Nghiên cứu hệ thống hộ trợ đỗ xe thông minh dựa trên vận dụng công nghệ internet = intelligent parking assist system based

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Nghiên cứu hệ thống hộ trợ đỗ xe thông minh dựa trên vận dụng công nghệ internet = intelligent parking assist system based

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逢 逢 逢 逢 逢 逢 逢 逢 逢 逢 逢 逢逢 逢 基基基基基基基基基基基基基基 基基基基基基基 Intelligent Parking Assist System based on Internet of Things Technologies 逢逢逢逢逢逢逢逢 逢逢逢逢逢 逢逢逢逢逢 逢 逢 逢逢逢逢逢 逢 逢 逢 逢 逢 逢 逢 逢 逢 逢 逢 Intelligent Parking Assist System based on Internet of Things Technologies Acknowledgements First and foremost, I would like to my advisers, Professor Ming-Fong Tsai and Professor Fang-Rong Hsu Professor Tsai, thank you very much for your encouragement, guidance, and support for the years I spent in Feng Chia You are truly visionary and a great advisor Professor Hsu, thank you for supporting me and your useful advice that you have given me I really enjoyed those brainstorming and discussion meetings that we had Without both of you, this research would not be possible Thank you I am grateful to Professor Chyi-Ren Dow for supporting me and giving me the opportunity to study in Feng Chia Many thanks to Professor Wei-Bin Lee, Professor Wei-Chih Hong, Professor Yi-Chung Chen, Professor Tzong-An Su for the knowledge you gave me in my courses To all Professors and Teaching Assistants who have taught me, I thank you I would also like to thank to all my lab-mates in Wireless Networking Lab and Intelligent of Things Lab for giving me a great working place and great help while I work here In particular, I would like to thank my dear friend Curtis Ye for the wonderful time that we spent together I also greatly appreciate all the help from Bo Cai, Ching-Fu Hsiang, ChiaYuan, Qi-Feng and other friends Special thanks to my family, especially my Mom and Dad, for their support and encouragement over the years Finally, I am thankful to my wife for her love giving me i FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Abstract In recent years, there has been a rapid development of technologies devising solutions for intelligent transportation systems, including intelligent parking assist systems However, previous systems revealed several weaknesses, such as models which are not scalable, not provide a full range of parking services to users, not effectively manage parking resources, and have high latency in real-time parking services To overcome these problems, this thesis examines previous research and proposes a new model for intelligent parking assist systems We also introduce novel algorithms that increase the efficiency of the proposed system based on Internet of Things (IoT) technologies Our system can help users to automatically find an optimal parking space at the least cost, based on new performance metrics In addition, this thesis also proposes an intelligent parking assist system with a full range of end-to-end support services including: finding a suitable parking space based on the user’s profile, outside guidance service, enter car park service, and indoor guidance service Our system has been simulated and successfully implemented in the real world The simulation results show that our system helps to improve the probability of successful parking and minimizes user waiting time Keywords: Smart parking system, Internet of Things technologies, performance metrics ii FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies Table of Contents Acknowledgements i Abstract ii Table of Contents iii List of Figures v List of Tables vii Chapter Introduction to the Development of Intelligent Parking Systems 1.1 Automated parking system 1.2 Intelligent parking assist system 1.3 Classification of intelligent parking assist system 1.4 Shortfalls of current Parking Systems Chapter Architecture for Intelligent Parking Assist Systems based on Internet of Things Technologies 2.1 Internet of Things technologies 2.2 Structure of an IPAS System based on IoT technologies 11 2.2.1 Local Parking Unit 11 2.2.2 Database Server 13 2.2.3 Software Client 15 2.3 IoT Hardware for IPAS Systems 16 2.3.1 Sensors 16 2.3.2 Arduino, Raspberry Pi Control Units 18 2.4 Protocol stack for IPAS systems 19 2.5 Propose the IPAS network based on IoT technologies 21 2.5.1 Parking Network 22 2.5.2 Construct the neighbor table of nodes 25 Chapter Mathematical 28 Models for IPAS Systems iii FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies 3.1 Linked-Cost function estimation 28 iii FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies 3.2 Total Parking Cost Estimation 31 3.3 Parking Queue Models 33 Chapter Smart Services System Over Parking Networks .35 4.1 Introduction 35 4.2 System Framework 36 4.3 Parking Services 38 4.3.1 Searching Service and Booking Service 38 4.3.2 Tracking service 40 4.3.3 Guidance service 41 4.3.4 Locking Service and Warning Service 42 4.4 Implementation 43 Chapter Enhance the Performance of Wireless Communication in Intelligent Parking System 47 5.1 Indoor guidance using Ultra-wideband signals 47 5.2 Improve the quality of data transmission in IPAS system using a look up table structure 51 5.3 An adaptive solution for data transmission between local IoT network and server system using MQTT protocol 56 Chapter Evaluate the Performance of Intelligent Parking System .60 6.1 Arena simulation tool 60 6.2 Scenarios setup 61 6.3 Evaluate the performance of IPAS system 63 6.3.1 Without consideration of parking fee 63 6.3.2 With consideration of parking fee 67 Chapter Conclusion 69 7.1 Summary 69 7.2 Perspectives 69 7.3 The future of IPAS system 70 FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies 71 References FCU e-Theses & Dissertations (2018) Intelligent Parking Assist System based on Internet of Things Technologies List of Figures Figure 1 An automated parking system Figure The basic configuration of an IPAS system Figure The basic structure of an IPAS system based on Internet of Things technologies 11 Figure 2 The role of the control unit in an IPAS system 12 Figure The use of ultrasonic sensor to detect the presence of the car at the parking space 13 Figure Propose to use Fog Computing in building intelligent parking assist system 14 Figure The interface of an IPAS system running on iOS platform 16 Figure Andruino/Raspberry Pi module used as control unit in Intelligent Parking Assist System 19 Figure Stack of protocols for Intelligent Parking Assist System 21 Figure Infrastructure/Backbone of the CPN architecture 22 Figure Car park network deployment for car parking system 23 Figure 10 Parking network 24 Figure 11 Simple neighbour tables 25 Figure 12 Neighbour tables sorted by descending values of F, , 26 Figure 13 A searching for a parking space based on the cost function 27 Figure The service queue 33 Figure System framework for IPAS services 37 Figure Illustrate the Searching/Booking Service 39 Figure Illustrate the Tracking service 40 Figure 4 Illustrate the guidance services: (a) Outside guidance, (b) Entering car park guidance, (c) Indoor guidance 42 Figure Illustrate the Car Locking and Warning Service 43 FCU e-Theses & Dissertations (2018) Figure Average waiting time in a normal network vs the proposed network We realize that if we use the percentage of free spaces in each car park as a parameter for planning with regard to forwarding users, the waiting time of the user for service will be greatly reduced compared to an ordinary network In Fig 6.4, we compare the average total time of each vehicle in a normal network model and our proposed network model We can see that if the value of α is 0.8 and β is 0.2, our proposed network achieves best performance compared to other pairs of (α, β) If the value of α is and β is 0, the average total time is approximately equal to the average total time in a normal network It is the worst case The best solution in this network, with (α = 0.2, β = 0.8), reduces the average total time the user stays in the system by approximately 50% 64 FCU e-Theses & Dissertations (2018) Figure Average total time in normal network vs the proposed network The following results are description of all values of α and β: Table Average waiting time in case of POIS(20 minute) 65 FCU e-Theses & Dissertations (2018) Table Average waiting time in case of POIS(15 minute) Table Average total time in case of POIS(20 minute) 66 FCU e-Theses & Dissertations (2018) Table Average total time in case of POIS(15 minute) 6.3.2 With consideration of parking fee In figure 6.5, we can see with shortest path option (α = 1, β = 0, γ = 0), the average waiting time of the user is greater than 20 minutes and this is not the optimal value Besides the parking fee is highest with Fcost = 100 If we choose the least cost option in term of parking fee, the average waiting time that vehicles wait for parking is the longest and more than 25 minutes, but the parking fee that user should pay is the smallest with Fcost = And, with best space option, we can see in Fig 6.5 that the average waiting time is minimal With the set of values (α = 0.2, β = 0.8, γ = 0) we can see the user has the smallest average waiting time and it is smaller than 10 minutes This set of values coincides with the optimal values of the waiting time as in [10], but we could see the parking fee which users should to pay is still not an optimal value with Fcost = 36 This because the value of α is means that users only care about the wait time for parking without regard to the fee should pay for parking In this paper, we propose to use the set of values (α = 0.2, β = 0.5, γ = 0.3) because the waiting time may be acceptable by users and the cost of parking fee is near to optimal values This will bring a lot of significant for users with very long parking time 67 FCU e-Theses & Dissertations (2018) Figure Average waiting time vs parking fee 68 FCU e-Theses & Dissertations (2018) Chapter Conclusion 7.1 Summary This thesis studies the models of intelligent parking systems based on IoT technologies This research also introduces a novel parking network which connects all parking lots and offers intelligent services These services have the following benefits: This thesis helps to provide an architecture of intelligent parking networks from which local parking networks with existing infrastructure can be easily integrated into the system Our large-scale parking system architecture makes it convenient for service providers to manage and utilize the parking lot resources efficiently This system provides more information about car parking places in real-time It will give more options to users to select the appropriate free parking space via their smartphone It will help users to quickly and accurately reach their desired parking space It helps users to monitor and give warnings about the current parking situation when they are outside of a car park In addition, this study proposes a new method to help users estimate the cost in terms of travel time and parking time, because we provide an optimal solution for the parking requests searched for by users This study also proposes new methods to improve the performance of intelligent parking systems 7.2 Perspectives Parking is becoming more and more popular in modern life The research and development of smart parking models is becoming an emerging topic of interest IoT technology has recently exploded in all kinds of applications in life Therefore, this thesis raises the perspective of the construction of future data networks and the modelling of intelligent cities 69 FCU e-Theses & Dissertations (2018) 7.3 The future of IPAS system In the future, vehicles will become smart objects Vehicles will themselves be aware of the surrounding environment and will be able to provide solutions to traffic situations They will interact with other nearby vehicles and find an optimal route to the most appropriate parking lot All vehicles will be managed by unique ID addresses similar to the ID of each individual A vehicle identification system will be developed, which can identify vehicle IDs at great distances (much more than current technologies such as RFID); this will help to identify and locate vehicles more accurately and quickly The management of vehicles by ID helps operators to easily compile statistical data on the activities of each vehicle, including travel time and parking time, which will feed into plans to construct intelligent parking networks more effectively In addition, parking fees and other services applicable to vehicles will become more convenient The construction of parking lots does not require too much equipment to assist with the management and collection of parking lot data The future of the IoT will also change, with all objects, including vehicles, connecting and communicating with each other, not only through the Internet connection, but also in new ways Therefore, users can access parking information anywhere 70 FCU e-Theses & Dissertations (2018) References [1] A O Kotb, Y C Shen, Y Huang, “Smart Parking Guidance, Monitoring and Reservations: A Review,” IEEE Intelligent Transportation System Magazine, pp 616, April 2017 [2] Https://en.wikipedia.org/wiki/Automated_parking_system, Retrieved 15 April 2018 [3] Patrascu, Daniel (2010), “How Automated Parking System Work,” Autoevolution, accessed 15 April 2018 [4] Ir Hamelink, J Leon, “The Mechanical Parking Guide 2011,” ISBN 1-466-43786-3 [5] K Ashton, “That ‘Internet of Things’ Thing,” 22 June 2009, Retrieved 15 April 2018 [6] “Internet of Things Global Standards Initiative” ITU Retrieved 15 April 2018 [7] International Telecommunication Union, “Overview of the Internet of Things,” Recommendation ITU-T Y.2060, June 2012 [8] A Sakai, K Mizuno, T Sugimoto, and T Okuda, “Parking guidance and information systems,” Vehicle Navigation and Information Systems Conference, 1995 [9] P Loannou, Y Zhang, “Intelligent driver assist system for urban driving,” Digital Media Industry & Academic Forum (DMIAF), 2016 [10] S Alfatihi, S Chihab, Y S Alj, “Intelligent Parking System for Car Parking Guidance and Damage Notification,” 4th International Conference on Intelligent Systems Modelling & Simulation (ISMS), 2013 [11] K Axhausen, J Polak, M Boltze, and J Puzicha, “Effectiveness of the parking guidance information system in frankfurt am main,” Traffic engineering & control, vol 35, no 5, pp 304-9, 1994 [12] Y Ji, W Guo, P Blythe, D Tang, and W Wang, “Understanding drivers’ perspective on parking guidance information,” IET Intelligent Transport Systems, vol 8, no 4, pp 398-406, June 2014 71 FCU e-Theses & Dissertations (2018) [13] S E Yoo, P K Chong, T Kim, J Kang, D Kim, C Shin, K Sung, and B Jang, “PGS: Parking guidance system based on wireless sensor network,” 3rd International Symposium on Wireless Pervasive Computing (ISWPC), pp 218-222, 2008 [14] Y Asakura and M Kashiwadani, “ Effects of parking availability information on system performance: a simulation model approach,” Proc IEEE Vehicle Navigation and Information Systems Conference, 1994, pp 251-254 [15] H Z Guan, L H Liu, and M J Liao, “Approach for planning of parking guidance and information system,” Journal of Highway and Transportation Research and Development, vol 1, p 034, 2003 [16] J W Polak, I C Hilton, K W Axhausen, and W Young, “Parking guidance and information systems: performance and capability,” Traffic engineering & control, vol 31, no 10, pp 519-524, 1990 [17] G N Hainalkar, M S Vanjale, “Smart parking system with pre & post reservation, billing and traffic app,” Traffic Engineering & Control, In International Conference on Intelligent Computing and Control Systems (ICICCS), pp 500-505, June 2017 [18] P Sheelarani, S P Anand, S Shamili, K Sruthi, “Effective car parking reservation system based on internet of things technologies,” World Conference on Futuristic Trends in Research and Innovation for Social Welfare (Startup Conclave), pp 1-4, March 2016 [19] C W Hsu, M H Shih, H Y Huang, Y C Shiue, S C Huang, “Verification of Smart Guiding System to Search for Parking Space via DSRC Communication,” 12th International Conference on ITS Telecommunications, pp 77-81, November 2012 [20] C Yuan, L Fei, C Jianxin, J Wei, “A Smart Parking System using WiFi and Wireless Sensor Network,” International Conference on Consumer ElectronicsTaiwan, pp 1-2, May 2016 72 FCU e-Theses & Dissertations (2018) [21] F Caicedo, “Real-time parking information management to reduce search time, vehicle displacement and emissions”, Transportation Research Part D: Transport and Environment, Vol 15, No 4, pp 228-234, June 2010 [22] S Bitam, A Mellouk, “ITS-Cloud: Cloud Computing for Intelligent Transport System”, Globecom 2012 – Communications Software, Services and Multimedia Symposium, pp 2054-2059, December 2012 [23] T N Pham, M F Tsai, D.B Nguyen, C R Dow, D J Deng, “A Cloud-Based Smart-Parking System Based on Internet of Things Technologies,” IEEE Access, Volume 3, pp 1581-1591, September 2015 [24] M F Tsai, Y C Kiong, A Sinn, “Smart Service Relying on Internet of Things Technology in Parking Systems,” Journal of Suppercomputing, September 2016 [25] T Rajabioun and P Ioannou, “On-street and off-street parking availability predection using multivariate spatiotemporal models”, IEEE Transactions on Intelligent Transportation Systems, Vol 16, No 5, pp 2913-2924, 2015 [26] S.N Karimi, “AzureITS: A New Cloud Computing Intelligent Transportation System”, (eds) Algorithms and Architectures for Parallel Processing ICA3PP 2013 Lecture Notes in Computer Science, Vol 8285 Springer, Cham [27] J Joszczuk–Januszewska, “The Advantages of the Use of Cloud Computing in Intelligent Transport Systems”, Mikulski J (eds) Modern Transport Telematics TST 2011 Communications in Computer and Information Science, Vol 239 Springer, Berlin, Heidelberg [28] Y Xiao, C Zhu, “Vehicular fog computing: Vision and challenges”, IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp 6-9, May 2017 [29] O Osanaiye, S Chen, Z Yan, R Lu, K Choo, M Dlodlo, “From cloud to fog computing: A review and a conceptual live VM migration framework”, IEEE Access, pp 8284-8300, May 2017 73 FCU e-Theses & Dissertations (2018) [30] B Tang, Z Chen, G Hefferman, S Pei, W Tao, H He, Q Yang, “Incooperating Intelligent in Fog Computing for Big Data Analysis in Smart Cities,” IEEE Transactions on Industrial Informatics, Vol 13, No 5, pp 2140-2150, May 2017 [31] Y C P Chang, S Chen, T J Wang, Y Lee, “Fog computing node system software architecture and potential applications for NB-IoT industry,” International Computer Symposium, pp 727-730, December 2016 [32] J Shi, L Jin, J Li, Z Fang, “A smart parking system based on NB-IoT and third- party payment platform,” 17th International Symposium on Communications and Information Technologies (ISCIT), pp 1-5, September 2017 [33] L C Png, L Chen, S Liu, W K Peh, “An Arduino-based indoor positioning system (IPAS) using visible light communication and ultrasound,” IEEE International Conference on Consumer Electronics, pp 217-218, September 2014 [34] Y Geng, C G Cassandras, “New Smart Parking System Based on Resource Allocation and Reservations,” IEEE transactions on intellegent transportation system, Vol 14, No 3, pp 1129-1139, September 2013 [35] J T Ang, S W Chin, J H Chin, Z X Choo, Y M Chang, “iSCAPS – Innovative Smart Car Park System integrated with NFC technology and e-Valet function,” IEEE Conference Publications on Computer and Information Technology (WCCIT), pp – 6, June 2013 [36] B M Mahendra, S Sonoli, N Bhat, Raju, T Raghu, “IoT based sensor enabled smart car parking for advanced driver assistance system,” 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp 2188-2193, May 2017 [37] C K Ng, S N Cheong, E Hajimohammadhosseinmemar, W J Yap, “Mobile outdoor parking space detection application,” IEEE 8th Control and System Graduate Research Colloquium (ICSGRC), pp 81-86, August 2017 74 FCU e-Theses & Dissertations (2018) [38] N R N Zadeh, J C Dela, “Smart Urban Parking Detection System,” 6th IEEE International Conference on Control System, Computing and Engineering, pp 370373, November 2016 [39] P Ramaswamy, “IoT smart parking system for reducing green house gas emission,” International Conference on Recent Trends in Information Technology (ICRTIT), pp 1-6, April 2016 [40] T N Pham, M F Tsai, T Y Wu, N Guizani, “An Algorithm for Selection of Effective Error Correction Coding in Wireless Networks based on a Lookup Table Structure,” International Journal of Communication Systems, Vol 30, No 17, June 2017 [41] T N Pham, Y C Kiong, M F Tsai, C C Huang, “A Design of Intelligent Carpool System Taking Advantage of Social Networks,” International Joint Conference on Convergence, pp 1-6, January 2016 [42] M F Tsai, T N Pham, C F Hsiang, C H Chang, “An adaptive solution for images streaming in vehicle networks using MQTT protocol,” 3rd EAI International Conference on IoT as a Service (IoTaaS 2017), Taiwan, September 2017 [43] M F Tsai, T N Pham, B K Hu, F R Hsu, “Improvement in UWB Indoor Positioning by Using Multiple Tags to Filter Positioning Errors,” Journal Internet Technology, March 2018 (Accepted) [44] M F Tsai, T N Pham, C F Hsiang, “Evaluation of the Effect of Variations in Vehicle Velocity and Channel Bandwidth on an Image-Streaming System in Vehicular Networks,” ACM/Springer Mobile Networks & Applications (MONET), March 2018 (Accepted) [45] K Hantrakul, S Sitti, N Tantiharanukul, “Parking lot guidance software based on MQTT protocol,” International Conferene on Digital Arts, Media and Technology (ICDAMT), pp 75-78, March 2017 75 FCU e-Theses & Dissertations (2018) [46] M Karthi, P Harris, “Smart Parking with Reservation in Cloud Based Environment,” IEEE International Conference on Cloud Computing in Emerging Markets (CCEM), pp 164-167, October 2016 [47] N R N Zadeh, J C D Cruz, “Smart Urban parking detection system,” IEEE International Conference on Control System, Computing and Engineering (ICCSCE), pp 370-373, November 2016 [48] I Wigmore: "Internet of Things (IoT)" TechTarget, June 2014 [49] C C Huang, Y S Tai, S J Wang, “Vacant Parking Space Detection Based on Planed Bayesian Hierachical Framework,” IEEE transaction on circuits and systems for video technology, Vol 23, No 9, pp 1598-1610, September 2013 [50] J Chinrungreng, S Dumnin, and R Pongthornseri, “iParking: a Parking Management Framework,” 11th International Conference on ITS Telecommunications, pp 63-68, August 2011 [51] S C Khang, T J Hong, T S Chin, S Wang, “Wireless Mobile-based Shopping Mall Car Parking System (WMCPS),” Services Computing Conference (APSCC), 2010 IEEE Asia-Pacific, pp 573 – 577, December 2010 [52] Z Suryady, G.R Sinniah, S Haseeb, M.T Siddique, M.F.M Ezani, “Rapid development of smart parking system with cloud-based platforms,” The 5th International Conference on Information and Communication Technology for The Muslim World (ICT4M), pp 1-6, November 2014 [53] H H Chang, Y C Chu, Y B Huang, T Y Lin and M F Tsai, “Enhancing the Accuracy of Indoor Positioning by using Multiple Bluetooth Low Energy Beacon Devices,” International Conference on Future Computer and Communication , pp 15 , April 2017 [54] S Kajioka, T Mori, T Uchiya, I Takumi, and H Matsuo, “Experiment of indoor position presumption based on rssi of Bluetooth le beacon,” 3rd IEEE Global Conference on Consumer Electronics (GCCE), pp 337–339, Oct 2014 76 FCU e-Theses & Dissertations (2018) [55] X Y Lin, T W Ho, C C Fang, Z S Yen, B J Yang, and F Lai, “A mobile indoor positioning system based on ibeacon technology,” 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 4970–4973, Aug 2015 [56] M E Rida, F Liu, Y Jadi, A A A Algawhari, and A Askourih, “Indoor location position based on bluetooth signal strength,” 2nd International Conference on Information Science and Control Engineering (ICISCE), pp 769–773, April 2015 [57] M F Tsai, N Chilamkurti, S Zeadally, A Vinel, “MAC-level Forward Error Correction mechanism for minimum error recovery overhead and retransmission,” Journal of Mathematical and Computer Modelling, Vol 53, No 11, pp 2067-2077, 2011 [58] A Ghaida, A L Suhail, K W Louis, T Y Abdallah, “Energy Efficiency Analysis of Adaptive Error Correction in Wireless Sensor Networks,” International Journal of Computer Science, Vol 9, No 2, July 2012 [59] N A Mahiddin, N Safie, E Nadia, S Safei, E Fadzli, “Indoor postion detectetion using wifi and trilateration technique,” Faculty of Informatics, University Sultan ZainalAbidin,Terengganu, Malaysia [60] J.E Hammann, N.A Markovitch, “Introduction to Arena [simulation software],” Simulation Conference Proceedings, pp 519 - 523, December 1995 [61] W David Kelton, Randall Sadowski, Nancy Zupick, “Simulation with Arena,” 6th edition, McGraw-Hill, 2014 [62] Altiok, Tayfur and Benjamin Melamed, “Simulation Modeling and Analysis with ARENA”, Elsevier, Inc., 2007 [63] Rossetti, D Manuel, “Simulation Modeling with Arena”, John Wiley & Sons, Inc., 2010 [64] K Govinda, A P Azad, “End-to-End Service Assurance in IoT MQTT-SN,” 12th Annual IEEE Consumer Communications and Networking Conference (CCNC), pp 290-296, January 2015 77 FCU e-Theses & Dissertations (2018) [65] A Balk, D Maggiorini, M Gerla, M.Y Sanadini, “Adaptive MPEG-4 Video Streaming with Bandwidth Estimation”, Volume 2601 of series Lecture Notes in Computer Science, pp.525-538, 2003 [66] H Yin, C Lin, Q Zhang, “End-to-End stored FGS video transmission based on adaptive smoothing and TCP-friendly rate control,” International Conference on Computer Networks and Mobile Computing, pp 304-310, October 2003 78 FCU e-Theses & Dissertations (2018) ... Development of Intelligent Parking Systems 1.1 Automated parking system 1.2 Intelligent parking assist system 1.3 Classification of intelligent parking assist system 1.4... characteristics of the current intelligent parking assist system 1.1 Automated parking system An early form of intelligent parking assist systems was the automated parking system (APS) As a result... technologies such as BMW’s self -parking system, Mercedes’ parking assistance system, Audi’s guidance parking system and Toyota’s intelligent parking assistance system [8] These systems have some interesting

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