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### Study of indoor positioning algorithms based on light fidelity

1. Seminar III Presentation On “Study of Indoor Positioning Algorithms based on Light Fidelity ” By Jordan Choudhari (SY ME-IT) Guide Dr. R . N. Phursule 6/22/2020 1
2.  Introduction  Aim and Objectives  Literature Survey  Comparative Study  Comparison Analysys  Applications  Common Misconceptions  Conclusion  References 6/22/2020 2
3. Moving comfortably in new environment is not possible because we are new to it. If we are having knowledge about that environment than it may be possible, Hence to overcome this factor we are proposing a new concept(rather than Wi-Fi) in which we can track our location with the help of our smartphone. Our location would be traced with the help of Li-Fi system. Introduction 6/22/2020 3
4. Introduction Figure 1: VLC frequency spectrum [1] 6/22/2020 4
5. Aim : To study different algorithms for Indoor Positioning system using light –Fidelity (Li-Fi). Objectives : i. Study various proposed algorithms for LiFi ii. Provide real time location and guide users to their destination within reasonable distance using Light Fidelity (Li-Fi). 6/22/2020 5
6. Paper 1: Indoor Positioning System Using Wi-Fi & Bluetooth Low Energy Technology  INDOOR POSITIONING SYSTEM Wireless indoor positioning system is a system to locate objects or people inside a building using radio waves, magnetic fields, acoustic signals, or other sensory information collected by mobile devices  RSS SCHEME FOR INDOOR NAVIGATION It is most common for positioning schemes to estimate the unknown receiver’s position by exploiting the geometric relations between transmitters and the receiver. Estimating Received Signal Strength (RSS), Angle of Arrival (AoA) and timing information such as Time of Arrival (ToA), Time Difference of Arrival (TDoA). 6/22/2020 6
7. Paper 1: Indoor Positioning System Using Wi-Fi & Bluetooth Low Energy Technology  WI-FI BASED INDOOR POSITIONING Figure 2: Trilateration[2] By using dense network of access points, taking RSSI measurements over Wi-Fi signals, determining distance of user’s device from individual access points, and finally applying trilateration 6/22/2020 7
8. Literature Survey(1/8) 1. Visible Light communications based indoor positioning via compressed sensing [2] Author: Kristina Gligorić´, Manisha Ajmani, Dejan Vukobratović´ andSinan Sinanovic´ Year and Publication: IEEE COMMUNICATIONS LETTERS, VOL. 22, NO. 7, JULY 2018 Methodology: LEDs transmitting their positional information simultaneously and at the user's device, installed at a fixed location inside the infrastructure and continuously transmit their location. Mobile optical receiver comes in the vicinity of the LED transmitter, it receives an optical signal and it decodes the LED position to locate its own position. 6/22/2020 8
9. Literature Survey(2/8) 2. Indoor Position by LED Visible Light communication and Image Sensors [3] Author: Mohammad Shaifur Rahman, Md. Mejbaul Haque, Ki-Doo Kim Year and Publication: International Journal of Electrical and Computer Engineering (IJECE), December 2017. Methodology: They proposed high precision indoor positioning using lightning LEDs. LEDs from array transmit their 3D coordinate (x, y, and z) information At receiver side sensor used for receiving the light signal and each pixel can act as an individual photosensor and multiple signals calculated and an unknown 3D coordinate of the point is estimated 6/22/2020 9
10. Literature Survey(3/8) Fig 3 . Procedure of POSITIONAL ALGORITHM WITH IMAGE SENSORS [3] 6/22/2020 10
11. Literature Survey(4/8) 3. Epsilon: A Visible Light Based Positioning System [4] Author: Liqun Li, Microsoft Research, Beijing; Pan Hu, University of Massachusetts Amherst; Chunyi Peng Year and Publication: 11th USENIX Symp. Apr. 2018. Methodology: Fig 4. Localization in Elpson 6/22/2020 11
12. Literature Survey(5/8) 4. TDoA Based Indoor Visible Light Positioning Systems [5] Author: Qu Wang, Trong-Hop Do, Junho Hwang, Myungsik Yoo Year and Publication: ICUFN 2018 Fig.5. TDoA Based Positioning 6/22/2020 12
13. Literature Survey(6/8) 5. Two-Phase Framework for Indoor Positioning Systems Using Visible Light [6] Author: Gregary B. Prince and Thomas D. C. Little Year and Publication: Sensors Article, Published: 12 June 2018 . Methodology: They proposed an algorithmic framework for indoor positioning. These framework works have two phases; A. Coarse Phase – estimate weighted proximity as less as one beacons within Mobile Terminals (MTs). A. Fine phase- where the positioning algorithm performs beacons within MTs FoV- Triangulation Based Positioning Using AoA and Trilateration Based Positioning Using ToF or RSS are evaluated. 6/22/2020 13
14. Literature Survey(7/8) Fig 6. Coarse Phase proximity method 6/22/2020 14
15. Literature Survey(8/8) Fig 7. Fine phase trilateration Framework 6/22/2020 15
16. Parameter Wi-Fi Li-Fi Spectrum Used RF Visible Light Standard IEEE 802.11 IEEE 802.15.7 Range Based on Radio propagation & interference ( < 300 m) Based on Light Intensity (< 10m) Data Transfer Rate* Low(100 Mbps – 1 Gbps) Very High (224 Gbps) Power Consumption High Low Cost High Low Bandwidth Limited Unlimited 16 Table 1: Comparison of Wi-Fi and Li-Fi 6/22/2020
17. COMPARISON ANALYSIS Features [2] [3] [5] [6] [7] [8] Transmitter N LED sources Array of 4 LEDs Visible light LED Single LED LED panel anchor (LED) luminaries Receiver User device with photodiode (PD) Image sensors Mobile phone smartphone with a light sensor inexpensive photo diode VLC-capable MT Positioning type 2D 3D 2D 3D 2D 2D Positioning algorithm CS-based VLC positioning geometric relations of the LED image Distances. trilateration algorithm RSSI ,LIPOS algorithm TDoA algorithm Two phase algorithm (Fine phase& coarse phase Simulation - Matlab Simulation moderate-scale model-based Simulations. Model based Simulation Matlab Simulation Monte Carlo simulation, CandLES simulation Synchronization needed Y Y Y Y N Y Accuracy MPE ∼ 0.4m to ∼ 0.27m, 0-0.15m if pixel size is 36´10-6 m. ~0.4m 1.8m avg 3.59 cm OOK: 57.5 cm, 2-PPM: 56.5 cm, and 4-PAM: 56.3 cm Table 2. Comparison between different literature papers 6/22/2020 17
18.  Airplanes  Hospitals  Petrochemical industry  Nuclear power plants  In home and office appliances  Smart lighting  Vehicle and traffic lights:  Underwater  In health surveillance Figure 5 :Some of viable applications for LiFi [9] 6/22/2020 18
19.  Lights cannot be dimmed  The flickering light is disturbing for human eye  VLC is unidirectional downlink  Existing lights have to be replaced  This is exclusively a LoS (line-of-sight) technology  Interference from Sunlight 6/22/2020 19
20. Conclusion Visible light frequency based Light Fidelity (Li-Fi) provides a better alternative for traditional technologies for Indoor Positioning System. This technology is not only widely available but also license free. Thus, this comparative study provides us better insight on the Li-Fi technology Li-Fi system provides a better alternative solution to Wi-Fi based positioning system with accuracy in indoor positioning with low energy consumption and provide real time location and guide users to their destination within reasonable distance using Light Fidelity (Li-Fi). 6/22/2020 20
21. References [1]V. Varshney, R. K. Goel and M. A. Qadeer, "Indoor positioning system using Wi-Fi & Bluetooth Low Energy technology," 2016 Thirteenth International Conference on Wireless and Optical Communications Networks (WOCN), Hyderabad, 2016, pp. 1-6. [2]K. Gligorić, M. Ajmani, D. Vukobratović and S. Sinanović, "Visible Light Communications- Based Indoor Positioning via Compressed Sensing," in IEEE Communications Letters, vol. 22, no. 7, pp. 1410-1413, July 2018. [3] M. S. Rahman, M. M. Haque, and K.-D. Kim. Indoor positioning by led visible light communication and image sensors. International Journal of Electrical and Computer Engineering (IJECE), 1(2), 2011. [4] L. Li P. Hu C. Peng G. Shen F. Zhao "Epsilon: A visible light based positioning system" Proc. 11th USENIX Symp. NSDI pp. 331-343 Apr. 2014 [online] Available: [5] Q. Wang, H. Luo, A. Men, F. Zhao, X. Gao, J. Wei, Y. Zhang, and Y. Huang, “Light positioning: A high-accuracy visible light indoor positioning system based on attitude identification and propagation model,” Int. J. of Distributed Sensor Networks, vol. 14, no. 2, pp. 1–15, Jan. 2018. [6] D. Trong-Hop H. Junho Y. Myungsik "TDoA based indoor visible light positioning systems" 2013 Fifth Int. Conf. on Ubiquitous and Future Networks (ICUFN) pp. 456-458 2013. [8] G. Prince and T. Little, “Two-Phase Framework for Indoor Positioning Systems Using Visible Light,” Sensors, vol. 18, no. 6, p. 1917, 2018. [7] L. I. Albraheem, L. H. Alhudaithy, A. A. Aljaser, M. R. Aldhafian and G. M. Bahliwah, "Toward Designing a Li-Fi-Based Hierarchical IoT Architecture," in IEEE Access, vol. 6, pp. 40811-40825,2018. 6/22/2020 21
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