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Hussein, Sherif Kamel
- Wi-Fi Microcontroller based Smart Menu
Abstract Views :202 |
PDF Views:122
Authors
Affiliations
1 Department of Communications and Computer Engineering, University for Modern Sciences and Arts, Giza, EG
1 Department of Communications and Computer Engineering, University for Modern Sciences and Arts, Giza, EG
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 11, No 1 (2019), Pagination: 61-76Abstract
Nowadays the technology is embedded in every utilized application to increase the reliability and minimize the human errors caused by the conventional methods. The traditional methods usually been used in restaurant is by taking the customer’s orders and write it down on a piece of paper. Many ordering systems have been proposed in order to solve this issue. In this paper a newly proposed model called Smart Menu is designed basedon the Wi-Fi technology as the communication medium and Peripheral Interface Controller ( ARM Cortex – m7 processor ) as the hardware which implements faster ordering system. The aim for the smart menu model is to build and design both hardware and software for the ordering and delivering system at restaurants by using TFT LCD connected to the kitchen through WI-Fi technology. Result shows that the hardware and software are successfully functional and able to be used as a smart ordering system. The proposed model is able to handle the lack number of the workers, reduce the lateness and the error on ordering foods by the customers.Keywords
Thick Film Transistor (TFT), Advanced Risk Machine Microcontroller (ARM) cortex-M7, wireless Fidelity (Wi-Fi), Graphically Liquid Crystal Display (GLCD), Secure Digital (SD) Card.References
- V. Chandra Sekhara Santosh, A. Shanker“ The Unique Restaurant Interactive Ordering System System”, The International Journal of Engineering and Science, Vol.4, No.8, pp.644-650, pp.644 Aug 2014.
- B.Vinodhini, K.Abinaya, R.Roja, M.Rajeshwari “Wireless Two-way Two way Restaurant Ordering System via Touch Screen” The International Journal Of Engineering And Science, Science, Vol.3, No.7, pp. 01 01-05, 2014.
- B.Vinodhini, K.Abinaya, R.Roja, M.Rajeshwari,” Design and Development of an E- Restaurant using RTOS programming to Enhance the Quality of Service”, International Journal of Inventions in Electronics & Electrical Engine Engineering, Vol.1, pp. 1-9, Jan-Dec 2015.
- Dr. ShaikMeeravali ,K.Sudhakar, M.Swathi “Design of the Restaurant Self-Ordering Self Ordering System Based on ZigBee Technology. (Using ARM cortex microcontroller and color GLCD)” International Journal of Engineering Research & Technology, Vol.2, No.9, pp.730 pp.730-733, Sep 2013.
- Venmathi.V, Eswari.M, Jasmine Jenita.R, Jayasri.S, Kavitha.R “Touch Screen Based Advanced Menu Display and Ordering System for Restaurants” International Journal of Engineering Science and Computing, Vol.6,.6, No.4, pp.3482-3485, pp.3482 Apr 2016.
- N. M. Z.Hashim, N. A. Ali, A.S. Jaafar, N.R.Mohamad, L.Salahuddin, N. A. Ishak, “Smart Ordering System via Bluetooth”, International Journal of Computer Trends and Technology,pp.2253 Technology,pp.22532256,2013.
- Gracia, D. and Yiu,, J. (2015) Exploring the ARM® Cortex® M7 Core: Providing Adaptability for the Internet of Tomorrow. Available at: http://www.nxp.com/assets/documents/data/en/whitepapers/CORTEXM7WP.pdf
- Lagerstam, C. (2016) Newhaven display international, Inc., high quality standard and custom OLEDs, LCDs and VFDs. Available at: http://www.newhavendisplay.com/app_notes/TPcompare.pdf
- A Novel Prototype Model for Swarm Mobile Robot Navigation Based Fuzzy Logic Controller
Abstract Views :207 |
PDF Views:115
Authors
Affiliations
1 Department of Communications and Computer Engineering October University for Modern Sciences and Arts, EG
2 Arab East Colleges for Graduate Studies,-Riyadh, SA
1 Department of Communications and Computer Engineering October University for Modern Sciences and Arts, EG
2 Arab East Colleges for Graduate Studies,-Riyadh, SA
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 11, No 2 (2019), Pagination: 63-77Abstract
Autonomous mobile robots have been used to carry out different tasks without continuous human guidance. To achieve the tasks, they must be able to navigate and avoid different kinds of obstacles that faced them. Navigation means that the robot can move through the environment to reach a destination. Obstacles avoidance considers a challenge which robot must overcome. In this work, the authors propose an efficient technique for obstacles avoidance through navigation of swarm mobile robot in an unstructured environment. All robots cooperate with each other to avoid obstacles. The robots detect the obstacles position around them and store their positions in shared memory. By accessing the shared memory, the other robots of the swarm can avoid the detected obstacles when they face them. To implement this idea, the Authors used a MATLAB® and V-REP® (Virtual Robot Experimentation Platform).Keywords
Mobile Robot, Swarm Robot, Navigation, Obstacle Avoidance, Fuzzy Logic Controller.References
- Murphy, R. 2000. Introduction to AI robotics. MIT press.
- Niku, S. 2010. Introduction to robotics. John Wiley & Sons.
- Nehmzow, Ulrich. 2012. Mobile robotics : A practical introduction. London: Praxis.
- Alves S. F., Rosario J. M., Ferasoli Filho H., Rincon L. K., & Yamasaki R. A. 2011. Conceptual bases of robot navigation modeling, control and applications. In Advances in Robot Navigation. InTech.
- Siegwart, Roland, Illah Reza Nourbakhsh, and Davide Scaramuzza. 2014;2011;. Introduction to autonomous mobile robots. 2nd ed. Cambridge: MIT Press.
- Goris, K. 2005. Autonomous mobile robot mechanical design. VrijeUniversiteitBrussel, Engineering Degree Thesis, Brussels, Belgium.
- Özkil A. G. 2009. Technical Report on Autonomous Mobile Robot Navigation.
- I brahim, M. Y., and A. Fernandes. 2004. Study on mobile robot navigation techniques.
- Nirmala, G., Dr S. Geetha, and Dr S. Selvakumar. 2017. Mobile robot localization and navigation in artificial intelligence: Survey. Computational Methods in Social Sciences 4 (2): 12-22.
- Beni, Gerardo. 2005. From swarm intelligence to swarm robotics. In . Vol. 3342, 1-9. Berlin, Heidelberg: Springer Berlin Heidelberg.
- Şahin, Erol. 2005. Swarm robotics: From sources of inspiration to domains of application. In . Vol. 3342, 10-20. Berlin, Heidelberg: Springer Berlin Heidelberg.
- Brutschy, A. 2009. Task allocation in swarm robotics. Towards a method for selforganized allocation to complex tasks. University Libre de Brux-elles, 1050 Bruxelles, Belgium, Technical Report TRlIRIDIA12009–007, 52009.
- Rashid, Razif, Irraivan Elamvazuthi, Mumtaj Begam, and M. Arrofiq. 2010. Differential drive wheeled mobile robot (WMR) control using fuzzy logic techniques.
- Rekik, Chokri, Mohamed Jallouli, and Nabil Derbel. 2009. Integrated genetic algorithms and fuzzy control approach for optimization mobile robot navigation.
- Faisal, Mohammed, Ramdane Hedjar, Mansour Al Sulaiman, and Khalid Al-Mutib. 2013. Fuzzy logic navigation and obstacle avoidance by a mobile robot in an unknown dynamic environment. International Journal of Advanced Robotic Systems 10 (1): 37.
- Narvydas, G., R. Simutis, and V. Raudonis. 2007. Autonomous mobile robot control using fuzzy logic and genetic algorithm.
- Güzel, Mehmet Serdar, Mehmet Kara, and Mehmet Sıtkı Beyazkılıç. 2017. An adaptive framework for mobile robot navigation. Adaptive Behavior 25 (1): 30-9.
- Hayes, A. T., and P. Dormiani-Tabatabaei. 2002. Self-organized flocking with agent failure: Off-line optimization and demonstration with real robots.
- Nga Le Thi Thuy, and Thang Nguyen Trong. 2017. The multitasking system of swarm robot based on null-space-behavioral behavioral control combined with fuzzy logic. Micromachines 8 (12): 357.
- Ducatelle,, Frederick, Gianni A. Di Caro, Carlo Pinciroli, Francesco Mondada, and Luca Gambardella. 2011. Communication assisted navigation in robotic swarms: Self-organization Self organization and cooperation.
- Sugawara, K., T. Kazama, and T. Watanabe. 2004. Foraging behavior of interacting robots with virtual pheromone.
- Batalin, Maxim A., and Gaurav S. Sukhatme. 2004. Coverage, exploration and deployment by a mobile robot and communication network. Telecommunication Systems 26 (2): 181-96. 181 96.
- Houcque, David. "Introduction to Matlab for engineering students." students Northwestern University (2005): 1-64.
- “Math Works”, [Online]. Available: https://www.mathworks.com. Accessed: September 2018.
- “Coppelia Robotics”, [Online]. Available: http://www.coppeliarobotics.com. Accessed: September 2018.
- Mondada, F., Franzi, E., & Guignard, A.1999. The development of khepera. In Experiments with the Mini-Robot Khepera, Proceedings of the First International Khepera Workshop No. LSRO LSRO-CONF2006-060: 7-14.
- “K Team ”, [Online]. Available: https://www.k-team.com.Accessed: March 2018
- Increasing the Investment's Opportunities in Kingdom of Saudi Arabia by Studying and Analyzing the Social Media Data
Abstract Views :119 |
PDF Views:73
Authors
Affiliations
1 Department of Communications and Computer Engineering, October University for Modern Sciences and Arts, Giza, EG
2 Master of Computer Science, Arab East Colleges for Graduate Studies, Riyadh, SA
1 Department of Communications and Computer Engineering, October University for Modern Sciences and Arts, Giza, EG
2 Master of Computer Science, Arab East Colleges for Graduate Studies, Riyadh, SA
Source
AIRCC's International Journal of Computer Science and Information Technology, Vol 14, No 5 (2022), Pagination: 29-44Abstract
Social networking sites are a significant source of information to know the behavior of users and to know what is occupying society of all ages and accordingly helpful information can be provided to specialists and decision-makers. According to official sources, 98.43% of Saudi youth use social networking sites. The study and analysis of social media data are done to provide the necessary information to increase investment opportunities within the Kingdom of Saudi Arabia, by studying and analyzing what people occupy on the communication sites through their tweets about the labor market and investment. Given the huge volume of data and also its randomness, a survey of the data will be done and collected from through keywords, the priority of arranging the data, and recording it as (positive - negative - mixed). The study analysis and conclusion will be based on data-mining and its techniques of analysis and deduction.Keywords
Big Data, Data Analytics, Data Mining, Social Media, Kdd, Facebook, Twitter, Instagram.References
- J. Han, M. Kamber, J. Pei, "Data Mining Concepts And Techniques", Diego, 2011.
- Daniel T. Larose, "Discovering Knowledge In Data An Introduction To Data Mining", 2005.
- R. Zafarani, M.A. Abbasi, And H. Liu, "Social Media Mining: An Introduction", Cambridge University Press,16.
- J. Han, M. Kamber, and J. Pei, "Data Mining: Concepts and Techniques", Morgan Kaufmann, San Francisco, 2011.
- P.N. Tan, M. Steinbach And V. Kumar, "Introduction To Data Mining", Pearson Addison Wesley, Boston, 2006.
- Prabhjot Kaura, Anu Goyal, Kavita Sharma, Pritia, Anupriya Jain, Prasenjit Banerjee, "Social Media In Data Mining Review Paper", Manav Rachna International University, Faridabad,India,2018.
- Amali Pushpam, Gnana Jayanthi Joseph, "Over View On Data Mining In Social Media", International Journal Of Computer Sciences And Engineering,November 2017.
- Annie Syrien, M.Hanumanthappa, "A Study On Social Network Analysis Through Data Mining Techniques – A Detailed Survey", International Journal Of Advanced Research In Computer And Communication Engineering,Vol. 5, Special Issue 2, October 2016.
- D.Kavitha, Mca, M.Phi., "Survey Of Data Mining Techniques For Social Networking Websites", Assistant Professor, Kg College Of Arts And Science, Coimbatore,Ijcsmc, Vol. 6, Issue. 4, April 2017, Pg.418 – 426.
- Flow Chart Definition, Https://Www.Edrawsoft.Com/Flowchart-Definition.Html?Gclid=Cj0kcqjwjpacbhdkarisaiszn7qrrt9bx9cakidk2mpap2mfkgs8x4bfgw-Av3mqvcfdcdn7ctb720kaagjfealw_Wcb,2020.
- Unified Modeling Language (Uml) | SequenceDiagrams,Https://Www.Geeksforgeeks.Org/Unified-Modeling-Language-Uml-Sequence-Diagrams/.
- What Is Class Diagram?,Https://Www.Visual-Paradigm.Com/Guide/Uml-Unified-Modeling-Language/What-Is-Class-Diagram/.