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Journal articles on the topic 'Location tracking'

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Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

GAVRILĂ, Cristinel, Eleonora JELESCU, and Marian ALEXANDRU. "OUTDOOR HYBRID LOCATION TRACKING SYSTEM WITH REMOTE MONITORING." Review of the Air Force Academy 14, no. 1 (May 16, 2016): 85–90. http://dx.doi.org/10.19062/1842-9238.2016.14.1.12.

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2

Kumar, G. Sunderesh, M. Gokulnath, and S. Priya. "Location tracking using Google Cloud Messaging on Android." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 651–54. http://dx.doi.org/10.31142/ijtsrd10925.

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3

Wadhwa, Lalit Kumar, Vishnu Priye, Reshma Muralidharan, Chitralekha Ruikar, and Venancius Norman. "Real Time Location Tracking System for Metal Miners." International Journal of Future Computer and Communication 3, no. 4 (2014): 267–70. http://dx.doi.org/10.7763/ijfcc.2014.v3.309.

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4

Potter, Bruce. "Wireless-based location tracking." Network Security 2003, no. 11 (November 2003): 4–5. http://dx.doi.org/10.1016/s1353-4858(03)01105-x.

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5

Bajaj, R., S. L. Ranaweera, and D. P. Agrawal. "GPS: location-tracking technology." Computer 35, no. 3 (March 2002): 92–94. http://dx.doi.org/10.1109/2.993780.

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6

Bajaj, R., S. L. Ranaweera, and D. P. Agrawal. "GPS: location-tracking technology." Computer 35, no. 4 (2002): 92–94. http://dx.doi.org/10.1109/mc.2002.993780.

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7

Hashim, Norlezah, Fakrulradzi Idris, Tuan Nur Anisa Tuan Ab Aziz, Siti Halma Johari, Rozilawati Mohd Nor, and Norfariza Ab Wahab. "Location tracking using LoRa." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (August 1, 2021): 3123. http://dx.doi.org/10.11591/ijece.v11i4.pp3123-3128.

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<span>Local area network (LAN) as Bluetooth, WiFi and ZigBee are well established technology. The biggest problem with many LAN is the battery consumption and short ranges link budgets. LoRa is a new, private, unlicensed and spread spectrum modulation technique which allows sending low rates at extremely long ranges with minimal power consumption. More importantly, there is no access fee associated with this type of wireless technology. The main idea behind this work is to conduct performance and capability analysis of a currently available LoRa transceiver. We develop a location monitoring system using LoRa and global positioning system (GPS) module and we analyze the detectable range of its data, its battery consumption as well as received signal strength indicator (RSSI). Our deployment experiment demonstrates that the sy<span>stem is able to detect the transmitted data within 290 meters of distances. Using 6 volts of battery AA, the transmission of data still occurred after 24 hours</span>. <span>This project is emphasized a location monitoring system that provide low power usage</span> but long range.</span>

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8

Scarponcini, Paul. "ISO 19133 Tracking and Navigation Standard." Transportation Research Record: Journal of the Transportation Research Board 1935, no. 1 (January 2005): 77–84. http://dx.doi.org/10.1177/0361198105193500109.

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Most information maintained by a department of transportation (DOT) includes a physical location to specify where the data apply. Most often, this location is described with a linear referencing method (LRM). Because no single method is best for all applications, multiple methods are often used in each DOT. Engineers use stationing to locate construction items. Transportation data administrators may use mile point to locate roadway characteristics. Safety officers often use reference markers to locate crashes. TRB has stated that location can serve as an integrating concept for assimilating data from multiple sources. Until now, there were no standards for linear referencing methods; they vary between databases and between DOTs. Consequently, it has been difficult to integrate data from numerous sources by using locations with disparate formats. A new ISO standard should help remedy this situation. The ISO 19133 tracking and navigation standard includes a package for linear reference systems. It generalizes how linear locations are specified to enable translation between locations from different methods. It is based on the generalized model for linear reference, an abstraction of the NCHRP 20-27 conceptual model. According to the standard, locations are formalized as position expressions composed of a method of measurement (LRM), a linear element along which the measure is made, and the measurement itself. Locations can be on the linear element or offset laterally to either side. This paper explains the standard, how it was derived, and its implementation at the Minnesota DOT in its location data manager project.

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9

S, Kumaravel, Premkumar M, Subash J, Rajkumar K, and Sathishkumar K. "Tracking of Soldiers Location in any Environment using Intelligent Tracking and Health Indication System by using RSSI." SIJ Transactions on Computer Science Engineering & its Applications (CSEA) 05, no. 03 (June 19, 2017): 06–10. http://dx.doi.org/10.9756/sijcsea/v5i3/05010090101.

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10

Xiu, Chunbo, Shian Wei, Rongfeng Wan, Yi Cheng, Jing Luo, and Huixin Tian. "CamShift Tracking Method Based on Target Decomposition." Mathematical Problems in Engineering 2015 (2015): 1–20. http://dx.doi.org/10.1155/2015/524120.

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In order to avoid the inaccurate location or the failure tracking caused by the occlusion or the pose variation, a novel tracking method is proposed based on CamShift algorithm by decomposing the target into multiple subtargets for location separately. Distance correlation matrices are constructed by the subtarget sets in the template image and the scene image to evaluate the correctness of the location results. The error locations of the subtargets can be corrected by resolving the optimization function constructed according to the relative positions among the subtargets. The directions and sizes of the correctly located subtargets with CamShift algorithm are updated to reduce the disturbance of the background in the tracking progress. Simulation results show that the method can perform the location and tracking of the target and has better adaptability to the scaling, translation, rotation, and occlusion. Furthermore, the computational cost of the method increases slightly, and its average tracking computational time of the single frame is less than 25 ms, which can meet the real-time requirement of the TV tracking system.

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11

Abd Elrhman, Omer Ali Abubakr, Asim Mohammed Ahmed, Tarig Hyder Mekki, and Ghassan Mohammed Taha. "Android Based Vehicle Tracking System." ADVANCES IN BUSINESS RESEARCH INTERNATIONAL JOURNAL 1, no. 2 (December 31, 2015): 35. http://dx.doi.org/10.24191/abrij.v1i2.10062.

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Android, as an operating system, has provided users with great opportunity to innovate and get things done in a mobile device. This paper presents how to use the GPS technology in Android devices to complete an interactive application which can be used to monitor a fleet of vehicles and display their positions on Google Maps. By using SMS messages, this information can be transmitted to the server. It provides a telemonitoring system for distribution or transportation vehicles owned by a specific company. The whole system is made of two key parts. The first one is the client, which represents an Android application that is installed in the vehicle. During a vehicle’s motion, its location can be reported by SMS messages. The second is the server, which is a computer programme representing a map using Google Maps to show the last known locations of all tracked vehicles. The current system is able to provide the monitoring process from anywhere. The purpose of this system is to use the Android platform to provide the following features: i) Location information (longitude, latitude). ii) Real time tracking using SMS. iii) Map View of all vehicles’ locations. This system is needed by many companies to monitor illegal and unethical use of their vehicles. It also provides assurance that the location of the vehicle is known in the case of robbery.

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12

Hawbani, Ammar, Xingfu Wang, Saleem Karmoshi, Hassan Kuhlani, Aiman Ghannami, Adili Abudukelimu, and Rafia Ghoul. "GLT: Grouping Based Location Tracking for Object Tracking Sensor Networks." Wireless Communications and Mobile Computing 2017 (2017): 1–19. http://dx.doi.org/10.1155/2017/4509697.

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The use of wireless sensor networks (WSN) in tracking applications is growing rapidly. In these applications, the nodes detect, monitor, and track a target, object, or event. In this paper, we consider the problem of tracking mobile objects in wireless sensor networks (WSN). We present a novel tracking model, named Grouping based Location Tracking (GLT), scaling well with the number of nodes and the number of mobile objects. GLT is based on the Grouping Hierarchy Structure, GHS. In GHS, nodes are partitioned into groups (not clusters) according to their maximum covered region (MCR) such that each group contains a number of nodes and a number of leaders. GLT consists of two tiers. The first tier, which is called the Notification Tree (NT), enhances the activation mechanism, the data cleaning mechanism, and the energy balancing mechanism. On the other hand, the second tier, which is called the Hierarchical Spanning Tree (HST), supports the data reporting mechanism and the lifetime prolonging mechanism. Simulations results show that GLT reduces the communication node selections overhead without diminishing object tracking accuracy and achieves a significant energy consumption reduction and network lifetime extension compared with the state-of-the-art approaches.

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13

Yang, Chi-Shian. "Three Dimensional Indoor Location Tracking Viewer." KSII Transactions on Internet and Information Systems 3, no. 1 (February 25, 2009): 108–18. http://dx.doi.org/10.3837/tiis.2009.01.006.

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14

Joo, Won-lee, Hyo-Sun Kim, Yeong-Ah Jung, and Yeon-Chan Hong. "Advanced Indoor Location Tracking Using RFID." Journal of the Korea Academia-Industrial cooperation Society 18, no. 1 (January 31, 2017): 425–30. http://dx.doi.org/10.5762/kais.2017.18.1.425.

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15

Yi-Bing Lin and Shu-Yuen Hwang. "Comparing the PCS location tracking strategies." IEEE Transactions on Vehicular Technology 45, no. 1 (1996): 114–21. http://dx.doi.org/10.1109/25.481828.

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16

Edwards, G., and R. Jayne. "Location Tracking Using Differential Range Measurements." International Journal of Computers and Applications 27, no. 3 (January 2005): 199–205. http://dx.doi.org/10.1080/1206212x.2005.11441768.

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17

Mason, Andrew Michael, Nicholas John Dingle, William John Knottenbelt, Derek Bell, William Buchanan, and Christoph Thuemmler. "Modelling infection spread using location tracking." International Journal of Healthcare Technology and Management 11, no. 6 (2010): 442. http://dx.doi.org/10.1504/ijhtm.2010.036925.

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18

Wang, K., J. M. Liao, and J. M. Chen. "Intelligent location tracking strategy in PCS." IEE Proceedings - Communications 147, no. 1 (2000): 63. http://dx.doi.org/10.1049/ip-com:20000227.

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19

Tabbane, S. "An alternative strategy for location tracking." IEEE Journal on Selected Areas in Communications 13, no. 5 (June 1995): 880–92. http://dx.doi.org/10.1109/49.391746.

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20

Lin, Yi-Bing, and Phone Lin. "Performance modeling of location tracking systems." ACM SIGMOBILE Mobile Computing and Communications Review 2, no. 3 (July 1998): 24–27. http://dx.doi.org/10.1145/1321387.1321389.

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21

Sharma, Jayesh. "Live GPS Location Tracking using GPRS." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (July 15, 2021): 744–48. http://dx.doi.org/10.22214/ijraset.2021.36081.

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In this paper, a real time tracking system is put forward. In this we are going to design a system which is used for tracking and positioning by using (GPS) and (GSM). This design is based on embedded application, which will regularly monitor location and report the status. This tracking device which is used in real time vehicle location tracking is done using the Arduino Uno Atmega328P, SIM800A module and NEO 6M GPS module. For doing so, the Arduino Uno Atmega328P is combined serially to a GSM module and GPS module. The design make use of RS-232 protocol for serial communication between the modems and the microcontroller. A serial driver IC is used for transforming TTL voltage levels to RS-232 voltage levels. The GSM module is used to regularly send the position of the vehicle from distant place. The GPS module that makes use of satellite technology for its navigation system will regularly give information like longitude, latitude, speed, distance travelled etc. For this purpose, Amazon Cloud Services is used for location data handling. The MySQL database is used to reserve all the data of the GPS.

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22

Sawaitul, Sanjay D. "Cross Pose Facial Recognition Method for Tracking any Person’s Location an Approach." International Journal of Trend in Scientific Research and Development Volume-2, Issue-1 (December 31, 2017): 1428–32. http://dx.doi.org/10.31142/ijtsrd7186.

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23

Graham, Dan J., and Robert W. Jeffery. "Location, Location, Location: Eye-Tracking Evidence that Consumers Preferentially View Prominently Positioned Nutrition Information." Journal of the American Dietetic Association 111, no. 11 (November 2011): 1704–11. http://dx.doi.org/10.1016/j.jada.2011.08.005.

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24

Lee, Sungnam, Yohan Chon, and Hojung Cha. "Smartphone-Based Indoor Pedestrian Tracking Using Geo-Magnetic Observations." Mobile Information Systems 9, no. 2 (2013): 123–37. http://dx.doi.org/10.1155/2013/295838.

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With the widespread use of smartphones, the use of location-based services (LBS) with smartphones has become an active research issue. The accurate measurement of user location is necessary to provide LBS. While outdoor locations are easily obtained with GPS, indoor location information is difficult to acquire. Previous work on indoor location tracking systems often relied on infrastructures that are influenced by environmental changes and temporal differences. Several studies have proposed infrastructure-less systems that are independent of the surroundings, but these works generally required non-trivial computation time or energy costs. In this paper, we propose an infrastructure-less pedestrian tracking system in indoor environments. The system uses accelerometers and magnetic sensors in smartphones without pre-installed infrastructure. We reduced the cumulative error of location tracking by geo-magnetic observations at corners and spots with magnetic fluctuations. In addition, we developed a robust estimation model that is tolerant to false positives, as well as a mobility model that reflects the characteristics of multiple sensors. Extensive evaluation in a real environment indicates that our system is accurate and cost-effective.

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25

Yang, Chi-Shian, and Wan-Young Chung. "Location-aware visualization of VRML models in indoor location tracking system." Journal of Sensor Science and Technology 16, no. 3 (May 31, 2007): 220–28. http://dx.doi.org/10.5369/jsst.2007.16.3.220.

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26

Liang, Tao, Jian Bing Guo, and Hai Yan Ren. "Tracking Algorirthm Based on Location Prediction for Wireless Sensor Network." Advanced Materials Research 562-564 (August 2012): 1856–60. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.1856.

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In many wireless sensor networks tracking technologies,location-based pediction target tracking technology have a natural advantage of reducing the energy consumption of nodes in tracking the process. However, the existing location-based prediction target tracking algorithm is not perfect.So Location-Based Pediction Target Tracking Algorirthm (LBP) was proposed. There are three parts in LBP,target position prediction algorithm based self-simlar,target tracking based on dynamic wakeup cluster(DWC),and three levels recovery mechanism.

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27

Swathi, T., and B. S. Malleswari. "Location Based Tracking System for Emergency Services." International Journal of Computer Applications Technology and Research 3, no. 12 (December 23, 2014): 836–38. http://dx.doi.org/10.7753/ijcatr0312.1017.

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28

Sharma, Gokarna, Hari Krishnan, Costas Busch, and Steven R. Brandt. "Near-Optimal Location Tracking Using Sensor Networks." International Journal of Networking and Computing 5, no. 1 (2015): 122–58. http://dx.doi.org/10.15803/ijnc.5.1_122.

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29

Kumar, Saurabh, and Kara M. Kockelman. "Tracking Size, Location, and Interactions of Businesses." Transportation Research Record: Journal of the Transportation Research Board 2077, no. 1 (January 2008): 113–21. http://dx.doi.org/10.3141/2077-15.

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30

A., Sayali, Roshni N., and Vaishali R. "Teacher Location Tracking System in College Campus." International Journal of Computer Applications 163, no. 1 (April 17, 2017): 35–38. http://dx.doi.org/10.5120/ijca2017913454.

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31

Yeh, Shun-yuan, Keng-hao Chang, Chon-in Wu, Hao-hua Chu, and Jane Yung-jen Hsu. "GETA sandals: a footstep location tracking system." Personal and Ubiquitous Computing 11, no. 6 (February 1, 2007): 451–63. http://dx.doi.org/10.1007/s00779-006-0098-z.

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32

Ali Hassen, Ashraf Mohamed. "The proposed System for Indoor Location Tracking." International Journal of Computer Applications Technology and Research 2, no. 6 (November 1, 2013): 690–98. http://dx.doi.org/10.7753/ijcatr0206.1012.

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33

Magas, Michela, and Polina Proutskova. "A Location-Tracking Interface for Ethnomusicological Collections." Journal of New Music Research 42, no. 2 (June 2013): 151–60. http://dx.doi.org/10.1080/09298215.2013.821999.

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34

Liu, Daqian, Wanjun Liu, and Bowen Fei. "Location-matching tracking under convolutional neural network." Journal of Electronic Imaging 27, no. 05 (October 19, 2018): 1. http://dx.doi.org/10.1117/1.jei.27.5.053043.

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35

Paperno, E., and D. Semyonov. "A new method for eye location tracking." IEEE Transactions on Biomedical Engineering 50, no. 10 (October 2003): 1174–79. http://dx.doi.org/10.1109/tbme.2003.817635.

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36

Konovalov, Аleksandr А. "Target tracking algorithm for passive coherent location." IET Radar, Sonar & Navigation 10, no. 7 (August 2016): 1228–33. http://dx.doi.org/10.1049/iet-rsn.2015.0482.

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37

Richard, Mary Raichel, Aleena Maria John, Aneesha T Ranjan, Shara M S, and Brilly Sangeetha. "Survey on Employee Location Tracking System (ELS)." International Journal of Computer Trends and Technology 28, no. 2 (October 25, 2015): 111–13. http://dx.doi.org/10.14445/22312803/ijctt-v28p120.

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38

Eibl, Eva P. S., Ivan Lokmer, Christopher J. Bean, and Eggert Akerlie. "Helicopter location and tracking using seismometer recordings." Geophysical Journal International 209, no. 2 (February 7, 2017): 901–8. http://dx.doi.org/10.1093/gji/ggx048.

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39

Suman, Yogesh, and Navin Rajpal. "Mobile Location Tracking Techniques: Analysis and Evaluation." IETE Technical Review 21, no. 5 (September 2004): 351–56. http://dx.doi.org/10.1080/02564602.2004.11417163.

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40

Kim, Kang-Wook, Jihye Kwon, Chang-Gun Lee, and Junghee Han. "Accurate Indoor Location Tracking Exploiting Ultrasonic Reflections." IEEE Sensors Journal 16, no. 24 (December 15, 2016): 9075–88. http://dx.doi.org/10.1109/jsen.2016.2617398.

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41

Gruteser, M., and Xuan Liu. "Protecting privacy in continuous location-tracking applications." IEEE Security & Privacy Magazine 2, no. 2 (March 2004): 28–34. http://dx.doi.org/10.1109/msecp.2004.1281242.

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42

Kizakevich, Paul N., Michael McCartney, Ann Zhang, Robert Furberg, Steve Duncan, and Roy Whitmore. "Indoor Location Tracking Using Bluetooth Proximity Beacons." Epidemiology 17, Suppl (November 2006): S39. http://dx.doi.org/10.1097/00001648-200611001-00061.

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43

Lai, Yeong-Lin, and Jay Cheng. "A Cloud-Storage RFID Location Tracking System." IEEE Transactions on Magnetics 50, no. 7 (July 2014): 1–4. http://dx.doi.org/10.1109/tmag.2014.2303810.

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44

Patil, Abhishek, Jonathan Munson, David Wood, and Alan Cole. "Bluebot: Asset tracking via robotic location crawling." Computer Communications 31, no. 6 (April 2008): 1067–77. http://dx.doi.org/10.1016/j.comcom.2008.01.041.

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45

Yongqiang, He, Qin Qin, and Jun-peng Wang. "Game Theory Based Location Smoothing in Wireless Sensor Networks." International Journal of Online Engineering (iJOE) 12, no. 03 (March 31, 2016): 16. http://dx.doi.org/10.3991/ijoe.v12i03.5400.

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Abstract: Location estimation of mobile target is an important research in wireless sensor networks. However, the phenomenon of non line of sight affects the accuracy of location estimating algorithms greatly. In order to improve the accuracy of location estimation of mobile targets, we proposed a game theory based location method algorithm in wireless sensor networks. In the proposed method, we first estimate the initial locations of mobile target with a support vector regression model, and then use game theory to smooth the already estimated locations. In the game model, game based filter and noise generator are two game rivals. The game filter aims to minimize the objective function of the game model, and the noise generator aims to maximize the same objective function. We propose a differential game theory based algorithm for solving the optimal resolution. The experiments show that, the proposed method is more powerful, and can be used to mobile target locating and tracking.

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46

Etherington, Thomas R., Stéphane Pietravalle, and Dave P. Cowan. "Visualising uncertainty in radio-telemetry wildlife-tracking data to aid better study design." Wildlife Research 37, no. 6 (2010): 482. http://dx.doi.org/10.1071/wr09151.

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Context. Animal movements recorded by radio-telemetry produce a series of spatio-temporal point-location estimates that sample an animal’s continuous track. However, uncertainty in the point locations themselves, and uncertainty of how the animal moved between locations, could be large enough to render data unsuitable for some purposes. Aims. Our objective was to develop a method that would visualise these uncertainties by calculating the maximum range of possible movements around the sampled point locations, given different probabilities of point-location error and animal-movement speed. By visualising the uncertainties, we hope to aid better study design. Methods. To quantify the probability of different levels of uncertainty, we use a probability density function (PDF) of point-location error and movement speed. By choosing a cut-off probability on each PDF, ellipses can be drawn for consecutive pairs of point-location estimates, which when combined show the maximum range of possible movements at those specific cut-off probabilities of location error and movement speed. We demonstrate how to establish the PDFs and apply the methodology by using an example of grizzly bear (Ursus arctos) radio-telemetry data. Key results. By establishing a range of probability cut-offs within each PDF, it is possible to visualise the area within which a grizzly bear could have moved under different combinations of those cut-offs. Conclusions. Comparison of the potential maximum range of possible movements, under different combinations of probability cut-offs, enables the relative importance of each source of uncertainty to be evaluated. Acquiring data from intense sampling would be particularly useful in providing robust information on likely movement speeds. Implications. This approach could be used during study design and testing to prioritise efforts towards reducing uncertainty in the point-location estimates, and uncertainty of where the animal moved between locations to ensure the radio-telemetry method used is appropriate for the study’s objectives.

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47

Ullah, Mohib, Maqsood Mahmud, Habib Ullah, Kashif Ahmad, Ali Shariq Imran, and Faouzi Alaya Cheikh. "HEAD BASED TRACKING." Electronic Imaging 2020, no. 6 (January 26, 2020): 74–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.6.iriacv-072.

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For tracking multiple targets in a scene, the most common approach is to represent the target in a bounding box and track the whole box as a single entity. However, in the case of humans, the body goes through complex articulation and occlusion that severely deteriorate the tracking performance. In this paper, we argue that instead of tracking the whole body of a target, if we focus on a relatively rigid body organ, better tracking results can be achieved. Based on this assumption, we followed the tracking-by-detection paradigm and generated the target hypothesis of only the spatial locations of heads in every frame. After the localization of head location, a constant velocity motion model is used for the temporal evolution of the targets in the visual scene. For associating the targets in the consecutive frames, combinatorial optimization is used that associates the corresponding targets in a greedy fashion. Qualitative results are evaluated on four challenging video surveillance dataset and promising results has been achieved.

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48

Lee, Kwang-Pyo, Hyun-Soo Lee, Moonseo Park, Hyunsoo Kim, and Sangwon Han. "A REAL-TIME LOCATION-BASED CONSTRUCTION LABOR SAFETY MANAGEMENT SYSTEM." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 20, no. 5 (July 4, 2014): 724–36. http://dx.doi.org/10.3846/13923730.2013.802728.

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The construction industry continues to record a high number of accidents compared to other industries. Furthermore, the ramifications of construction accidents are growing in terms of both economic loss and loss of life with trends toward larger-scale, more complex projects. For this reason, there is an increasing awareness of the importance of safety management in the construction industry, and the need for more effective safety management techniques. This paper introduces a real-time location-based construction labor safety management system that tracks and visualizes workers’ locations in real-time and sends early warnings to endangered workers. The system is developed by integrating: a real-time locating system (RTLS) for tracking of workers’ location; a location monitoring system for mapping the workers location on a computerized building model; and alarm technology for sending early warnings. The developed system has been applied to an apartment project and an RTLS technology test center in Korea, and proved to be effective in tracking and monitoring workers in real-time and preventing construction accidents. It is envisioned that the developed system will enable proactive construction safety management in South Korea and the methodologies developed in this study will be applicable to other contexts with minimal customization.

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49

Chiang, Luciano E., and Jorge E. Jacob. "Low Cost Sun-Tracking Photovoltaic Panel." International Journal of Mechanical Engineering Education 26, no. 4 (October 1998): 293–302. http://dx.doi.org/10.1177/030641909802600403.

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A photovoltaic panel (PVP) incorporating a sun-tracking system was designed, built and tested. The performance improvement obtained due to the two-axis tracking system justifies the additional cost, which is minimized by using off-the-shelf components in a compact and reliable configuration. The PVP charges two 6-V batteries which in turn are used to feed the control system using only a small proportion of the converted solar energy. Thus the entire system works autonomously and independent of geographic location. Its convenience is therefore suggested for isolated and remote low-power applications. In particular it is intended for use in desertic locations in northern Chile and, by extension, in geographically similar locations in other developing countries.

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50

Al-Naima, Fawzi M., Ramzy S. Ali, and Ahmed J. Abid. "Design of an Embedded Solar Tracking System Based on GPS and Astronomical Equations." International Journal of Information Technology and Web Engineering 9, no. 1 (January 2014): 12–30. http://dx.doi.org/10.4018/ijitwe.2014010102.

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This article presents the design of a reliable, accurate, and easy to install solar dual axis tracking system. The system utilizes the GPS for fixing the time, date and location in terms of longitude and latitude. Approximations having high accuracy of the astronomical equations to represent the declination angle and the equation of time are selected to determine the sun locations needed by the designed tracking system in any chosen location on earth. The proposed system is standalone, accurate, durable, reliable, and cost efficient. Annual energy assessments of the system are also given.

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