuit. Resistance of parallel resistor represents the probability of occurrence of internal short circuit. Current passing through the parallel resistor indicates the leakage current inside of the battery which is not detected. To verify the model in high energy lithium-ion battery, induced internal short circuit suggested in UL standard is conducted. And change of voltage, internal leakage current, parallel resistor’s value is analyzed.
{"title":"Electrical Analysis about internal short circuit using additional resistance in high energy lithium-ion battery","authors":"Seungyun Han, Changki Choi, Sanguk Kwon, Seongjun Lee, Jonghoon Kim","doi":"10.23919/ICCAS50221.2020.9268389","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268389","url":null,"abstract":"Safety is critical issue for using lithium-ion battery. There are many causes and effects of faults in lithium-ion battery. Thermal runaway is the most hazardous safety problem. It leads to the dangerous result such as fire or explosion of the battery. If thermal runaway is occurred in application, its application like electrical vehicle or energy storage system would be a catastrophe. For preventing thermal runaway, diagnosis and prognosis of main causes are significant. One of the main causes of thermal runaway is internal short circuit. In this work, change of voltage and temperature from internal short circuit are analyzed. Usually, it is hard to detect internal short circuit in normal electrical equivalent circuit model (EECM). Thus, lots of papers apply a parallel resistor in EECM to catch internal short circuit. In this paper, this model is used to show effects from internal short circuit. Resistance of parallel resistor represents the probability of occurrence of internal short circuit. Current passing through the parallel resistor indicates the leakage current inside of the battery which is not detected. To verify the model in high energy lithium-ion battery, induced internal short circuit suggested in UL standard is conducted. And change of voltage, internal leakage current, parallel resistor’s value is analyzed.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"23 1","pages":"469-498"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80130512","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268278
Tzu-Hsuan Ho, K. Song
In this paper, we propose an AR-based robotic system that can plan and execute a trajectory based on a 3D medical model and allow the surgeon to supervise the execution of surgical process. In order to achieve image-guided surgery, a hand-eye calibration procedure is developed by using AprilTag to obtain the transformation between the workspace coordinate and the robot coordinate, and perform the image navigation task of the surgical robot to complete a drilling task. A procedure of robot supervised control is proposed to assign or modify the robot trajectory based on AR visualization and 3D model. A specified AR marker is used to project virtual objects in the AR glasses. We developed a robot registration algorithm to match the AR virtual coordinate system and the workspace coordinate system, and convert the planned trajectory into robot trajectory. Experimental results on the lab-built robotic system show that a user can adjust the position and orientation of the insertion point on a bone model, and transmit the trajectory information to the robot for execution. The proposed visualization-based robot navigation method has the potential to enhance the safety of surgical operation.
{"title":"Supervised Control for Robot-Assisted Surgery Using Augmented Reality","authors":"Tzu-Hsuan Ho, K. Song","doi":"10.23919/ICCAS50221.2020.9268278","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268278","url":null,"abstract":"In this paper, we propose an AR-based robotic system that can plan and execute a trajectory based on a 3D medical model and allow the surgeon to supervise the execution of surgical process. In order to achieve image-guided surgery, a hand-eye calibration procedure is developed by using AprilTag to obtain the transformation between the workspace coordinate and the robot coordinate, and perform the image navigation task of the surgical robot to complete a drilling task. A procedure of robot supervised control is proposed to assign or modify the robot trajectory based on AR visualization and 3D model. A specified AR marker is used to project virtual objects in the AR glasses. We developed a robot registration algorithm to match the AR virtual coordinate system and the workspace coordinate system, and convert the planned trajectory into robot trajectory. Experimental results on the lab-built robotic system show that a user can adjust the position and orientation of the insertion point on a bone model, and transmit the trajectory information to the robot for execution. The proposed visualization-based robot navigation method has the potential to enhance the safety of surgical operation.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"30 1","pages":"329-334"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76184092","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268336
Sergazy Narynov, Daniyar Mukhtarkhanuly, B. Omarov, K. Kozhakhmet, Bauyrzhan Omarov
According to the latest who data published in 2017, the number of suicides in Kazakhstan was 4855, or 3.55% of the total number of deaths. The age-adjusted death rate is 27.74 per 100,000 population. Kazakhstan is ranked 4th in the world by this indicator. This article compares machine learning algorithms with and without a teacher to identify depressive content in social media posts, with a focus on hopelessness and psychological pain for semantic analysis as key causes of suicide. Suicide is not spontaneous, and preparation for suicide can last about a year, during which time a person will show signs of their condition in our case by posting depressive content on their social network profile. This algorithm helps in detecting depressive content that can cause suicide to help people find confident help from psychologists at the national center for suicide prevention in Kazakhstan. Having obtained the highest score for 95% of the f1 score for a random forest (training with a teacher) with the tf-idf vectorization model, we can conclude by saying that the K-means algorithm(training without a teacher) using tf-idf shows impressive results that are only 4% lower in f1 and accuracy.
{"title":"Machine Learning Approach to Identifying Depression Related Posts on Social Media","authors":"Sergazy Narynov, Daniyar Mukhtarkhanuly, B. Omarov, K. Kozhakhmet, Bauyrzhan Omarov","doi":"10.23919/ICCAS50221.2020.9268336","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268336","url":null,"abstract":"According to the latest who data published in 2017, the number of suicides in Kazakhstan was 4855, or 3.55% of the total number of deaths. The age-adjusted death rate is 27.74 per 100,000 population. Kazakhstan is ranked 4th in the world by this indicator. This article compares machine learning algorithms with and without a teacher to identify depressive content in social media posts, with a focus on hopelessness and psychological pain for semantic analysis as key causes of suicide. Suicide is not spontaneous, and preparation for suicide can last about a year, during which time a person will show signs of their condition in our case by posting depressive content on their social network profile. This algorithm helps in detecting depressive content that can cause suicide to help people find confident help from psychologists at the national center for suicide prevention in Kazakhstan. Having obtained the highest score for 95% of the f1 score for a random forest (training with a teacher) with the tf-idf vectorization model, we can conclude by saying that the K-means algorithm(training without a teacher) using tf-idf shows impressive results that are only 4% lower in f1 and accuracy.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"4 1","pages":"6-11"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84346293","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268259
Subham Agrawal, Chathura Simasinghe, A. Jafari, Appolinaire C. Etoundi, J. Chong
The design of the human knee joint has been a challenging task due to the presence of intricate parts, complex mechanisms and their interdependence which joins them together. A bio-inspired design for the condylar knee joint has been proposed in earlier publications [1], [2]. However, the manufacturing limitation of the design was not considered. This paper introduces a de-risked and optimised design through the use of standard design and manufacturing techniques based on the gathered data from a robotics leg test bench. Moreover, this paper presents an optimised design derived from a state-of-the-art artificial intelligence tool. The optimized design using conventional methods is tested against real-world loading conditions during finite element analysis and the results are presented.
{"title":"A De-risked Bio-inspired Condylar Prosthetic Knee Joint for a Robotic Leg Test Rig","authors":"Subham Agrawal, Chathura Simasinghe, A. Jafari, Appolinaire C. Etoundi, J. Chong","doi":"10.23919/ICCAS50221.2020.9268259","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268259","url":null,"abstract":"The design of the human knee joint has been a challenging task due to the presence of intricate parts, complex mechanisms and their interdependence which joins them together. A bio-inspired design for the condylar knee joint has been proposed in earlier publications [1], [2]. However, the manufacturing limitation of the design was not considered. This paper introduces a de-risked and optimised design through the use of standard design and manufacturing techniques based on the gathered data from a robotics leg test bench. Moreover, this paper presents an optimised design derived from a state-of-the-art artificial intelligence tool. The optimized design using conventional methods is tested against real-world loading conditions during finite element analysis and the results are presented.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"41 1","pages":"592-597"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86014335","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268226
Eugene Jeong, Minseok Seo, Kyung-Soo Kim
Brain-computer interface (BCI) has been in the center of interest for many researchers for the past few decades, resulting in various methods to obtain signals from the brain and algorithms to process the signal. Among those brain signal obtaining methods under research, functional near infra-red spectroscopy (fNIRS) is a method with great potential of acquiring accurate data of neural activities. This paper provides the fundamentals for building an fNIRS system and how to process the acquired data to obtain a signal relevant of neural activity. Customization for particular applications is possible enabling novice brain researchers to join the research field and further improve BCI.
{"title":"Basic steps for building and using a functional near infra-red spectroscopy (fNIRS) System","authors":"Eugene Jeong, Minseok Seo, Kyung-Soo Kim","doi":"10.23919/ICCAS50221.2020.9268226","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268226","url":null,"abstract":"Brain-computer interface (BCI) has been in the center of interest for many researchers for the past few decades, resulting in various methods to obtain signals from the brain and algorithms to process the signal. Among those brain signal obtaining methods under research, functional near infra-red spectroscopy (fNIRS) is a method with great potential of acquiring accurate data of neural activities. This paper provides the fundamentals for building an fNIRS system and how to process the acquired data to obtain a signal relevant of neural activity. Customization for particular applications is possible enabling novice brain researchers to join the research field and further improve BCI.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"33 1","pages":"1010-1012"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86223134","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 : 2020-10-13DOI: 10.23919/ICCAS50221.2020.9268365
Elaiza Nicole Salamat, Jaehyun Yoo
Advancement of technology has led to the improvement of agricultural practices, which results in the increase of agricultural production and aids in solving the global food shortage. In this study, the intensive cultivation of food will be automated by designing a microcontroller based wireless sensor network (WSN) system, which will facilitate the constant conditioning inside the growing houses, especially during the fruiting stage. The system consists of two stations: sensors and actuators station and remote monitoring station. The sensors and actuators are placed in a structured model and wireless sensor nodes are programmed to enable reading of data from the sensors. Temperature, humidity and substrate moisture are controlled according to the desired conditions The whole system is monitored and controlled through transmission of data recorded to the remote monitoring station using WSN.
{"title":"Development of Growing House Control System using Wireless Sensor Network","authors":"Elaiza Nicole Salamat, Jaehyun Yoo","doi":"10.23919/ICCAS50221.2020.9268365","DOIUrl":"https://doi.org/10.23919/ICCAS50221.2020.9268365","url":null,"abstract":"Advancement of technology has led to the improvement of agricultural practices, which results in the increase of agricultural production and aids in solving the global food shortage. In this study, the intensive cultivation of food will be automated by designing a microcontroller based wireless sensor network (WSN) system, which will facilitate the constant conditioning inside the growing houses, especially during the fruiting stage. The system consists of two stations: sensors and actuators station and remote monitoring station. The sensors and actuators are placed in a structured model and wireless sensor nodes are programmed to enable reading of data from the sensors. Temperature, humidity and substrate moisture are controlled according to the desired conditions The whole system is monitored and controlled through transmission of data recorded to the remote monitoring station using WSN.","PeriodicalId":6732,"journal":{"name":"2020 20th International Conference on Control, Automation and Systems (ICCAS)","volume":"39 1","pages":"1031-1033"},"PeriodicalIF":0.0,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88058600","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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