Tanuja Patgar, Kavitha Devi Cs
On-Board Design Models and Algorithm for Communication Based Train Control and Tracking System (eBook, ePUB)
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Tanuja Patgar, Kavitha Devi Cs
On-Board Design Models and Algorithm for Communication Based Train Control and Tracking System (eBook, ePUB)
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This book covers the latest advances in CBTC research in On-board components locomotive messaging system, GPS sensors, communications wayside and switching network. It also focuses on architecture and methodology using data fusion technique.
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This book covers the latest advances in CBTC research in On-board components locomotive messaging system, GPS sensors, communications wayside and switching network. It also focuses on architecture and methodology using data fusion technique.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 144
- Erscheinungstermin: 30. Mai 2022
- Englisch
- ISBN-13: 9781000642643
- Artikelnr.: 64093169
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 144
- Erscheinungstermin: 30. Mai 2022
- Englisch
- ISBN-13: 9781000642643
- Artikelnr.: 64093169
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Kavitha Devi CS received B.E degree in Electronics and Communication Engineering from Visvesvaraya Technological University, Belgaum. Karnataka, India in 2002. In 2009, she received M.Tech in Computer Science Engineering Visvesvaraya Technological University, Belgaum.Karnataka, India. She is pursuing her PhD in "Design and Implementation of Compact Microstrip Filters" in Visvesvaraya Technological University, Belagavi, India. Her research interest includes Wireless Communication, Microwave and Engineering, Microwave devices, Antennas and wave propagation, Electromagnetic Waves, Wireless Sensor Network, Virtual Reality, Deep Learning, Data Science and Computer Vision with 27 paper publications, 1 international patent, vidwan score of 7.4, 2 silver medals in NPTEL courses, 8 Google scholar citations and RG Score 2.21(Research Gate). She is fellow member for I.S.T.E, I.E.T.E, C.R.S.I and I.S.S.S. Presently serving as Assistant Professor at Dr. Ambedkar Institute of Technology, Bangalore, India.
Tanuja P. Patgar received B.E degree in Electronics and Communication from Kuvempu university, Karnataka, India in 1996. In 2010, she received M.E in Control and Instrumentation from University Vishweshraya Collage of Engineering, Bangalore, India. She received her PhD from Visvesvaraya Technological University, Belgaum, India in 2020. Her research field is Wireless Sensor Network, Artificial Neural Network, Machine learning, Deep Learning, Data Science and Computer Vision. She has pioneered research in wireless sensor network, control system and has published 35 international refereed Journal papers. She has edited several international and national journals, books and frequently gives invited keynote lectures at national. She is awarded with national Innovative Educationalist in Engineering and Technology, Maulana Abdul Kalam Azad excellence Award of Education, Talent Teacher Ideal Teacher Pratibha Puraskar, Best paper award. She is academic adviser for AI based startup. She has served as a Congress Chair for International Congress on Mobile and Wireless Hong kong and Technical Program Committee Member and Scientific Committee Member for IFERP and IAENG Conference. She is fellow member for I.S.T.E, I.E.T.E, I.S.A, IMAP, IFERP, IAENG and SDIWC. Presently serving at Dr. Ambedkar Institute of Technology, Bangalore, India.
Tanuja P. Patgar received B.E degree in Electronics and Communication from Kuvempu university, Karnataka, India in 1996. In 2010, she received M.E in Control and Instrumentation from University Vishweshraya Collage of Engineering, Bangalore, India. She received her PhD from Visvesvaraya Technological University, Belgaum, India in 2020. Her research field is Wireless Sensor Network, Artificial Neural Network, Machine learning, Deep Learning, Data Science and Computer Vision. She has pioneered research in wireless sensor network, control system and has published 35 international refereed Journal papers. She has edited several international and national journals, books and frequently gives invited keynote lectures at national. She is awarded with national Innovative Educationalist in Engineering and Technology, Maulana Abdul Kalam Azad excellence Award of Education, Talent Teacher Ideal Teacher Pratibha Puraskar, Best paper award. She is academic adviser for AI based startup. She has served as a Congress Chair for International Congress on Mobile and Wireless Hong kong and Technical Program Committee Member and Scientific Committee Member for IFERP and IAENG Conference. She is fellow member for I.S.T.E, I.E.T.E, I.S.A, IMAP, IFERP, IAENG and SDIWC. Presently serving at Dr. Ambedkar Institute of Technology, Bangalore, India.
1. Vision of Intelligent Control and Tracking Rail System: Global Evident
Data 2. Train Navigation Control and Information Management System 3.
Hybrid System for Train Tracking and Monitoring Model 4. Locomotive
Tracking in SatelliteVisible And Low Satellite Visible Area 5. Train
Trajectory Optimization Based On Di-Filter Theory 6. Heterogeneous Sensor
Data Fusion DGPS-WSN-RFID-Based Train Tracking Model 7. Wireless Locomotive
Real-Time Surveillance Model 8. Predictive Analysis of Intelligent Rail
Trip Detection Service Using Machine Learning
Data 2. Train Navigation Control and Information Management System 3.
Hybrid System for Train Tracking and Monitoring Model 4. Locomotive
Tracking in SatelliteVisible And Low Satellite Visible Area 5. Train
Trajectory Optimization Based On Di-Filter Theory 6. Heterogeneous Sensor
Data Fusion DGPS-WSN-RFID-Based Train Tracking Model 7. Wireless Locomotive
Real-Time Surveillance Model 8. Predictive Analysis of Intelligent Rail
Trip Detection Service Using Machine Learning
1. Vision of Intelligent Control and Tracking Rail System: Global Evident
Data 2. Train Navigation Control and Information Management System 3.
Hybrid System for Train Tracking and Monitoring Model 4. Locomotive
Tracking in SatelliteVisible And Low Satellite Visible Area 5. Train
Trajectory Optimization Based On Di-Filter Theory 6. Heterogeneous Sensor
Data Fusion DGPS-WSN-RFID-Based Train Tracking Model 7. Wireless Locomotive
Real-Time Surveillance Model 8. Predictive Analysis of Intelligent Rail
Trip Detection Service Using Machine Learning
Data 2. Train Navigation Control and Information Management System 3.
Hybrid System for Train Tracking and Monitoring Model 4. Locomotive
Tracking in SatelliteVisible And Low Satellite Visible Area 5. Train
Trajectory Optimization Based On Di-Filter Theory 6. Heterogeneous Sensor
Data Fusion DGPS-WSN-RFID-Based Train Tracking Model 7. Wireless Locomotive
Real-Time Surveillance Model 8. Predictive Analysis of Intelligent Rail
Trip Detection Service Using Machine Learning