Pub Date : 2020-02-01DOI: 10.1109/AECT47998.2020.9194150
Hisham Khalil, M. M. Ahmed, U. Rafique, Reham Almesaeed, Waseem Nazar
In this paper, the optimum placement of a conformal antenna array based on the path loss profile has been discussed. The arrays are considered to be conformed on the wings and cylindrical fuselage of an Unmanned Aerial Vehicles (UAVs). Two types of feeding designs have been presented: Rectangular Waveguide (RWG) for fuselage conformal antenna array and Substrate Integrated Waveguide for wing conformal antenna array. The optimum placement of conformal arrays proposed on the basis of path loss profile for the air-to-air link (AA) and air-to-ground link (AG). The proposed arrays have been designed and simulated in Ansys HFSS and it has been observed that the proposed arrays offer gains of 11.15 dBi and 9.8 dBi for wing and fuselage, respectively.
{"title":"Optimum Placement of Conformal Antenna Array Based on Path Loss Profile","authors":"Hisham Khalil, M. M. Ahmed, U. Rafique, Reham Almesaeed, Waseem Nazar","doi":"10.1109/AECT47998.2020.9194150","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194150","url":null,"abstract":"In this paper, the optimum placement of a conformal antenna array based on the path loss profile has been discussed. The arrays are considered to be conformed on the wings and cylindrical fuselage of an Unmanned Aerial Vehicles (UAVs). Two types of feeding designs have been presented: Rectangular Waveguide (RWG) for fuselage conformal antenna array and Substrate Integrated Waveguide for wing conformal antenna array. The optimum placement of conformal arrays proposed on the basis of path loss profile for the air-to-air link (AA) and air-to-ground link (AG). The proposed arrays have been designed and simulated in Ansys HFSS and it has been observed that the proposed arrays offer gains of 11.15 dBi and 9.8 dBi for wing and fuselage, respectively.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134196565","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194191
Aries Subiantoro, Muhammad Hadi, A. Muis
This paper deals with the design of distributed linear parameter varying model predictive controller (LPVMPC) to solve consensus problem on nonholomonic model with event-triggered mechanism. The nonlinear dynamic of nonholomonic model is simplified into linear time variant model by discretizing with Euler method. A quadratic cost function is determined by including terminal state and varying weight matrices, in order to reduce offset due to modeling simplification. The control signal for very agents are calculated by solving quadratic programming problem. A local optimal state controller is integrated with LPV-MPC during eventtriggered mechanism. In order to reduce computational load, the predictive controller only performs optimization only when the trigger conditions are met. The proposed controller is also verified in case of numerical simulation test, and shown its capability to provide good response of nonholomonic mobile robot’s consensus protocol.
{"title":"Distributed Linear Parameter Varying Model Predictive Controller with Event-Triggered Mechanism for Nonholonomic Mobile Robot","authors":"Aries Subiantoro, Muhammad Hadi, A. Muis","doi":"10.1109/AECT47998.2020.9194191","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194191","url":null,"abstract":"This paper deals with the design of distributed linear parameter varying model predictive controller (LPVMPC) to solve consensus problem on nonholomonic model with event-triggered mechanism. The nonlinear dynamic of nonholomonic model is simplified into linear time variant model by discretizing with Euler method. A quadratic cost function is determined by including terminal state and varying weight matrices, in order to reduce offset due to modeling simplification. The control signal for very agents are calculated by solving quadratic programming problem. A local optimal state controller is integrated with LPV-MPC during eventtriggered mechanism. In order to reduce computational load, the predictive controller only performs optimization only when the trigger conditions are met. The proposed controller is also verified in case of numerical simulation test, and shown its capability to provide good response of nonholomonic mobile robot’s consensus protocol.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117057563","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194192
Waqas Ahmad, Sheeraz Ahmed, Najia Sheeraz, Ayub Khan, A. Ishtiaq, Malka Saba
Vehicular Ad-hoc Networks (VANETs) is the most eminent field nowadays in Intelligent Transportation System. Applications included emergency alerts, positioning, and tracking of vehicles. Vehicle Localization in municipal areas is a major issue for protection applications. Many solutions have been provided including Global Positioning Systems (GPS) but these applications do not provide accuracy. Hence, a novel approach has been proposed here known as Received Signal Strength (RSS) Based Localization which aims to find accurate location of a target vehicle. It provides communication with Road Side Units (RSUs) by receiving signal within its range, and finds the average RSS. After the RSS has been found it is aided to the RSS Based Localization algorithm which finds accurate location of the vehicle. The main factor of proposed algorithm is its high signal to noise ratio which is obtained from the closest RSU. After the location of the vehicle is found, its Cramer Rao Lower Bound is analyzed. All the simulations performed shows that our suggested RSS based Localization are better than others traditional least squares and weighted least squares techniques.
{"title":"Localization Error Computation for RSSI Based Positioning System in VANETs","authors":"Waqas Ahmad, Sheeraz Ahmed, Najia Sheeraz, Ayub Khan, A. Ishtiaq, Malka Saba","doi":"10.1109/AECT47998.2020.9194192","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194192","url":null,"abstract":"Vehicular Ad-hoc Networks (VANETs) is the most eminent field nowadays in Intelligent Transportation System. Applications included emergency alerts, positioning, and tracking of vehicles. Vehicle Localization in municipal areas is a major issue for protection applications. Many solutions have been provided including Global Positioning Systems (GPS) but these applications do not provide accuracy. Hence, a novel approach has been proposed here known as Received Signal Strength (RSS) Based Localization which aims to find accurate location of a target vehicle. It provides communication with Road Side Units (RSUs) by receiving signal within its range, and finds the average RSS. After the RSS has been found it is aided to the RSS Based Localization algorithm which finds accurate location of the vehicle. The main factor of proposed algorithm is its high signal to noise ratio which is obtained from the closest RSU. After the location of the vehicle is found, its Cramer Rao Lower Bound is analyzed. All the simulations performed shows that our suggested RSS based Localization are better than others traditional least squares and weighted least squares techniques.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125997807","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194179
N. Bahbouh, A. Alkhodre, A. A. Sen, Abdallah Namoun, S. Albouq
The importance of modern technology is prevalent in our lives for it helps us achieve our everyday activities and tasks. People with special needs represent a significant segment of the society and always require some sort of assistance to make their lives as normal as possible. Indeed, technological advancements can be exploited to achieve this endeavor. In this research, deaf mothers are guided to detect the needs of their babies by employing the Internet of Things and a mobile application. This research proposes a new algorithm to monitor children during their sleep based on successive periodic snapshots or sound, and when detecting any change in their environment the smart monitoring system alerts the mother by shaking a wearable bracelet or ringing her mobile phone. The proposed system has been implemented and tested and has been proven to be superior to other systems with respect to the implementation cost, accuracy of alerts, flexibility, and energy consumption.
{"title":"A Cost Effective IoT-based System for Monitoring Baby Incidents by Deaf Parents","authors":"N. Bahbouh, A. Alkhodre, A. A. Sen, Abdallah Namoun, S. Albouq","doi":"10.1109/AECT47998.2020.9194179","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194179","url":null,"abstract":"The importance of modern technology is prevalent in our lives for it helps us achieve our everyday activities and tasks. People with special needs represent a significant segment of the society and always require some sort of assistance to make their lives as normal as possible. Indeed, technological advancements can be exploited to achieve this endeavor. In this research, deaf mothers are guided to detect the needs of their babies by employing the Internet of Things and a mobile application. This research proposes a new algorithm to monitor children during their sleep based on successive periodic snapshots or sound, and when detecting any change in their environment the smart monitoring system alerts the mother by shaking a wearable bracelet or ringing her mobile phone. The proposed system has been implemented and tested and has been proven to be superior to other systems with respect to the implementation cost, accuracy of alerts, flexibility, and energy consumption.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132138606","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194177
Rana Nassif, Mohamed Waleed Fahkr
Large amounts of text are collected on the internet every day. As more text documents become available, it becomes essential to categorize them for efficient archiving, retrieval and search. In this paper, we investigate both statistical and machine learning techniques like (HMM & Deep learning network) combined with two well-known word embedding models (word2vec & Glove) for supervised document classification. The investigated combinations are compared with state-of-the-art approaches applied on the same data. The main contribution of this paper is to demonstrate the importance of both the meaning and the order of the word on topic modeling. This has often been overlooked in previous work as neither were taken into consideration where in some others only one was taken. This paper shows that one of our proposed models; which employed a hybrid between LSTM and CNN neural networks, obtained better accuracy on the same dataset than all state-of-the-art models in the literature.
{"title":"Supervised Topic Modeling Using Word Embedding with Machine Learning Techniques","authors":"Rana Nassif, Mohamed Waleed Fahkr","doi":"10.1109/AECT47998.2020.9194177","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194177","url":null,"abstract":"Large amounts of text are collected on the internet every day. As more text documents become available, it becomes essential to categorize them for efficient archiving, retrieval and search. In this paper, we investigate both statistical and machine learning techniques like (HMM & Deep learning network) combined with two well-known word embedding models (word2vec & Glove) for supervised document classification. The investigated combinations are compared with state-of-the-art approaches applied on the same data. The main contribution of this paper is to demonstrate the importance of both the meaning and the order of the word on topic modeling. This has often been overlooked in previous work as neither were taken into consideration where in some others only one was taken. This paper shows that one of our proposed models; which employed a hybrid between LSTM and CNN neural networks, obtained better accuracy on the same dataset than all state-of-the-art models in the literature.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131704716","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194213
Mohammad Ayoub Khan, M. Quasim, F. Algarni, Abdullah Alharthi
The role of the Internet has significantly changed due to the development in communication technologies. Nowadays, billions of people and physical devices are connected via Internet. In near future, storage and computational services will be more pervasive and distributed. Even in recent times, we can see that people, machines, objects, and platforms are connected with wireless or wired sensors. Considering such an internet setting with billions of connected devices, in this paper, we present a study on the background, state-of-the-art, growth, key players, applications, challenges, and future opportunities in the area of Internet of Things (IoT). The Kingdom of Saudi Arabia’s IoT and M2M (Machine to Machine) communication market is estimated to grow to $16.01 billion by 2019 from $4.88 billion in 2014[26]. We also discuss general aspects and issues of IoT and explore the implication of all these in a developing country’s setting taking the case of Saudi Arabia.
{"title":"Internet of Things: On the Opportunities, Applications and Open Challenges in Saudi Arabia","authors":"Mohammad Ayoub Khan, M. Quasim, F. Algarni, Abdullah Alharthi","doi":"10.1109/AECT47998.2020.9194213","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194213","url":null,"abstract":"The role of the Internet has significantly changed due to the development in communication technologies. Nowadays, billions of people and physical devices are connected via Internet. In near future, storage and computational services will be more pervasive and distributed. Even in recent times, we can see that people, machines, objects, and platforms are connected with wireless or wired sensors. Considering such an internet setting with billions of connected devices, in this paper, we present a study on the background, state-of-the-art, growth, key players, applications, challenges, and future opportunities in the area of Internet of Things (IoT). The Kingdom of Saudi Arabia’s IoT and M2M (Machine to Machine) communication market is estimated to grow to $16.01 billion by 2019 from $4.88 billion in 2014[26]. We also discuss general aspects and issues of IoT and explore the implication of all these in a developing country’s setting taking the case of Saudi Arabia.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121331476","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194220
Jawad Ahmad, Ahsen Tahir, J. Khan, Atif Jameel, Q. Abbasi, W. Buchanan
Compressive sensing is a compression technique that can be effectively utilised in multimedia encryption. This paper proposes a new compressive sensing image encryption scheme using the Secure Hash Algorithm (SHA-512), Discrete Cosine Transform (DCT), orthogonal matrix and discrete Chirikov map-based random permutation. DCT is applied on a plaintext image and a block of DCT coefficients is multiplied with an orthogonal matrix. Inverse DCT and scaling are performed to restrict the values between 0 and 255. Furthermore, values are shuffled using Chirikov-based pseudo-random permutation. A strong trade-off exists between DCT block size and computational efficiency. The quality and Signal to Noise Ratio (SNR) of the decrypted image decreases when the size of the DCT matrix is reduced, increasing the speed of the encryption algorithm. An extensive security analyses of the proposed scheme are performed, which establishes the robustness, computational efficiency and security of the technique against cryptographic attacks.
{"title":"A Novel Multi-Chaos Based Compressive Sensing Encryption Technique","authors":"Jawad Ahmad, Ahsen Tahir, J. Khan, Atif Jameel, Q. Abbasi, W. Buchanan","doi":"10.1109/AECT47998.2020.9194220","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194220","url":null,"abstract":"Compressive sensing is a compression technique that can be effectively utilised in multimedia encryption. This paper proposes a new compressive sensing image encryption scheme using the Secure Hash Algorithm (SHA-512), Discrete Cosine Transform (DCT), orthogonal matrix and discrete Chirikov map-based random permutation. DCT is applied on a plaintext image and a block of DCT coefficients is multiplied with an orthogonal matrix. Inverse DCT and scaling are performed to restrict the values between 0 and 255. Furthermore, values are shuffled using Chirikov-based pseudo-random permutation. A strong trade-off exists between DCT block size and computational efficiency. The quality and Signal to Noise Ratio (SNR) of the decrypted image decreases when the size of the DCT matrix is reduced, increasing the speed of the encryption algorithm. An extensive security analyses of the proposed scheme are performed, which establishes the robustness, computational efficiency and security of the technique against cryptographic attacks.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121509821","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194181
S. Faizullah, Muhammad Asad Khan, Ali Alzahrani, Imdadullah Khan
The advancement in cloud networks has enabled connectivity of both traditional networked elements and new devices from all walks of life, thereby forming the Internet of Things (IoT). In an IoT setting, improving and scaling network components as well as reducing cost is essential to sustain exponential growth. In this domain, software-defined networking (SDN) is revolutionizing the network infrastructure with a new paradigm. SDN splits the control/routing logic from the data transfer/forwarding. This splitting causes many issues in SDN, such as vulnerabilities of DDoS attacks. Many solutions (including blockchain based) have been proposed to overcome these problems. In this work, we offer a blockchain-based solution that is provided in redundant SDN (load-balanced) to service millions of IoT devices. Blockchain is considered as tamper-proof and impossible to corrupt due to the replication of the ledger and consensus for verification and addition to the ledger. Therefore, it is a perfect fit for SDN in IoT Networks. Blockchain technology provides everyone with a working proof of decentralized trust. The experimental results show gain and efficiency with respect to the accuracy, update process, and bandwidth utilization.
{"title":"Permissioned Blockchain-Based Security for SDN in IoT Cloud Networks","authors":"S. Faizullah, Muhammad Asad Khan, Ali Alzahrani, Imdadullah Khan","doi":"10.1109/AECT47998.2020.9194181","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194181","url":null,"abstract":"The advancement in cloud networks has enabled connectivity of both traditional networked elements and new devices from all walks of life, thereby forming the Internet of Things (IoT). In an IoT setting, improving and scaling network components as well as reducing cost is essential to sustain exponential growth. In this domain, software-defined networking (SDN) is revolutionizing the network infrastructure with a new paradigm. SDN splits the control/routing logic from the data transfer/forwarding. This splitting causes many issues in SDN, such as vulnerabilities of DDoS attacks. Many solutions (including blockchain based) have been proposed to overcome these problems. In this work, we offer a blockchain-based solution that is provided in redundant SDN (load-balanced) to service millions of IoT devices. Blockchain is considered as tamper-proof and impossible to corrupt due to the replication of the ledger and consensus for verification and addition to the ledger. Therefore, it is a perfect fit for SDN in IoT Networks. Blockchain technology provides everyone with a working proof of decentralized trust. The experimental results show gain and efficiency with respect to the accuracy, update process, and bandwidth utilization.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"7 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114031133","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194217
Arbab Mansoor Ahmad, N. Minallah, N. Ahmed, A. Ahmad, Nouman Fazal
Vegetation is one of the most important part of an ecosystem. It is responsible for providing oxygen and gets in carbon dioxide, hence providing a suitable place for the human beings to live. The information about this vegetation is very critical. Using remote sensing, this information can be taken and gathered and later on used for different purposes. This paper aims to classify vegetation into different types and categories. Three machine learning algorithms i.e. K-means, Support Vector Machine (SVM) and Artificial Neural Networks (ANN) have been used because of their being the most popular and well known algorithms of the current time to classify vegetation. K-means being unsupervised classifier is used to compare it to two supervised classifiers i.e. SVM and ANN. Non-vegetation including buildings, roads, rivers etc. are also classified into their respective categories. This classification can be useful in many ways. They can be used by government agencies and authorities to get information about the yield of a specific crop e.g. tobacco, maize etc. This information could be very useful for gathering statistics of the crop and its location on map. These locations can be used for extracting the crops and for future planning regarding it. The information about buildings and roads can help in town planning for future.
{"title":"Remote Sensing Based Vegetation Classification Using Machine Learning Algorithms","authors":"Arbab Mansoor Ahmad, N. Minallah, N. Ahmed, A. Ahmad, Nouman Fazal","doi":"10.1109/AECT47998.2020.9194217","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194217","url":null,"abstract":"Vegetation is one of the most important part of an ecosystem. It is responsible for providing oxygen and gets in carbon dioxide, hence providing a suitable place for the human beings to live. The information about this vegetation is very critical. Using remote sensing, this information can be taken and gathered and later on used for different purposes. This paper aims to classify vegetation into different types and categories. Three machine learning algorithms i.e. K-means, Support Vector Machine (SVM) and Artificial Neural Networks (ANN) have been used because of their being the most popular and well known algorithms of the current time to classify vegetation. K-means being unsupervised classifier is used to compare it to two supervised classifiers i.e. SVM and ANN. Non-vegetation including buildings, roads, rivers etc. are also classified into their respective categories. This classification can be useful in many ways. They can be used by government agencies and authorities to get information about the yield of a specific crop e.g. tobacco, maize etc. This information could be very useful for gathering statistics of the crop and its location on map. These locations can be used for extracting the crops and for future planning regarding it. The information about buildings and roads can help in town planning for future.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"100 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131486473","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 : 2020-02-01DOI: 10.1109/AECT47998.2020.9194154
A. Ayman, Omneya Attalah, H. Shaban
Recognizing daily human activity using machine learning techniques is of great interest to many researchers working in the field of human health monitoring. Recently, wearable sensors have been used extensively for human activity recognition (HAR) for their great ability for capturing human actions during his daily life. Wearable wrist sensors have the advantage of being easily and comfortably worn. Extracting multimodal data from such sensors could enhance recognition rates leading to a healthier life style. Machine learning (ML) techniques have exciting capabilities, and can be used to facilitate HAR process. In this paper, a new daily HAR system is proposed for accurately recognizing daily human activity based on multimodal data from a wearable IMU wrist sensor. Two publically available datasets are employed to examine its effectiveness. The results indicate that the proposed HAR system is competitive to other recent related HAR approaches. This proves that the proposed HAR system is robust and, can be used for health monitoring applications.
{"title":"Smart System for Recognizing Daily Human Activities Based on Wrist IMU Sensors","authors":"A. Ayman, Omneya Attalah, H. Shaban","doi":"10.1109/AECT47998.2020.9194154","DOIUrl":"https://doi.org/10.1109/AECT47998.2020.9194154","url":null,"abstract":"Recognizing daily human activity using machine learning techniques is of great interest to many researchers working in the field of human health monitoring. Recently, wearable sensors have been used extensively for human activity recognition (HAR) for their great ability for capturing human actions during his daily life. Wearable wrist sensors have the advantage of being easily and comfortably worn. Extracting multimodal data from such sensors could enhance recognition rates leading to a healthier life style. Machine learning (ML) techniques have exciting capabilities, and can be used to facilitate HAR process. In this paper, a new daily HAR system is proposed for accurately recognizing daily human activity based on multimodal data from a wearable IMU wrist sensor. Two publically available datasets are employed to examine its effectiveness. The results indicate that the proposed HAR system is competitive to other recent related HAR approaches. This proves that the proposed HAR system is robust and, can be used for health monitoring applications.","PeriodicalId":331415,"journal":{"name":"2019 International Conference on Advances in the Emerging Computing Technologies (AECT)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132504948","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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