Pub Date : 2022-05-11DOI: 10.1080/24751839.2022.2062918
A. Psathas, Andonis Papaleonidas, L. Iliadis, G. Papathanassiou, S. Valkaniotis
ABSTRACT Timely and rational prediction of coseismic landslides is crucial for the design and development of key infrastructure capable to protect human lives in seismically active regions. This research introduces the novel Hybrid Coseismic Landslide Forecasting model (COLAFOS) that takes into consideration three parameters namely: The Average Slope of the Active Areas, the Slope Aspect and the types of Geological forms. The developed model was tested on two datasets from the island of Lefkada Greece, for years 2003 and 2015. COLAFOS is a hybrid model, employing the Fuzzy c-Means clustering, the Ensemble Adaptive Boosting (ENS_AdaBoost) and the Ensemble Subspace k-Nearest Neighbour (ENSUB k-NN) algorithms. The introduced model managed to correctly classify the coseismic landslides according to their severity, with a success rate of 70.07% and 72.88% for 2003 and 2015, respectively. The algorithm has shown very good performance for the classes of major severity, reaching an accuracy up to 92%. Accuracy, Sensitivity, Specificity, Precision and F-1 Score, were used to evaluate the performance of the model. Given the fact that this is a multi-class classification problem, ‘One Versus All’ Strategy was used in the evaluation process. Although the datasets were relatively unbalanced, the evaluation indices sealed the efficiency of the model.
{"title":"COLAFOS: a hybrid machine learning model to forecast potential coseismic landslides severity","authors":"A. Psathas, Andonis Papaleonidas, L. Iliadis, G. Papathanassiou, S. Valkaniotis","doi":"10.1080/24751839.2022.2062918","DOIUrl":"https://doi.org/10.1080/24751839.2022.2062918","url":null,"abstract":"ABSTRACT Timely and rational prediction of coseismic landslides is crucial for the design and development of key infrastructure capable to protect human lives in seismically active regions. This research introduces the novel Hybrid Coseismic Landslide Forecasting model (COLAFOS) that takes into consideration three parameters namely: The Average Slope of the Active Areas, the Slope Aspect and the types of Geological forms. The developed model was tested on two datasets from the island of Lefkada Greece, for years 2003 and 2015. COLAFOS is a hybrid model, employing the Fuzzy c-Means clustering, the Ensemble Adaptive Boosting (ENS_AdaBoost) and the Ensemble Subspace k-Nearest Neighbour (ENSUB k-NN) algorithms. The introduced model managed to correctly classify the coseismic landslides according to their severity, with a success rate of 70.07% and 72.88% for 2003 and 2015, respectively. The algorithm has shown very good performance for the classes of major severity, reaching an accuracy up to 92%. Accuracy, Sensitivity, Specificity, Precision and F-1 Score, were used to evaluate the performance of the model. Given the fact that this is a multi-class classification problem, ‘One Versus All’ Strategy was used in the evaluation process. Although the datasets were relatively unbalanced, the evaluation indices sealed the efficiency of the model.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"420 - 449"},"PeriodicalIF":2.7,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45356686","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 : 2022-05-11DOI: 10.1080/24751839.2022.2065765
Mihailo Ilic, M. Ivanović
ABSTRACT This paper highlights the use of software agents and simulating real-world medical phenomena. We start with a brief overview of different approaches and tools for developing software agents and running simulations. One of the more recent tools was utilized in this paper to develop a model of disease spread in a population of agents and for performing experiments. We proposed an extension of the SIRD model, which includes a new state for agents, spatial component, and also different risk groups based on age. Multiple factors affect the longevity of a pathogen in a given population, for instance, its infectivity and deadliness. This paper shows interesting results of extensive experiments performed with novel, modified SIRD model and impact of key factors on disease spread.
{"title":"Spatial SIRD model with different risk groups – multiagent approach for modelling an epidemic","authors":"Mihailo Ilic, M. Ivanović","doi":"10.1080/24751839.2022.2065765","DOIUrl":"https://doi.org/10.1080/24751839.2022.2065765","url":null,"abstract":"ABSTRACT This paper highlights the use of software agents and simulating real-world medical phenomena. We start with a brief overview of different approaches and tools for developing software agents and running simulations. One of the more recent tools was utilized in this paper to develop a model of disease spread in a population of agents and for performing experiments. We proposed an extension of the SIRD model, which includes a new state for agents, spatial component, and also different risk groups based on age. Multiple factors affect the longevity of a pathogen in a given population, for instance, its infectivity and deadliness. This paper shows interesting results of extensive experiments performed with novel, modified SIRD model and impact of key factors on disease spread.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"450 - 464"},"PeriodicalIF":2.7,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47442878","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 In traditional learning, learners and their lecturers, or tutors can meet face-to-face. In such lectures, the lecturers, or tutors can introduce printed book tutorials. However, in several circumstances, such as distance education, learners cannot interact with their teachers. Therefore, online learning resources would be helpful for learners to get knowledge. With a large and diverse number of learning resources, selecting appropriate learning resources to learn is very important. This study presents a deep matrix decomposition model extended from standard matrix decomposition to recommend learning resources based on learners' abilities and requirements. We test the proposed model on two groups of experimental data, including the data group of students' learning outcomes at a university for course recommendation and another group of 5 datasets of user learning resources to provide valuable recommendations for supporting learners. The experiments have revealed promising results compared to some baselines. The work is expected to be a good choice for large-scale datasets.
{"title":"An approach for learning resource recommendation using deep matrix factorization","authors":"Tran Thanh Dien, Nguyen Thanh Hai, Nguyen Thai-Nghe","doi":"10.1080/24751839.2022.2058250","DOIUrl":"https://doi.org/10.1080/24751839.2022.2058250","url":null,"abstract":"ABSTRACT In traditional learning, learners and their lecturers, or tutors can meet face-to-face. In such lectures, the lecturers, or tutors can introduce printed book tutorials. However, in several circumstances, such as distance education, learners cannot interact with their teachers. Therefore, online learning resources would be helpful for learners to get knowledge. With a large and diverse number of learning resources, selecting appropriate learning resources to learn is very important. This study presents a deep matrix decomposition model extended from standard matrix decomposition to recommend learning resources based on learners' abilities and requirements. We test the proposed model on two groups of experimental data, including the data group of students' learning outcomes at a university for course recommendation and another group of 5 datasets of user learning resources to provide valuable recommendations for supporting learners. The experiments have revealed promising results compared to some baselines. The work is expected to be a good choice for large-scale datasets.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"381 - 398"},"PeriodicalIF":2.7,"publicationDate":"2022-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42710847","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 : 2022-04-05DOI: 10.1080/24751839.2022.2058252
J. Bernacki, R. Scherer
ABSTRACT We consider the identification of imaging devices by analysing images they produce. The problem is studied in the literature, yet the existing solutions are rather computationally demanding. We propose a high-speed algorithm for the identification of imaging devices. The aim is to provide additional security by identification of legitimate imaging devices or an identification for forensics. The experimental evaluation confirms efficient identification of devices models and brands by the proposed algorithm, compared with the state-of-the-art method. Moreover, our algorithm is approximately two orders of magnitude faster, which is very important in resource-constrained IoT ecosystems or very large databases.
{"title":"Digital forensics: a fast algorithm for a digital sensor identification","authors":"J. Bernacki, R. Scherer","doi":"10.1080/24751839.2022.2058252","DOIUrl":"https://doi.org/10.1080/24751839.2022.2058252","url":null,"abstract":"ABSTRACT We consider the identification of imaging devices by analysing images they produce. The problem is studied in the literature, yet the existing solutions are rather computationally demanding. We propose a high-speed algorithm for the identification of imaging devices. The aim is to provide additional security by identification of legitimate imaging devices or an identification for forensics. The experimental evaluation confirms efficient identification of devices models and brands by the proposed algorithm, compared with the state-of-the-art method. Moreover, our algorithm is approximately two orders of magnitude faster, which is very important in resource-constrained IoT ecosystems or very large databases.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"399 - 419"},"PeriodicalIF":2.7,"publicationDate":"2022-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44523728","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 : 2022-03-22DOI: 10.1080/24751839.2022.2047470
Tsutomu Kumazawa, M. Takimoto, Y. Kambayashi
ABSTRACT Model checking is a formal and automated verification technique to show that a software system behaves in accordance with the given specification. Traditional model checking uses exhaustive search techniques for finding violative behaviours of the specification. The techniques, however, often do not work for huge systems because it demands a huge amount of computational resources. Search-Based Software Engineering is known to effectively solve many software engineering problems including model checking. It pursues the good balance between efficiency and qualities of solutions by using swarm intelligence and metaheuristic search methodologies. This article focuses on the state-of-the-art model checking with Ant Colony Optimization. Ant Colony Optimization is a metaheuristic, population-based and stochastic optimization algorithm. We propose two exploration strategies to further improve the balance in model checking based on Ant Colony Optimization. The proposed strategies introduce different kinds of randomized selection mechanisms to diversify solutions found by many agents. The strategies help the search algorithm extend the reachable regions effectively. Through numerical experiments, we confirmed that the proposed strategies require less computation time and memory as compared to the existing model checking with Ant Colony Optimization at the cost of finding slightly less qualified solutions.
{"title":"Exploration strategies for balancing efficiency and comprehensibility in model checking with ant colony optimization","authors":"Tsutomu Kumazawa, M. Takimoto, Y. Kambayashi","doi":"10.1080/24751839.2022.2047470","DOIUrl":"https://doi.org/10.1080/24751839.2022.2047470","url":null,"abstract":"ABSTRACT Model checking is a formal and automated verification technique to show that a software system behaves in accordance with the given specification. Traditional model checking uses exhaustive search techniques for finding violative behaviours of the specification. The techniques, however, often do not work for huge systems because it demands a huge amount of computational resources. Search-Based Software Engineering is known to effectively solve many software engineering problems including model checking. It pursues the good balance between efficiency and qualities of solutions by using swarm intelligence and metaheuristic search methodologies. This article focuses on the state-of-the-art model checking with Ant Colony Optimization. Ant Colony Optimization is a metaheuristic, population-based and stochastic optimization algorithm. We propose two exploration strategies to further improve the balance in model checking based on Ant Colony Optimization. The proposed strategies introduce different kinds of randomized selection mechanisms to diversify solutions found by many agents. The strategies help the search algorithm extend the reachable regions effectively. Through numerical experiments, we confirmed that the proposed strategies require less computation time and memory as compared to the existing model checking with Ant Colony Optimization at the cost of finding slightly less qualified solutions.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"341 - 359"},"PeriodicalIF":2.7,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42521513","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 : 2022-03-06DOI: 10.1080/24751839.2022.2040898
N. Jyothi, Rekha Patil
ABSTRACT The Vehicular Adhoc Network (VANET) is a newly added smart technique in vehicles to ensure safety and reduce time consumption. Even though it saves time and guarantees safe travel, security and privacy are the most difficult issues in the VANET. Moreover, this is due to the fact that the methods exploit public key infrastructure, group signature, etc., Meanwhile, the hackers can acquire the sensitive data’s which are usually kept in the tamper-proof devices by using side-channel attacks. The VANET also possesses several security-related issues. To circumvent this we propose an efficient privacy-preserving and fuzzy-based trust evaluation scheme. This method ensures the security and authenticity of the VANET. To ensure security our proposed method utilizes a modified Elliptical Curve cryptographic (ECC) method which also reduces the computational complexities created by the conventional ECC. In our proposed method the TPD parameters are renewed more often to eliminate the attacks and permits batch verification methods to reduce the time. The experimental analysis is conducted in Matlab simulator in terms of computational cost, communication cost, evaluation of trustworthiness, privacy protection. The experimental analysis shows that proposed method provides 94% of trustworthiness and time consumption and communication overheads are reduced to greater extent.
{"title":"A fuzzy-based trust evaluation framework for efficient privacy preservation and secure authentication in VANET","authors":"N. Jyothi, Rekha Patil","doi":"10.1080/24751839.2022.2040898","DOIUrl":"https://doi.org/10.1080/24751839.2022.2040898","url":null,"abstract":"ABSTRACT The Vehicular Adhoc Network (VANET) is a newly added smart technique in vehicles to ensure safety and reduce time consumption. Even though it saves time and guarantees safe travel, security and privacy are the most difficult issues in the VANET. Moreover, this is due to the fact that the methods exploit public key infrastructure, group signature, etc., Meanwhile, the hackers can acquire the sensitive data’s which are usually kept in the tamper-proof devices by using side-channel attacks. The VANET also possesses several security-related issues. To circumvent this we propose an efficient privacy-preserving and fuzzy-based trust evaluation scheme. This method ensures the security and authenticity of the VANET. To ensure security our proposed method utilizes a modified Elliptical Curve cryptographic (ECC) method which also reduces the computational complexities created by the conventional ECC. In our proposed method the TPD parameters are renewed more often to eliminate the attacks and permits batch verification methods to reduce the time. The experimental analysis is conducted in Matlab simulator in terms of computational cost, communication cost, evaluation of trustworthiness, privacy protection. The experimental analysis shows that proposed method provides 94% of trustworthiness and time consumption and communication overheads are reduced to greater extent.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"270 - 288"},"PeriodicalIF":2.7,"publicationDate":"2022-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46844822","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 : 2022-01-02DOI: 10.1080/24751839.2021.1989242
P. Koprinkova-Hristova, M. Ivanović, B. Diri
Intelligent Systems can be thought of as a concept with a very broad scope. They can have hardware from small microprocessors to large processors, micro-mechanics to macromechanics. Intelligent Systems can have software from low-level simple codes to much more complex codes, can be connected locally or via Internet or can work offline independently. They can be operated or managed remotely or can be autonomous and able to act as a rule-based system or as a learning capable Artificial Intelligence system. We can see ‘Intelligent Systems’ in every area that comes to mind such as Robotics, Finance, Industry, Space technologies, Education, Home Appliances, Health, Communication, Security, Military, Aviation, Energy, and so on. The 14th International Conference on Innovations in Intelligent Systems and Applications (INISTA 2020) took place during the period between 24 August and 26 August 2020 as an online event, organized by the University of Novi Sad, Serbia. Previously, INISTA had been hosted at Sofia, Bulgaria (2019), Thessaloniki, Greece (2018), Gdynia, Poland (2017), Sinaia, Romania (2016), Madrid, Spain (2015), Alberobello, Italy (2014), Albena, Bulgaria (2013), Trabzon, Turkey (2012), Istanbul, Turkey (2011), Kayseri, Turkey (2010), Trabzon, Turkey (2009), Istanbul, Turkey (2007), and Istanbul, Turkey (2005). Authors had been invited to submit high-quality, original research papers on the range of topics including, but not limited to, the following:
{"title":"Special issue: Innovations in Intelligent Systems and Applications","authors":"P. Koprinkova-Hristova, M. Ivanović, B. Diri","doi":"10.1080/24751839.2021.1989242","DOIUrl":"https://doi.org/10.1080/24751839.2021.1989242","url":null,"abstract":"Intelligent Systems can be thought of as a concept with a very broad scope. They can have hardware from small microprocessors to large processors, micro-mechanics to macromechanics. Intelligent Systems can have software from low-level simple codes to much more complex codes, can be connected locally or via Internet or can work offline independently. They can be operated or managed remotely or can be autonomous and able to act as a rule-based system or as a learning capable Artificial Intelligence system. We can see ‘Intelligent Systems’ in every area that comes to mind such as Robotics, Finance, Industry, Space technologies, Education, Home Appliances, Health, Communication, Security, Military, Aviation, Energy, and so on. The 14th International Conference on Innovations in Intelligent Systems and Applications (INISTA 2020) took place during the period between 24 August and 26 August 2020 as an online event, organized by the University of Novi Sad, Serbia. Previously, INISTA had been hosted at Sofia, Bulgaria (2019), Thessaloniki, Greece (2018), Gdynia, Poland (2017), Sinaia, Romania (2016), Madrid, Spain (2015), Alberobello, Italy (2014), Albena, Bulgaria (2013), Trabzon, Turkey (2012), Istanbul, Turkey (2011), Kayseri, Turkey (2010), Trabzon, Turkey (2009), Istanbul, Turkey (2007), and Istanbul, Turkey (2005). Authors had been invited to submit high-quality, original research papers on the range of topics including, but not limited to, the following:","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"1 - 5"},"PeriodicalIF":2.7,"publicationDate":"2022-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47567926","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 : 2022-01-01DOI: 10.1080/24751839.2022.2051925
G. Bocewicz, Peter Nielsen, Czeslaw Smutnicki, J. Pempera, Z. Banaszak
{"title":"Periodic distributed delivery routes planning subject to operation uncertainty of vehicles travelling in a convoy","authors":"G. Bocewicz, Peter Nielsen, Czeslaw Smutnicki, J. Pempera, Z. Banaszak","doi":"10.1080/24751839.2022.2051925","DOIUrl":"https://doi.org/10.1080/24751839.2022.2051925","url":null,"abstract":"","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"360-380"},"PeriodicalIF":2.7,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"60140885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-02DOI: 10.1080/24751839.2021.2008133
V. Nguyen, Son Thanh Le, Minh Khai Tran, Ha Manh Tran
ABSTRACT Constructing the 3D objects based on geometric modelling and graphical techniques is a well-known research activity applied in computer graphics. Techniques to process graphical models are widely used in the field of digital heritage and 3D game. Virtual reality (VR) and Augmented Reality (AR) are technical trends nowadays that can be studied and used in digital high-tech fields like medical training, digital heritage, entertainment industry, digital tourism and museum, etc. In this research, we present a new proposed method for reconstructing the 3D objects of tangible cultural heritages in the virtual environment based on the combination of geometric modelling, computer graphics, VR and AR technologies. The method consists of the following steps: we first collect data of a real object by using a 3D scanner. After processing obtained data, the output is a 3D point cloud. In the next step, we remove noisy data and triangulate the object surface. The novelty point focuses on reconstructing the 3D object by filling the holes. At the end, we build VR and AR applications for visualizing a virtual museum. The contribution of this research leads to open the door for applying in other fields such as 3D Game industry or digital tourism.
{"title":"Reconstruction of 3D digital heritage objects for VR and AR applications","authors":"V. Nguyen, Son Thanh Le, Minh Khai Tran, Ha Manh Tran","doi":"10.1080/24751839.2021.2008133","DOIUrl":"https://doi.org/10.1080/24751839.2021.2008133","url":null,"abstract":"ABSTRACT Constructing the 3D objects based on geometric modelling and graphical techniques is a well-known research activity applied in computer graphics. Techniques to process graphical models are widely used in the field of digital heritage and 3D game. Virtual reality (VR) and Augmented Reality (AR) are technical trends nowadays that can be studied and used in digital high-tech fields like medical training, digital heritage, entertainment industry, digital tourism and museum, etc. In this research, we present a new proposed method for reconstructing the 3D objects of tangible cultural heritages in the virtual environment based on the combination of geometric modelling, computer graphics, VR and AR technologies. The method consists of the following steps: we first collect data of a real object by using a 3D scanner. After processing obtained data, the output is a 3D point cloud. In the next step, we remove noisy data and triangulate the object surface. The novelty point focuses on reconstructing the 3D object by filling the holes. At the end, we build VR and AR applications for visualizing a virtual museum. The contribution of this research leads to open the door for applying in other fields such as 3D Game industry or digital tourism.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"254 - 269"},"PeriodicalIF":2.7,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46190644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-11-10DOI: 10.1080/24751839.2021.1987706
Andonis Papaleonidas, A. Psathas, L. Iliadis
ABSTRACT Human activity recognition (HAR) is vital in a wide range of real-life applications such as health monitoring of olderly people, abnormal behaviour detection and smart home management. HAR systems can employ smart human-computer interfaces and be parts of active, intelligent surveillance systems. The increasing use of high-tech mobile and wearable devices, such as smart phones, smart watches and smart bands, can be the key elements in building high accuracy models, as they can provide a tremendous number of signals. This research aims to develop and test a machine learning (ML) model, which can successfully recognize a performed activity using raw signals obtained by wearable devices. Photoplethysmography – Daily Life Activities (PPG-DaLiA) dataset contains data related to 15 individuals wearing physiological and motion sensors. PPG-DaLiA was used as an input to a custom data segmentation model to obtain the respective training and testing dataset. Overall, 23 ML well-established models were employed. The weighted and the fine k-nearest neighbours, the fine Gaussian support vector machines and the bagged trees were the algorithms that achieved the best performance with a very high accuracy level.
{"title":"High accuracy human activity recognition using machine learning and wearable devices’ raw signals","authors":"Andonis Papaleonidas, A. Psathas, L. Iliadis","doi":"10.1080/24751839.2021.1987706","DOIUrl":"https://doi.org/10.1080/24751839.2021.1987706","url":null,"abstract":"ABSTRACT Human activity recognition (HAR) is vital in a wide range of real-life applications such as health monitoring of olderly people, abnormal behaviour detection and smart home management. HAR systems can employ smart human-computer interfaces and be parts of active, intelligent surveillance systems. The increasing use of high-tech mobile and wearable devices, such as smart phones, smart watches and smart bands, can be the key elements in building high accuracy models, as they can provide a tremendous number of signals. This research aims to develop and test a machine learning (ML) model, which can successfully recognize a performed activity using raw signals obtained by wearable devices. Photoplethysmography – Daily Life Activities (PPG-DaLiA) dataset contains data related to 15 individuals wearing physiological and motion sensors. PPG-DaLiA was used as an input to a custom data segmentation model to obtain the respective training and testing dataset. Overall, 23 ML well-established models were employed. The weighted and the fine k-nearest neighbours, the fine Gaussian support vector machines and the bagged trees were the algorithms that achieved the best performance with a very high accuracy level.","PeriodicalId":32180,"journal":{"name":"Journal of Information and Telecommunication","volume":"6 1","pages":"237 - 253"},"PeriodicalIF":2.7,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43419397","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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