Pub Date : 2021-12-01DOI: 10.1109/iSES52644.2021.00021
Preeti Godabole, G. Bhole
The motive of using multicore processors in real time systems, is due to power requirement, processing speed and a heavy integration trend. Failing to meet the timing constraints in real time systems can lead to catastrophic results. So, every task in a real-time system has to be mapped and scheduled to meet the deadlines and utilize the system resources efficiently. Different measurable parameters, in each of the priority based scheduling mechanisms and type of application is identified. The simulation of varied time critical system is carried out for timing analysis using priority based approaches of task scheduling. The extensive experimentation of log uniform random task sets, indicates that there is a necessity of a multi objective task scheduling mechanism for real time systems. The partitioned approach of scheduling in priority based schedulers is desirable to achieve reliability in multicore real time systems.
{"title":"Timing Analysis in Multi-Core Real Time Systems","authors":"Preeti Godabole, G. Bhole","doi":"10.1109/iSES52644.2021.00021","DOIUrl":"https://doi.org/10.1109/iSES52644.2021.00021","url":null,"abstract":"The motive of using multicore processors in real time systems, is due to power requirement, processing speed and a heavy integration trend. Failing to meet the timing constraints in real time systems can lead to catastrophic results. So, every task in a real-time system has to be mapped and scheduled to meet the deadlines and utilize the system resources efficiently. Different measurable parameters, in each of the priority based scheduling mechanisms and type of application is identified. The simulation of varied time critical system is carried out for timing analysis using priority based approaches of task scheduling. The extensive experimentation of log uniform random task sets, indicates that there is a necessity of a multi objective task scheduling mechanism for real time systems. The partitioned approach of scheduling in priority based schedulers is desirable to achieve reliability in multicore real time systems.","PeriodicalId":293167,"journal":{"name":"2021 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134388170","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 : 2021-12-01DOI: 10.1109/iSES52644.2021.00037
Dhruvik Parikh, Sajil Vohra, Maryam Kaveshgar
For improved flight stability, the flight controller needs to compute precise attitudes of the quadrotor at a fast update rate. This paper provides a comparison between different sensor fusion algorithms for estimating attitudes using an Inertial Measurement Unit (IMU), specifically when the accelerometer gives erroneous readings. Three test cases with an emphasis on the influence of external acceleration on attitudes are selected. For each test case, noise filtered data from the IMU is streamed into four algorithms, namely Complementary, Kalman, Madgwick, and Mahony fusion filters. Furthermore, each algorithm is implemented on ESP32 (XtensaOR 32-bit LX6) microcontroller to benchmark the execution time. The estimated attitudes show that the Madgwick filter mitigates the effects of accelerations the most, while the Kalman filter and Mahony filter are robust to vibrations introduced to the system.
{"title":"Comparison of Attitude Estimation Algorithms With IMU Under External Acceleration","authors":"Dhruvik Parikh, Sajil Vohra, Maryam Kaveshgar","doi":"10.1109/iSES52644.2021.00037","DOIUrl":"https://doi.org/10.1109/iSES52644.2021.00037","url":null,"abstract":"For improved flight stability, the flight controller needs to compute precise attitudes of the quadrotor at a fast update rate. This paper provides a comparison between different sensor fusion algorithms for estimating attitudes using an Inertial Measurement Unit (IMU), specifically when the accelerometer gives erroneous readings. Three test cases with an emphasis on the influence of external acceleration on attitudes are selected. For each test case, noise filtered data from the IMU is streamed into four algorithms, namely Complementary, Kalman, Madgwick, and Mahony fusion filters. Furthermore, each algorithm is implemented on ESP32 (XtensaOR 32-bit LX6) microcontroller to benchmark the execution time. The estimated attitudes show that the Madgwick filter mitigates the effects of accelerations the most, while the Kalman filter and Mahony filter are robust to vibrations introduced to the system.","PeriodicalId":293167,"journal":{"name":"2021 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129520576","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 : 2021-10-05DOI: 10.36227/techrxiv.16676794.v1
Nehul Singh, S. Chouhan
Artificial intelligence has proven a matching technology to support multiple business system applications. This technology has been in use to reshape current business models and to provide innovative management strategies. Growing business competition among major players is also strengthening its applications. The business information system with use of artificial intelligence raises the competitiveness of enterprises in the global market. The fast pace of merging artificial intelligence and automation are propelling strategists to revise business models and to explore new possibilities to meet the customer expectations. This paper focuses on the impact of artificial intelligence on business systems. The article also presents an overview of influential academic achievements and innovations in the field of artificial intelligence and their solutions for entrepreneurial activities. In the end, we intend to discuss important points spurred around us in today’s scenario about the challenges and future of artificial intelligence.
{"title":"Role of Artificial Intelligence for Development of Intelligent Business Systems","authors":"Nehul Singh, S. Chouhan","doi":"10.36227/techrxiv.16676794.v1","DOIUrl":"https://doi.org/10.36227/techrxiv.16676794.v1","url":null,"abstract":"Artificial intelligence has proven a matching technology to support multiple business system applications. This technology has been in use to reshape current business models and to provide innovative management strategies. Growing business competition among major players is also strengthening its applications. The business information system with use of artificial intelligence raises the competitiveness of enterprises in the global market. The fast pace of merging artificial intelligence and automation are propelling strategists to revise business models and to explore new possibilities to meet the customer expectations. This paper focuses on the impact of artificial intelligence on business systems. The article also presents an overview of influential academic achievements and innovations in the field of artificial intelligence and their solutions for entrepreneurial activities. In the end, we intend to discuss important points spurred around us in today’s scenario about the challenges and future of artificial intelligence.","PeriodicalId":293167,"journal":{"name":"2021 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129342086","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 : 2010-06-22DOI: 10.1017/S1431927610093542
Péter Sárosi, C. Schooley, D. Leonard, E. Schumacher, E. Humphrey
Provides an abstract for each of the tutorial presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings.
{"title":"Tutorials","authors":"Péter Sárosi, C. Schooley, D. Leonard, E. Schumacher, E. Humphrey","doi":"10.1017/S1431927610093542","DOIUrl":"https://doi.org/10.1017/S1431927610093542","url":null,"abstract":"Provides an abstract for each of the tutorial presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings.","PeriodicalId":293167,"journal":{"name":"2021 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129199356","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：