Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298122
Christine F. Reilly, M. Clark
This paper presents work in progress that focuses on querying transactional graph data that is stored in a relational database system (RDBMS). We focus on transactional workloads where there are frequent insert and update operations. Although these types of workloads are common in social network, scientific, and business applications, much of the prior work has focused on graph analytics workloads where there is little to no change to the data over time. We introduce an approach that combines simple database queries with parallel programming, and compare our approach to the recursive SQL operations that are known to have poor performance. Our initial experiments and results provide guidance for the future directions of this project where we will refine the parallel programing approach and structure of the experiment in order to better compare these two approaches.
{"title":"Moving Recursion Out of the RDBMS for Transactional Graph Workloads","authors":"Christine F. Reilly, M. Clark","doi":"10.1109/UEMCON51285.2020.9298122","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298122","url":null,"abstract":"This paper presents work in progress that focuses on querying transactional graph data that is stored in a relational database system (RDBMS). We focus on transactional workloads where there are frequent insert and update operations. Although these types of workloads are common in social network, scientific, and business applications, much of the prior work has focused on graph analytics workloads where there is little to no change to the data over time. We introduce an approach that combines simple database queries with parallel programming, and compare our approach to the recursive SQL operations that are known to have poor performance. Our initial experiments and results provide guidance for the future directions of this project where we will refine the parallel programing approach and structure of the experiment in order to better compare these two approaches.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130798619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298147
Eunseo Lee, Gregg Vesonder, Elijah Wendel
This paper seeks to examine the potential and capabilities of the Amazon Alexa for aiding the elderly in their own homes. The Alexa System is expected to work alongside eldercare robots in order to provide healthcare to the increasing elderly population. Amazon Alexa provides tools that allow Alexa Skills to be developed and tested. The Alexa Skills that were developed provided an alarm system to remind an elderly person to take their medications, a diet tracking system to keep track of meals and nutrition, and a Skill that would alert a caregiver if the elderly person has fallen down.
{"title":"Eldercare Robotics - Alexa","authors":"Eunseo Lee, Gregg Vesonder, Elijah Wendel","doi":"10.1109/UEMCON51285.2020.9298147","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298147","url":null,"abstract":"This paper seeks to examine the potential and capabilities of the Amazon Alexa for aiding the elderly in their own homes. The Alexa System is expected to work alongside eldercare robots in order to provide healthcare to the increasing elderly population. Amazon Alexa provides tools that allow Alexa Skills to be developed and tested. The Alexa Skills that were developed provided an alarm system to remind an elderly person to take their medications, a diet tracking system to keep track of meals and nutrition, and a Skill that would alert a caregiver if the elderly person has fallen down.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130843820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298094
Sai Pavan, B. Kailath
The paper describes a full-fledged digital hardware implementation of Spiking Neural Network (SNN) architecture on a Field Programmable Gate Array (FPGA) and is focused on proposing a solution to reuse the same SNN for various applications for optimal hardware. This brain-inspired Neuromorphic computing approach to solve various problems has got a lot of potential and benefits. The accurate implementation of spiking neuron models occupies lot of hardware. Designing multiple SNNs for solving various applications is not seen as an ideal approach for implementation which is the key issue addressed in this work. Reusable architecture is proposed as a solution to this issue. The goal of this work is to demonstrate this reusability aspect to reduce the hardware usage by applying the same SNN to two different applications of gesture controlled robotic arm and pattern recognition. The entire hardware designing is done in Very High-Speed Integrated Circuit Hardware Description Language and simulated in ModelSim RTL simulator. The tool used for performing synthesis is Intel Quartus Prime. It has been demonstrated that the number of neurons and the hardware resource utilization required in the proposed dual application SNN framework is much less than the same for the reported works intended for single application.
{"title":"Reusable Spiking Neural Network Architecture","authors":"Sai Pavan, B. Kailath","doi":"10.1109/UEMCON51285.2020.9298094","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298094","url":null,"abstract":"The paper describes a full-fledged digital hardware implementation of Spiking Neural Network (SNN) architecture on a Field Programmable Gate Array (FPGA) and is focused on proposing a solution to reuse the same SNN for various applications for optimal hardware. This brain-inspired Neuromorphic computing approach to solve various problems has got a lot of potential and benefits. The accurate implementation of spiking neuron models occupies lot of hardware. Designing multiple SNNs for solving various applications is not seen as an ideal approach for implementation which is the key issue addressed in this work. Reusable architecture is proposed as a solution to this issue. The goal of this work is to demonstrate this reusability aspect to reduce the hardware usage by applying the same SNN to two different applications of gesture controlled robotic arm and pattern recognition. The entire hardware designing is done in Very High-Speed Integrated Circuit Hardware Description Language and simulated in ModelSim RTL simulator. The tool used for performing synthesis is Intel Quartus Prime. It has been demonstrated that the number of neurons and the hardware resource utilization required in the proposed dual application SNN framework is much less than the same for the reported works intended for single application.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"251 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133527219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298030
Mohamed Sofiane Batta, Z. Aliouat, H. Mabed, S. Harous
Mobile traffic is expected to grow by 30% by 2024, saving energy is a crucial necessity even for battery-powered devices such as smartphones for the sake of green computing. Clustering techniques were introduced to conserve the energy of network devices. However, proposed energy optimization techniques do not yield optimal battery life, they mostly consider devices with non-rechargeable batteries and deal with limited energy without considering battery aging (short-term vision). To this end, we focus on the long-term energy optimization and we introduce a dynamic clustering technique that take into consideration the state of health of devices batteries and their degradation level. The proposed scheme efficiently manages the energy resource to enhance the battery behavior which extends the network lifespan in the long term.Simulations results show that the proposed approach out-performs similar works available in the current literature. The batteries life cycle and the network lifetime are improved by 38% and 47% respectively. The average number of generated clusters is reduced by 39%.
{"title":"LTEOC: Long Term Energy Optimization Clustering For Dynamic IoT Networks","authors":"Mohamed Sofiane Batta, Z. Aliouat, H. Mabed, S. Harous","doi":"10.1109/UEMCON51285.2020.9298030","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298030","url":null,"abstract":"Mobile traffic is expected to grow by 30% by 2024, saving energy is a crucial necessity even for battery-powered devices such as smartphones for the sake of green computing. Clustering techniques were introduced to conserve the energy of network devices. However, proposed energy optimization techniques do not yield optimal battery life, they mostly consider devices with non-rechargeable batteries and deal with limited energy without considering battery aging (short-term vision). To this end, we focus on the long-term energy optimization and we introduce a dynamic clustering technique that take into consideration the state of health of devices batteries and their degradation level. The proposed scheme efficiently manages the energy resource to enhance the battery behavior which extends the network lifespan in the long term.Simulations results show that the proposed approach out-performs similar works available in the current literature. The batteries life cycle and the network lifetime are improved by 38% and 47% respectively. The average number of generated clusters is reduced by 39%.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133157449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298052
L. Badia, Nunzio Borra
In this paper, we draw an analogy between crowd-sensing scenarios and the real life activity of singing in a choir. We identify some similarities, in particular for what concerns the role of the network coordinator and the choir director, as well as the common desirability of eliminating non-collaborative behavior (free-riding). Inspired by this comparison, we identify some strategies that the "director" can implement during "choir rehearsals" and we give a game theoretic analysis of their effectiveness. The general model is based on characterizing the willingness to undertake effort for the common task as a user's private type, which is compared to the contribution cost to decide whether to contribute or free-ride. Imposing some access penalty is known to reduce significantly the onset of free-riding, and we discuss possible ways to implement such a penalty, namely, we compare a probabilistic exclusion of free riders, as well as a multiplicative and an additive penalty to access, and we show the better effectiveness of the last strategy.
{"title":"Crowdsensing Strategies Inspired by Choir Management Analyzed via Game Theory","authors":"L. Badia, Nunzio Borra","doi":"10.1109/UEMCON51285.2020.9298052","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298052","url":null,"abstract":"In this paper, we draw an analogy between crowd-sensing scenarios and the real life activity of singing in a choir. We identify some similarities, in particular for what concerns the role of the network coordinator and the choir director, as well as the common desirability of eliminating non-collaborative behavior (free-riding). Inspired by this comparison, we identify some strategies that the \"director\" can implement during \"choir rehearsals\" and we give a game theoretic analysis of their effectiveness. The general model is based on characterizing the willingness to undertake effort for the common task as a user's private type, which is compared to the contribution cost to decide whether to contribute or free-ride. Imposing some access penalty is known to reduce significantly the onset of free-riding, and we discuss possible ways to implement such a penalty, namely, we compare a probabilistic exclusion of free riders, as well as a multiplicative and an additive penalty to access, and we show the better effectiveness of the last strategy.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131882818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298144
U. K. Dey, R. Akl, Robin Chataut, Mohammadreza Robaei
People are increasingly relying on vehicular communities for a more safe and comfortable day-to-day car journey. So, expectation from vehicular technology is increasing more from time to time. As a result, vehicular technology is expected to support infotainment services to the traveler. Hence, the requirements for entertainment services need extra capacity along with safety services. One of the important pieces in the channel capacity is throughput. The existing IEEE 802.11p standard with the support of Dedicated Short Range Communication (DSRC) might not fulfill the required capacity in the coming days. To achieve that required throughput DSRC protocol needs to evolve. However, Multiple Input Multiple Output (MIMO) and 5G NR has the potential to improve throughput while maintaining the existing PHY layer specifications defined in the Wireless Access for Vehicular Environments (WAVE) standard. We propose a modified PHY layer of the DSRC protocol to integrate MIMO and 5G NR to enhance the existing data rate. Our experimental results show that the combination of MIMO and 5G NR can boost the throughput to 6.5 times better compared to MIMO enabled existing framework while keeping the BER (Bit Error Rate) as the same or in some cases below the combination of MIMO and DSRC.
{"title":"Modified PHY Layer for High Performance V2X Communication using 5G NR","authors":"U. K. Dey, R. Akl, Robin Chataut, Mohammadreza Robaei","doi":"10.1109/UEMCON51285.2020.9298144","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298144","url":null,"abstract":"People are increasingly relying on vehicular communities for a more safe and comfortable day-to-day car journey. So, expectation from vehicular technology is increasing more from time to time. As a result, vehicular technology is expected to support infotainment services to the traveler. Hence, the requirements for entertainment services need extra capacity along with safety services. One of the important pieces in the channel capacity is throughput. The existing IEEE 802.11p standard with the support of Dedicated Short Range Communication (DSRC) might not fulfill the required capacity in the coming days. To achieve that required throughput DSRC protocol needs to evolve. However, Multiple Input Multiple Output (MIMO) and 5G NR has the potential to improve throughput while maintaining the existing PHY layer specifications defined in the Wireless Access for Vehicular Environments (WAVE) standard. We propose a modified PHY layer of the DSRC protocol to integrate MIMO and 5G NR to enhance the existing data rate. Our experimental results show that the combination of MIMO and 5G NR can boost the throughput to 6.5 times better compared to MIMO enabled existing framework while keeping the BER (Bit Error Rate) as the same or in some cases below the combination of MIMO and DSRC.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124559297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298080
Oguz Ülgen, Serhat Erküçük, T. Baykaş
Terahertz communications is one of the promising technologies for the future mobile communication networks. Due to the ever increasing need for high-speed data transfer, higher bandwidths are required. As a solution, higher frequencies in the spectrum may be considered for future networks. In this paper, Terahertz band is selected since the latest technological advances make it possible to deploy mobile networks in this high-frequency band. To support higher bandwidth with an advanced multiple access method, non-orthogonal multiple access (NOMA) is implemented in this paper. Different from orthogonal multiple access (OMA), NOMA makes it possible for users to share the same frequency and time resources simultaneously, therefore increases the spectral efficiency. To measure the efficiency of the implemented methods, computer simulations are used and results are obtained for different scenarios. In the simulation results, it is shown that NOMA provides higher average data rates for these scenarios where users are located on variety of distances far from the Terahertz access point. As a result, this work shows NOMA for Terahertz communication networks is a promising method for future communication networks.
{"title":"Non-Orthogonal Multiple Access for Terahertz Communication Networks","authors":"Oguz Ülgen, Serhat Erküçük, T. Baykaş","doi":"10.1109/UEMCON51285.2020.9298080","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298080","url":null,"abstract":"Terahertz communications is one of the promising technologies for the future mobile communication networks. Due to the ever increasing need for high-speed data transfer, higher bandwidths are required. As a solution, higher frequencies in the spectrum may be considered for future networks. In this paper, Terahertz band is selected since the latest technological advances make it possible to deploy mobile networks in this high-frequency band. To support higher bandwidth with an advanced multiple access method, non-orthogonal multiple access (NOMA) is implemented in this paper. Different from orthogonal multiple access (OMA), NOMA makes it possible for users to share the same frequency and time resources simultaneously, therefore increases the spectral efficiency. To measure the efficiency of the implemented methods, computer simulations are used and results are obtained for different scenarios. In the simulation results, it is shown that NOMA provides higher average data rates for these scenarios where users are located on variety of distances far from the Terahertz access point. As a result, this work shows NOMA for Terahertz communication networks is a promising method for future communication networks.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114877192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298154
Justina Celentano, Eman Abdelfattah
This research presents data that has been analyzed regarding gun violence incidents in the United States. The data was evaluated using the Python programming language and its data analytics tools. The findings were visualized using heat maps and choropleth maps of the United States as well as other useful charts and graphs to perform an unbiased analysis on gun violence incidents. There were multiple findings, including how many incidents of gun violence are committed by men as well as how the states with the highest number of incidents are not always states with weak gun laws.
{"title":"Analyzing Gun Violence in the United States","authors":"Justina Celentano, Eman Abdelfattah","doi":"10.1109/UEMCON51285.2020.9298154","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298154","url":null,"abstract":"This research presents data that has been analyzed regarding gun violence incidents in the United States. The data was evaluated using the Python programming language and its data analytics tools. The findings were visualized using heat maps and choropleth maps of the United States as well as other useful charts and graphs to perform an unbiased analysis on gun violence incidents. There were multiple findings, including how many incidents of gun violence are committed by men as well as how the states with the highest number of incidents are not always states with weak gun laws.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114950144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298131
Jingang Liu, Chunhe Xia, Haihua Yan, Jie Sun
With the rapid rise of artificial intelligence technologies such as machine learning and the rapid development of the big data industry, more and more attention is paid to the use of data itself, especially the Chinese text data, which is more complex in expression and richer in the information. It is a necessary step to process the raw Chinese text data before it is used for specific application tasks. However, the current strategies for processing data are generally to deal with data in different fields and specific application tasks. In this paper, to further improve the quality of Chinese data processing and give play to the application value of Chinese data, we propose a general and feasible Chinese text preprocessing strategy, named the multi-level data preprocessing strategy (MLDPS). This strategy uses four effective links to process raw Chinese text data systematically. We believe that the proposed MLDPS has relatively strong practical significance, and provides a better idea for preprocessing Chinese text data.
{"title":"A Feasible Chinese Text Data Preprocessing Strategy","authors":"Jingang Liu, Chunhe Xia, Haihua Yan, Jie Sun","doi":"10.1109/UEMCON51285.2020.9298131","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298131","url":null,"abstract":"With the rapid rise of artificial intelligence technologies such as machine learning and the rapid development of the big data industry, more and more attention is paid to the use of data itself, especially the Chinese text data, which is more complex in expression and richer in the information. It is a necessary step to process the raw Chinese text data before it is used for specific application tasks. However, the current strategies for processing data are generally to deal with data in different fields and specific application tasks. In this paper, to further improve the quality of Chinese data processing and give play to the application value of Chinese data, we propose a general and feasible Chinese text preprocessing strategy, named the multi-level data preprocessing strategy (MLDPS). This strategy uses four effective links to process raw Chinese text data systematically. We believe that the proposed MLDPS has relatively strong practical significance, and provides a better idea for preprocessing Chinese text data.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116835596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298049
Nader Nagui, Omneya Attallah, M. Zaghloul, I. Morsi
This paper aims to design a real time autonomous navigation system (ANS) using low cost electronics devices with significant navigation accuracy levels. This system could be practically implemented inside any vehicle to enable autonomous movement. The proposed ANS is implemented through an open loop decentralized loosely integration approach of an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). Due its modularity, the 6 degree of freedom (DOF) MPU6050 breakout board is used to be the IMU in the system. The GPS receiver is selected to be the Skylab SKM53 module. Appropriate real time navigation accuracy levels are obtained through the correction of Position and Velocity (PV) readings coming out from the GPS. Two Extended Kalman Filters (EKFs) are used to provide the corrected PV readings. The filters are implemented through two state machines that are running simultaneously in a concurrent form on an Atmel ATmega16 microcontroller which is the main controller of the proposed ANS. The system also includes 3DRobotics 915 MHz wireless telemetry module to grant the real time processing of the navigation data. The system accuracy is validated on a real vehicular trajectory. The Root Mean Square Error (RMSE) values for the implemented ANS in ENU directions, have reached 0.254, 0.337 and 0.462 meters respectively, which is notably competitive with other recent related work.
{"title":"Smart Real-Time Autonomous Navigation System using integration of MEMS-based Low-Cost IMU/GPS","authors":"Nader Nagui, Omneya Attallah, M. Zaghloul, I. Morsi","doi":"10.1109/UEMCON51285.2020.9298049","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298049","url":null,"abstract":"This paper aims to design a real time autonomous navigation system (ANS) using low cost electronics devices with significant navigation accuracy levels. This system could be practically implemented inside any vehicle to enable autonomous movement. The proposed ANS is implemented through an open loop decentralized loosely integration approach of an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). Due its modularity, the 6 degree of freedom (DOF) MPU6050 breakout board is used to be the IMU in the system. The GPS receiver is selected to be the Skylab SKM53 module. Appropriate real time navigation accuracy levels are obtained through the correction of Position and Velocity (PV) readings coming out from the GPS. Two Extended Kalman Filters (EKFs) are used to provide the corrected PV readings. The filters are implemented through two state machines that are running simultaneously in a concurrent form on an Atmel ATmega16 microcontroller which is the main controller of the proposed ANS. The system also includes 3DRobotics 915 MHz wireless telemetry module to grant the real time processing of the navigation data. The system accuracy is validated on a real vehicular trajectory. The Root Mean Square Error (RMSE) values for the implemented ANS in ENU directions, have reached 0.254, 0.337 and 0.462 meters respectively, which is notably competitive with other recent related work.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128347735","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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