Pub Date : 2022-05-21DOI: 10.14313/jamris/3-2021/20
M. Drwiega
This paper presents a method of 3D maps integration based on overlapping regions detection and matching. The algorithm works without an initial guess about transformation. The process of finding transformation between maps can be divided into two steps. The first one is the estimation of an initial transformation based on feature extraction, description, and matching. The assumption is that the maps have an overlapping area that can be used during feature based processing. Then the found initial solution is corrected using local methods, for example, Iterative Closest Point (ICP) algorithm. The maps are stored in the octree based representation (octomaps) but during transformation estimation, a point cloud representation is used as well. In addition, the presented method was verified in various experiments: in a simulation, with wheeled robots, and with publicly available datasets. Eventually, the solution can be applied to many robotic applications related to the exploration of unknown environments. Nevertheless, so far the implemented method was validated with a group of wheeled robots.
{"title":"3D Maps Integration based on Overlapping Regions Matching","authors":"M. Drwiega","doi":"10.14313/jamris/3-2021/20","DOIUrl":"https://doi.org/10.14313/jamris/3-2021/20","url":null,"abstract":"\u0000This paper presents a method of 3D maps integration based on overlapping regions detection and matching. \u0000The algorithm works without an initial guess about transformation. The process of finding transformation between maps can be divided into two steps. \u0000The first one is the estimation of an initial transformation based on feature extraction, description, and matching. \u0000The assumption is that the maps have an overlapping area that can be used during feature based processing. \u0000Then the found initial solution is corrected using local methods, for example, Iterative Closest Point (ICP) algorithm. \u0000The maps are stored in the octree based representation (octomaps) but during transformation \u0000estimation, a point cloud representation is used as well. In addition, the presented method was verified in various experiments: in a simulation, with wheeled robots, and with publicly available datasets. \u0000Eventually, the solution can be applied to many robotic applications related to the exploration of unknown environments. \u0000Nevertheless, so far the implemented method was validated with a group of wheeled robots. \u0000","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"91 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76361166","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 : 2022-05-21DOI: 10.14313/jamris/3-2021/14
Abdul Sattar, Liuping Wang, A. Mohamed, A. Fisher
Different from conventional aircraft, an investigation on system identification and control design has been carried out on a small fixed wing unmanned aerial vehicle (UAV) with a multi-segment ailerons. The multi-segment aileron setup is configured as a multi-input and single-output system and each segment is modeled as a control input. Experiments are conducted in a wind tunnel to determine the frequency responses of the system and the corresponding transfer functions. Multiple PID controllers are designed and implemented in a cascaded form for each control surface. Furthermore, a heuristic switching control strategy is implemented for the aircraft where the multi-segment ailerons perform as a single-segment aileron in a normal flight condition, and adapts to multi-segment control when encountering severe turbulence or a large angle reference change. Experimental results reveal that although each control surface has the capability for stabilization of the aircraft, the proposed control strategy by combining the multiple actuation surfaces reduces the mean squared errors for the roll angle up to $37$ percent in the highly turbulent environment providing superior disturbance rejection properties to the aircraft.
{"title":"System Identification and Heuristic Control of Segmented Ailerons for Enhanced Stability of Fixed Wing UAVs","authors":"Abdul Sattar, Liuping Wang, A. Mohamed, A. Fisher","doi":"10.14313/jamris/3-2021/14","DOIUrl":"https://doi.org/10.14313/jamris/3-2021/14","url":null,"abstract":"Different from conventional aircraft, an investigation on system identification and control design has been carried out on a small fixed wing unmanned aerial vehicle (UAV) with a multi-segment ailerons. The multi-segment aileron setup is configured as a multi-input and single-output system and each segment is modeled as a control input. Experiments are conducted in a wind tunnel to determine the frequency responses of the system and the corresponding transfer functions. Multiple PID controllers are designed and implemented in a cascaded form for each control surface. Furthermore, a heuristic switching control strategy is implemented for the aircraft where the multi-segment ailerons perform as a single-segment aileron in a normal flight condition, and adapts to multi-segment control when encountering severe turbulence or a large angle reference change. Experimental results reveal that although each control surface has the capability for stabilization of the aircraft, the proposed control strategy by combining the multiple actuation surfaces reduces the mean squared errors for the roll angle up to $37$ percent in the highly turbulent environment providing superior disturbance rejection properties to the aircraft.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79261911","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 : 2022-05-21DOI: 10.14313/jamris/3-2021/18
Ihor Tereshchenko, A. Tereshchenko, N. Bilous, S. Shtangey, Z. Warsza
Many practical tasks of data multivariate statistical analysis from the standpoint of a risk-oriented process approach (in accordance with ISO 9001: 2015, 31000: 2018) requires the definition of the risk values for the dependent exogenous variables of some processes. This paper proposes the method, which consist of original stages sequence for calculating value-at-risk (VaR) or conditional-value-at-risk (CVaR) of dependent exogenous variables, presented of the extreme data frame of critical manufacture process parameters or other parameters, for example, extreme data of environmental monitoring and etc. Risk analysis method by the extreme data of dependent exogenous variables, presented of the data matrix, uses the result of solving the formalized problem of defines the tails parameters of the joint distributions of exogenous variables as components of a bivariate random variable. It can be argued that the tails parameters of the joint distributions of dependent exogenous variables make the validated corrections of the VaR and CVaR estimates for such variables. This method expands the practical application of extreme value theory for the value at risk analysis of any dependent variables as process parameters.
{"title":"Risk Analysis Method by the Extreme Data of Dependent Exogenous Variables","authors":"Ihor Tereshchenko, A. Tereshchenko, N. Bilous, S. Shtangey, Z. Warsza","doi":"10.14313/jamris/3-2021/18","DOIUrl":"https://doi.org/10.14313/jamris/3-2021/18","url":null,"abstract":"Many practical tasks of data multivariate statistical analysis from the standpoint of a risk-oriented process approach (in accordance with ISO 9001: 2015, 31000: 2018) requires the definition of the risk values for the dependent exogenous variables of some processes. This paper proposes the method, which consist of original stages sequence for calculating value-at-risk (VaR) or conditional-value-at-risk (CVaR) of dependent exogenous variables, presented of the extreme data frame of critical manufacture process parameters or other parameters, for example, extreme data of environmental monitoring and etc. Risk analysis method by the extreme data of dependent exogenous variables, presented of the data matrix, uses the result of solving the formalized problem of defines the tails parameters of the joint distributions of exogenous variables as components of a bivariate random variable. It can be argued that the tails parameters of the joint distributions of dependent exogenous variables make the validated corrections of the VaR and CVaR estimates for such variables. This method expands the practical application of extreme value theory for the value at risk analysis of any dependent variables as process parameters.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"111 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79301806","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 : 2022-05-01DOI: 10.14313/jamris/2-2022/15
Sheenal Malviya, Sourabh Dave, K. C. Bandhu, R. Litoriya
Abstract Cloud computing has emerged as a significant technology domain, primarily due to the emergence of big data, machine learning, and quantum computing applications. While earlier, cloud computing services were focused mainly on providing storage and some infrastructures/platforms for applications, the need to advance computational power analysis of massive datasets. It has made cloud computing almost inevitable from most client-based applications, mobile applications, or web applications. The allied challenge to protect data shared from and to cloud-based platforms has cropped up with the necessity to access public clouds. While conventional cryptographic algorithms have been used for securing and authenticating cloud data, advancements in cryptanalysis and access to faster computation have led to possible threats to the traditional security of cloud mechanisms. This has led to extensive research in homomorphic encryption pertaining to cloud security. In this paper, a security mechanism is designed targeted towards dynamic groups using public clouds. Cloud security mechanisms generally face a significant challenge in terms of overhead, throughput, and execution time to encrypt data from dynamic groups with frequent member addition and removal. A two-stage homomorphic encryption process is proposed for data security in this paper. The performance of the proposed system is evaluated in terms of the salient cryptographic metrics, which are the avalanche effect, throughput, and execution time. A comparative analysis with conventional cryptographic algorithms shows that the proposed system outperforms them regarding the cryptographic performance metrics.
{"title":"A Cryptographic Security Mechanism for Dynamic Groups for Public Cloud Environments","authors":"Sheenal Malviya, Sourabh Dave, K. C. Bandhu, R. Litoriya","doi":"10.14313/jamris/2-2022/15","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/15","url":null,"abstract":"Abstract Cloud computing has emerged as a significant technology domain, primarily due to the emergence of big data, machine learning, and quantum computing applications. While earlier, cloud computing services were focused mainly on providing storage and some infrastructures/platforms for applications, the need to advance computational power analysis of massive datasets. It has made cloud computing almost inevitable from most client-based applications, mobile applications, or web applications. The allied challenge to protect data shared from and to cloud-based platforms has cropped up with the necessity to access public clouds. While conventional cryptographic algorithms have been used for securing and authenticating cloud data, advancements in cryptanalysis and access to faster computation have led to possible threats to the traditional security of cloud mechanisms. This has led to extensive research in homomorphic encryption pertaining to cloud security. In this paper, a security mechanism is designed targeted towards dynamic groups using public clouds. Cloud security mechanisms generally face a significant challenge in terms of overhead, throughput, and execution time to encrypt data from dynamic groups with frequent member addition and removal. A two-stage homomorphic encryption process is proposed for data security in this paper. The performance of the proposed system is evaluated in terms of the salient cryptographic metrics, which are the avalanche effect, throughput, and execution time. A comparative analysis with conventional cryptographic algorithms shows that the proposed system outperforms them regarding the cryptographic performance metrics.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"49 1","pages":"46 - 54"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89223360","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 : 2022-05-01DOI: 10.14313/jamris/2-2022/10
Paweł Łupkowski, Olga Danilewicz, Dawid Ratajczyk, A. Wasielewska
Abstract We present the results of an exploratory analysis of human attitudes toward the social robot Vector. The study was conducted on natural language data (2,635 comments) retrieved from Reddit and YouTube. We describe the tag-set used and the (manual) annotation procedure. We present and compare attitude structures mined from Reddit and YouTube data. Two main findings are described and discussed: almost 20% of comments from both Reddit and YouTube consist of various manifestations of attitudes toward Vector (mainly attribution of autonomy and declaration of feelings toward Vector); Reddit and YouTube comments differ when it comes to revealed attitude structure – the data source matters for attitudes studies.
{"title":"‘It is Really Interesting How that Small Robot Impacts Humans.’ The Exploratory Analysis of Human Attitudes Toward the Social Robot Vector in Reddit and Youtube Comments","authors":"Paweł Łupkowski, Olga Danilewicz, Dawid Ratajczyk, A. Wasielewska","doi":"10.14313/jamris/2-2022/10","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/10","url":null,"abstract":"Abstract We present the results of an exploratory analysis of human attitudes toward the social robot Vector. The study was conducted on natural language data (2,635 comments) retrieved from Reddit and YouTube. We describe the tag-set used and the (manual) annotation procedure. We present and compare attitude structures mined from Reddit and YouTube data. Two main findings are described and discussed: almost 20% of comments from both Reddit and YouTube consist of various manifestations of attitudes toward Vector (mainly attribution of autonomy and declaration of feelings toward Vector); Reddit and YouTube comments differ when it comes to revealed attitude structure – the data source matters for attitudes studies.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"8 1","pages":"3 - 10"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83044045","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 : 2022-05-01DOI: 10.14313/jamris/2-2022/13
R. Szczepanowski, Tomasz Niemiec, E. Cichoń, K. Arent, Marcin Florkowski, Janusz Sobecki
Abstract The rapid development of robotics involves human-robot interaction (HRI). It is a necessary to assess user satisfaction to develop HRI effectively. Thus, HRI calls for interdisciplinary research, including psychological instruments such as survey questionnaire design. Here, we present a factor analysis of a Polish version of the Godspeed Questionnaire (GSQ) used to measure user satisfaction. The questionnaire was administered to 195 participants. Then, factor analysis of the GSQ was performed. Finally, reliability analysis of the Polish version of the GSQ was done. The adapted version of the survey was characterized by a four-factor structure, i.e., anthropomorphism, perceived intelligence, likeability, and perceived safety, with good psychometric properties.
{"title":"Factor Analysis of the Polish Version of Godspeed Questionnaire (GQS)","authors":"R. Szczepanowski, Tomasz Niemiec, E. Cichoń, K. Arent, Marcin Florkowski, Janusz Sobecki","doi":"10.14313/jamris/2-2022/13","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/13","url":null,"abstract":"Abstract The rapid development of robotics involves human-robot interaction (HRI). It is a necessary to assess user satisfaction to develop HRI effectively. Thus, HRI calls for interdisciplinary research, including psychological instruments such as survey questionnaire design. Here, we present a factor analysis of a Polish version of the Godspeed Questionnaire (GSQ) used to measure user satisfaction. The questionnaire was administered to 195 participants. Then, factor analysis of the GSQ was performed. Finally, reliability analysis of the Polish version of the GSQ was done. The adapted version of the survey was characterized by a four-factor structure, i.e., anthropomorphism, perceived intelligence, likeability, and perceived safety, with good psychometric properties.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"28 1","pages":"30 - 35"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83491292","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 : 2022-05-01DOI: 10.14313/jamris/2-2022/16
Sławomir Pietrzykowski, Artur Wymysłowski
Abstract This paper presents a method for automatically measuring plants’ heights in indoor hydroponic plantations using the OpenCV library and the Python programming language. Using the elaborated algorithm and Raspberry Pi-driven system with an external camera, the growth process of multiple pak choi cabbages (Brassica rapa L. subsp. Chinensis) was observed. The main aim and novelty of the presented research is the elaborated algorithm, which allows for observing the plants’ height in hydroponic stations, where reflective foil is used. Based on the pictures of the hydroponic plantation, the bases of the plants, their reflections, and plants themselves were separated. Finally, the algorithm was used for estimating the plants’ heights. The achieved results were then compared to the results obtained manually. With the help of a ML (Machine Learning) approach, the algorithm will be used in future research to optimize the plants’ growth in indoor hydroponic plantations.
{"title":"Application of the OpenCV library in indoor hydroponic plantations for automatic height assessment of plants","authors":"Sławomir Pietrzykowski, Artur Wymysłowski","doi":"10.14313/jamris/2-2022/16","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/16","url":null,"abstract":"Abstract This paper presents a method for automatically measuring plants’ heights in indoor hydroponic plantations using the OpenCV library and the Python programming language. Using the elaborated algorithm and Raspberry Pi-driven system with an external camera, the growth process of multiple pak choi cabbages (Brassica rapa L. subsp. Chinensis) was observed. The main aim and novelty of the presented research is the elaborated algorithm, which allows for observing the plants’ height in hydroponic stations, where reflective foil is used. Based on the pictures of the hydroponic plantation, the bases of the plants, their reflections, and plants themselves were separated. Finally, the algorithm was used for estimating the plants’ heights. The achieved results were then compared to the results obtained manually. With the help of a ML (Machine Learning) approach, the algorithm will be used in future research to optimize the plants’ growth in indoor hydroponic plantations.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"32 1","pages":"55 - 63"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87938270","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 : 2022-05-01DOI: 10.14313/jamris/2-2022/12
H. Suhaimi, N. Aziz, E. N. Mior Ibrahim, W. A. R. Wan Mohd Isa
Abstract In alignment with smart city initiatives, Malaysia is shifting its educational landscape to a smart learning environment. The Ministry of Education (MoE) has made History a mandatory subject for passing the Malaysian Certificate of Education to grow awareness and instil patriotism among Malaysian students. However, History has been known as one of the difficult subjects to study for many students. On the other hand, the Malaysian Government Education Blueprint 2013-2025 seeks to “leverage ICT scale up quality learning” across the country. Therefore, this study aims to identify the factors that influence the intention to use Augmented Reality (AR) for mobile learning in learning History subject among secondary school students in Malaysia. Quantitative approach has been chosen as the research method for this study. A direct survey was conducted on 400 secondary school students in one of the smart cities in Malaysia as the target respondents. The collected data are analysed through descriptive statistics and Multiple Linear Regression analysis by using Statistical Package for the Social Sciences. Based on the results, the identified factors that influence the intention to use AR for mobile learning in learning History subject are Gender, Perceived Usefulness, Perceived Enjoyment, and Attitude Towards Use. The identified factors can be a good reference for schools and teachers to strategize their teaching and learning methods in pertaining to History subject among secondary school students in Malaysia. Future studies may include the study of various types of schools in Malaysia and explore more moderating effects of demographic factors.
{"title":"Technology Acceptance in Learning History Subject Using Augmented Reality Towards Smart Mobile Learning Environment: Case in Malaysia","authors":"H. Suhaimi, N. Aziz, E. N. Mior Ibrahim, W. A. R. Wan Mohd Isa","doi":"10.14313/jamris/2-2022/12","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/12","url":null,"abstract":"Abstract In alignment with smart city initiatives, Malaysia is shifting its educational landscape to a smart learning environment. The Ministry of Education (MoE) has made History a mandatory subject for passing the Malaysian Certificate of Education to grow awareness and instil patriotism among Malaysian students. However, History has been known as one of the difficult subjects to study for many students. On the other hand, the Malaysian Government Education Blueprint 2013-2025 seeks to “leverage ICT scale up quality learning” across the country. Therefore, this study aims to identify the factors that influence the intention to use Augmented Reality (AR) for mobile learning in learning History subject among secondary school students in Malaysia. Quantitative approach has been chosen as the research method for this study. A direct survey was conducted on 400 secondary school students in one of the smart cities in Malaysia as the target respondents. The collected data are analysed through descriptive statistics and Multiple Linear Regression analysis by using Statistical Package for the Social Sciences. Based on the results, the identified factors that influence the intention to use AR for mobile learning in learning History subject are Gender, Perceived Usefulness, Perceived Enjoyment, and Attitude Towards Use. The identified factors can be a good reference for schools and teachers to strategize their teaching and learning methods in pertaining to History subject among secondary school students in Malaysia. Future studies may include the study of various types of schools in Malaysia and explore more moderating effects of demographic factors.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"19 1","pages":"20 - 29"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88325307","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}
Abstract The number of automobiles on the road grows in lockstep with the advancement of vehicle manufacturing. Road accidents appear to be on the rise, owing to this growing proliferation of vehicles. Accidents frequently occur in our daily lives, and are the top ten causes of mortality from injuries globally. It is now an important component of the worldwide public health burden. Every year, an estimated 1.2 million people are killed in car accidents. Driver drowsiness and weariness are major contributors to traffic accidents this study relies on computer software and photographs, as well as a Convolutional Neural Network (CNN), to assess whether a motorist is tired. The Driver Drowsiness System is built on the Multi-Layer Feed-Forward Network concept CNN was created using around 7,000 photos of eyes in both sleepiness and non-drowsiness phases with various face layouts. These photos were divided into two datasets: training (80% of the images) and testing (20% of the images). For training purposes, the pictures in the training dataset are fed into the network. To decrease information loss as much as feasible, backpropagation techniques and optimizers are applied. We developed an algorithm to calculate ROI as well as track and evaluate motor and visual impacts.
{"title":"Machine Learning and Artificial Intelligence Techniques for Detecting Driver Drowsiness","authors":"Prathap Rudra Boppuru, Pradeep Kumar Kukatlapalli, Cherukuri Ravindranath Chowdary","doi":"10.14313/jamris/2-2022/17","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/17","url":null,"abstract":"Abstract The number of automobiles on the road grows in lockstep with the advancement of vehicle manufacturing. Road accidents appear to be on the rise, owing to this growing proliferation of vehicles. Accidents frequently occur in our daily lives, and are the top ten causes of mortality from injuries globally. It is now an important component of the worldwide public health burden. Every year, an estimated 1.2 million people are killed in car accidents. Driver drowsiness and weariness are major contributors to traffic accidents this study relies on computer software and photographs, as well as a Convolutional Neural Network (CNN), to assess whether a motorist is tired. The Driver Drowsiness System is built on the Multi-Layer Feed-Forward Network concept CNN was created using around 7,000 photos of eyes in both sleepiness and non-drowsiness phases with various face layouts. These photos were divided into two datasets: training (80% of the images) and testing (20% of the images). For training purposes, the pictures in the training dataset are fed into the network. To decrease information loss as much as feasible, backpropagation techniques and optimizers are applied. We developed an algorithm to calculate ROI as well as track and evaluate motor and visual impacts.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"5 1","pages":"64 - 73"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75516354","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 : 2022-05-01DOI: 10.14313/jamris/2-2022/11
S. Khanmohammadi, M. Samadi
Abstract The application of quadcopter and intelligent learning techniques in urban monitoring systems can improve flexibility and efficiency features. This paper proposes a cloud-based urban monitoring system that uses deep learning, fuzzy system, image processing, pattern recognition, and Bayesian network. The main objectives of this system are to monitor climate status, temperature, humidity, and smoke, as well as to detect fire occur-rences based on the above intelligent techniques. The quadcopter transmits sensing data of the temperature, humidity, and smoke sensors, geographical coordinates, image frames, and videos to a control station via RF communications. In the control station side, the monitoring capabilities are designed by graphical tools to show urban areas with RGB colors according to the predetermined data ranges. The evaluation process illustrates simulation results of the deep neural network applied to climate status and effects of the sensors’ data changes on climate status. An illustrative example is used to draw the simulated area using RGB colors. Furthermore, circuit of the quadcopter side is designed using electric devices.
{"title":"A Cloud-Based Urban Monitoring System by Using a Quadcopter and Intelligent Learning Techniques","authors":"S. Khanmohammadi, M. Samadi","doi":"10.14313/jamris/2-2022/11","DOIUrl":"https://doi.org/10.14313/jamris/2-2022/11","url":null,"abstract":"Abstract The application of quadcopter and intelligent learning techniques in urban monitoring systems can improve flexibility and efficiency features. This paper proposes a cloud-based urban monitoring system that uses deep learning, fuzzy system, image processing, pattern recognition, and Bayesian network. The main objectives of this system are to monitor climate status, temperature, humidity, and smoke, as well as to detect fire occur-rences based on the above intelligent techniques. The quadcopter transmits sensing data of the temperature, humidity, and smoke sensors, geographical coordinates, image frames, and videos to a control station via RF communications. In the control station side, the monitoring capabilities are designed by graphical tools to show urban areas with RGB colors according to the predetermined data ranges. The evaluation process illustrates simulation results of the deep neural network applied to climate status and effects of the sensors’ data changes on climate status. An illustrative example is used to draw the simulated area using RGB colors. Furthermore, circuit of the quadcopter side is designed using electric devices.","PeriodicalId":37910,"journal":{"name":"Journal of Automation, Mobile Robotics and Intelligent Systems","volume":"35 1","pages":"11 - 19"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81365866","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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