Avoidance of Traffic Congestion In Regional Transport Office
Research Paper | Journal Paper
Vol.7 , Issue.1 , pp.894-898, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.894898
Abstract
Presently a day’s Driving permit framework is an extremely troublesome assignment for the legislature to display. Regularly, in driving test a hopeful connected for permit need to drive over a shut circle way before the experts. The competitor needs to roll over the way with no help over the land surface and on the off chance that he neglects to do he will be precluded. For that, the experts watch applicant physically. In our framework to decrease RTO permit process through zigbee innovation. The proposed innovative answer for the computerization of existing manual test process empowers the disposal of human intercession and enhances the driving test exactness while running paperless with Driving Skill Evaluation System. As a commitment to the general public this innovative arrangement can decrease the quantity of street mishaps in light of the fact that most mishaps results from absence of arranging, expectation and control which are very subject to driving expertise.
Key-Words / Index Term
ZIGBEE, RTO, Driving Test
References
[1] Yan Lin, Senior Member, IEEE, Gary A. Jordan, Mark Sanford, Jinxiang Zhu, Member, IEEE, and William H. Babcock, “Economic Analysis of Establishing Regional Transmission Organization and Standard Market Design in the Southeast”, IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. NO. 4, NOVEMBER 2006.
[2] Juszkiewicz," The use of Adobe Flex in combination with Java EE technology on the example of ticket booking system", in CAD Systems in Microelectronics (CADSM), 2011, pp. 317 – 320.
[3] Wan-Mi Chen, Yu-Cheng Chen, "Web design and implementation for remote control", in Intelligent Control and Automation (WCICA), 2012.
[4] Xiaosheng Yu, Yichang, China Cai Yi, "Design and Implementation of the Website Based on PHP & MYSQL", in E-Product E-Service and EEntertainment (ICEEE), 2010.
[5] Bazghandi, "Web Database Connectivity Methods (using Mysql) in Windows Platform", in Information and Communication Technologies, 2009, pp. 3577 -3581.
[6] Norul Huda Yusof, Rosilah Hassan, "Flash Notes and Easy Electronic Software (EES): New Technique to Improve Digital Logic Design Learning", in International Conference on Electrical Engineering and Informatics, 2011.
[7] Narayan S. Rau, “Issues in the Path Toward an RTO and Standard Markets”, IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 18, NO. 2, MAY 2003.
Citation
M. Shanthipriya, Smitha Elsa Peter, "Avoidance of Traffic Congestion In Regional Transport Office," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.894-898, 2019.
Active Power Loss Reduction by Particle Swarm Optimization Algorithm
Review Paper | Journal Paper
Vol.7 , Issue.1 , pp.904-906, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.904906
Abstract
This work presents Particle swarm optimization (PSO) algorithm for solving optimal reactive power problem. PSO is an optimization tool based on a population, where each member is seen as a particle, and each particle is a potential solution to the problem under analysis. Each particle in PSO has a randomized velocity associated to it, which moves through the space of the problem. However, unlike genetic algorithms, PSO does not have operators, such as crossover and mutation. PSO does not implement the survival of the fittest individuals; rather, it implements the simulation of social behaviour. Projected Particle swarm optimization (PSO) algorithm has been tested in standard IEEE 300 bus system and simulation results show the better performance of the proposed algorithm in reducing the real power loss.
Key-Words / Index Term
Optimal reactive power, Transmission loss, particle swarm optimization
References
[1] O.Alsac, B. Scott, “Optimal load flow with steady state security”,IEEE Transaction. PAS -1973, pp. 745-751.
[2] Lee K Y ,Paru Y M , Oritz J L –A united approach to optimal real and reactive power dispatch , IEEE Transactions on power Apparatus and systems 1985: PAS-104 : 1147-1153
[3] A.Monticelli , M .V.F Pereira ,and S. Granville , “Security constrained optimal power flow with post contingency corrective rescheduling” , IEEE Transactions on Power Systems :PWRS-2, No. 1, pp.175-182.,1987.
[4] Deeb N ,Shahidehpur S.M ,Linear reactive power optimization in a large power network using the decomposition approach. IEEE Transactions on power system 1990: 5(2) : 428-435
[5] E. Hobson ,’Network consrained reactive power control using linear programming, ‘ IEEE Transactions on power systems PAS -99 (4) ,pp 868-877, 1980
[6] K.Y Lee ,Y.M Park , and J.L Oritz, “Fuel –cost optimization for both real and reactive power dispatches” , IEE Proc; 131C,(3), pp.85-93.
[7] M.K. Mangoli, and K.Y. Lee, “Optimal real and reactive power control using linear programming” , Electr.Power Syst.Res, Vol.26, pp.1-10,1993.
[8] Berizzi.C.Bovo,M.Merlo,andM.Delfanti,(2012), “A GA approach to compare ORPF objective functions including secondary voltage regulation,” Electric Power Systems Research, vol. 84, no. 1, pp. 187 – 194.
[9] D. Devaraj, and B. Yeganarayana, “Genetic algorithm based optimal power flow for security enhancement”, IEE proc-Generation.Transmission and. Distribution; 152, 6 November 2005.
[10] C.A. Canizares , A.C.Z.de Souza and V.H. Quintana , “ Comparison of performance indices for detection of proximity to voltage collapse ,’’ vol. 11. no.3 , pp.1441-1450, Aug 1996 .
[11] Kennedy JF, Eberhart RC. Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, Perth, Australia, 1995. p. 1942–48.
[12] Eberhart RC, Kennedy JF. A new optimizer using particle swarm theory. In: Proceedings of international symposium on micro machine and human science, Japan, 1995. p. 39–43.
[13] Goldberg DE. Genetic algorithms in search, optimization, and machine learning. Reading (MA, USA): Addison Wesley; 1989.
[14] IEEE, “IEEE 118, 300 -test systems”, (1993), http://www.ee.washington.edu/trsearch/pstca/.
[15] S. Surender Reddy, “Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm”, International Journal of Electrical and Computer Engineering , Vol. 7, No. 5, pp. 2349-2356. 2017
[16] S.S. Reddy, et al., “Faster evolutionary algorithm based optimal power flow using incremental variables”, Electrical Power and Energy Systems, vol. 54, pp. 198-210, 2014.
Citation
Kanagasabai Lenin, "Active Power Loss Reduction by Particle Swarm Optimization Algorithm," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.904-906, 2019.
Smartphone based Ischemic Heart Disease (Heart Attack) Risk Prediction using Clinical Data and Data Mining Approaches
Research Paper | Journal Paper
Vol.7 , Issue.1 , pp.907-910, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.907910
Abstract
We designed a mobile application to deal with Ischemic Heart Disease (IHD) (Heart Attack) An Android based mobile application has been used for coordinating clinical information taken from patients suffering from Ischemic Heart Disease (IHD). The clinical information from 787 patients has been investigated and associated with the hazard factors like Hypertension, Diabetes, Dyslipidemia (Abnormal cholesterol), Smoking, Family History, Obesity, Stress and existing clinical side effect which may propose basic non-identified IHD. The information was mined with information mining innovation and a score is produced. Effects are characterized into low, medium and high for IHD. On looking at and ordering the patients whose information is acquired for producing the score; we found there is a noteworthy relationship of having a heart occasion when low and high and medium and high class are analyzed; p=0.0001 and 0.0001 individually. Our examination is to influence straightforward way to deal with recognize the IHD to risk and careful the population to get themselves assessed by a cardiologist to maintain a strategic distance from sudden passing. As of now accessible instruments has a few confinements which makes them underutilized by populace. Our exploration item may decrease this constraint and advance hazard assessment on time.
Key-Words / Index Term
Heart Disease, Risk score tree, Chi-Square, p-value, IHD, Prediction Data Mining, Android, Smartphone
References
[1] A. Islam and A. Majumder, “Coronary artery disease in Bangladesh: A review”, Indian Heart Journal, vol. 65, no. 4, pp. 424-435, 2013.
[2] M. Abu Sayeed, H. Mahtab, S. Sayeed, T. Begum,P. Khanam and A. Banu, ”Prevalence and risk factors of coronary heart disease in a rural population of Bangladesh”, Ibrahim Med. Coll. J., vol. 4, no. 2, 2010.
[3] P. Wilson, R. D’Agostino, D. Levy, A. Belanger, H. Silbershatz and W. Kannel,“Prediction of Coronary Heart Disease Using Risk Factor Categories”, Circulation, vol. 97, no. 18, pp. 1837-1847, 1998.
[4] R. D’Agostino, Sr, S. Grundy, L. Sullivan,P. Wilson and for the CHD Risk Prediction Group,“Validation of the Framingham Coronary Heart Disease Prediction Scores”, JAMA, vol. 286, no. 2, p. 180, 2001.
[5] L. Burke, J. Ma, K. Azar, G. Bennett, E. Peterson,Y. Zheng, W. Riley, J. Stephens, S. Shah, B. Suffoletto, T. Turan, B. Spring, J. Steinberger and C. Quinn, “Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention”, Circulation, vol. 132, no. 12, pp. 1157-1213, 2015.
[6] I. Witten, E. Frank and M. Hall, Data mining. Burlington, MA: Morgan Kaufmann, 2011.
[7] J. Han, M. Kamber and J. Pei, Data mining. Amsterdam: Elsevier/ Morgan Kaufmann, 2012.
[8] P. Tan, M. Steinbach and V. Kumar, Introduction to data mining. Boston: Pearson Addison Wesley, 2005.
[9] “Statistical Analysis 5: Chi - squared test for 2 - way tables”, statstutor. [Online]. Available:
[10] K. Ahmed, T. Jesmin and M. Zamilur Rahman, “Early Prevention and Detection of Skin Cancer Risk using Data Mining”, International Journal of Computer Applications, vol. 62, no. 4, pp. 1-6, 2013.
Citation
Sudhir Anakal, Chandrasekhar Uppin, Ambresh Bhadrashetty, "Smartphone based Ischemic Heart Disease (Heart Attack) Risk Prediction using Clinical Data and Data Mining Approaches," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.907-910, 2019.
Real Power Loss Reduction by Ant Colony Search Algorithm
Research Paper | Journal Paper
Vol.7 , Issue.1 , pp.911-914, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.911914
Abstract
The paper presents Ant colony search Algorithm (ACSA) for solving optimal reactive power problem. ACSA algorithms are developed based on the observation of foraging behavior of real ants. Although they are almost blind animals with very simple individual capacities, they can find the shortest route between their nest(s) and a source of food without using visual cues. They are also capable of adapting to changes in the environment; finding a new shortest path once the old one is no longer feasible due to a new obstacle. The studies by ethnologists reveal that such capabilities are essentially due to what is called pheromone trails, which ants use to communicate information among individuals regarding path and to decide where to go. During their trips a chemical trail (pheromone) is left on the ground. The pheromone guides other ants towards the target point. Furthermore, the pheromone evaporates over time. If many ants choose a certain path and lay down pheromones, the quantity of the trail increases and thus this trail attracts more and more ants. Each ant probabilistically prefers to follow a direction rich in pheromone rather than a poorer one. Proposed algorithm has been tested in standard IEEE 300 bus system and simulation results reveals about the better performance of the proposed algorithm in reducing the real power loss.
Key-Words / Index Term
Reactive power, Transmission loss, Ant colony search algorithm
References
[1] O.Alsac, B. Scott, “Optimal load flow with steady state security”,IEEE Transaction. PAS -1973, pp. 745-751.
[2] Lee K Y ,Paru Y M , Oritz J L –A united approach to optimal real and reactive power dispatch , IEEE Transactions on power Apparatus and systems 1985: PAS-104 : 1147-1153
[3] A.Monticelli , M .V.F Pereira ,and S. Granville , “Security constrained optimal power flow with post contingency corrective rescheduling” , IEEE Transactions on Power Systems :PWRS-2, No. 1, pp.175-182.,1987.
[4] Deeb N ,Shahidehpur S.M ,Linear reactive power optimization in a large power network using the decomposition approach. IEEE Transactions on power system 1990: 5(2) : 428-435
[5] E. Hobson ,’Network consrained reactive power control using linear programming, ‘ IEEE Transactions on power systems PAS -99 (4) ,pp 868=877, 1980
[6] K.Y Lee ,Y.M Park , and J.L Oritz, “Fuel –cost optimization for both real and reactive power dispatches” , IEE Proc; 131C,(3), pp.85-93.
[7] M.K. Mangoli, and K.Y. Lee, “Optimal real and reactive power control using linear programming” , Electr.Power Syst.Res, Vol.26, pp.1-10,1993.
[8] C.A. Canizares , A.C.Z.de Souza and V.H. Quintana , “ Comparison of performance indices for detection of proximity to voltage collapse ,’’ vol. 11. no.3 , pp.1441-1450, Aug 1996 .
[9] K.Anburaja, “Optimal power flow using refined genetic algorithm”, Electr.Power Compon.Syst , Vol. 30, 1055-1063,2002.
[10] D. Devaraj, and B. Yeganarayana, “Genetic algorithm based optimal power flow for security enhancement”, IEE proc-Generation.Transmission and. Distribution; 152, 6 November 2005.
[11] Berizzi, C. Bovo, M. Merlo, and M. Delfanti, “A ga approach tocompare orpf objective functions including secondary voltage regulation,”Electric Power Systems Research, vol. 84, no. 1, pp. 187 – 194,2012.
[12] C.-F. Yang, G. G. Lai, C.-H.Lee, C.-T. Su, and G. W. Chang, “Optimal setting of reactive compensation devices with an improved voltage stability index for voltage stability enhancement,” International Journal of Electrical Power and Energy Systems, vol. 37, no. 1, pp. 50 – 57,2012.
[13] P. Roy, S. Ghoshal, and S. Thakur, “Optimal var control for improvements in voltage profiles and for real power loss minimization using biogeography based optimization,” International Journal of Electrical Power and Energy Systems, vol. 43, no. 1, pp. 830 – 838, 2012.
[14] B. Venkatesh, G. Sadasivam, and M. Khan, “A new optimal reactive power scheduling method for loss minimization and voltage stability margin maximization using successive multi-objective fuzzy lp technique,”IEEE Transactions on Power Systems, vol. 15, no. 2, pp. 844 –851, may 2000.
[15] W. Yan, S. Lu, and D. Yu, “A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique,”IEEE Transactions on Power Systems, vol. 19, no. 2, pp. 913 –918, may 2004.
[16] W. Yan, F. Liu, C. Chung, and K. Wong, “A hybrid genetic algorithm interior point method for optimal reactive power flow,” IEEE Transactions on Power Systems, vol. 21, no. 3, pp. 1163 –1169, aug. 2006.
[17] J. Yu, W. Yan, W. Li, C. Chung, and K. Wong, “An unfixed piecewise optimal reactive power-flow model and its algorithm for ac-dc systems,”IEEE Transactions on Power Systems, vol. 23, no. 1, pp. 170 –176, feb.2008.
[18] F. Capitanescu, “Assessing reactive power reserves with respect to operating constraints and voltage stability,” IEEE Transactions on Power Systems, vol. 26, no. 4, pp. 2224–2234, nov. 2011.
[19] Z. Hu, X. Wang, and G. Taylor, “Stochastic optimal reactive power dispatch: Formulation and solution method,” International Journal ofElectrical Power and Energy Systems, vol. 32, no. 6, pp. 615 – 621,2010.
[20] Kargarian, M. Raoofat, and M. Mohammadi, “Probabilistic reactive power procurement in hybrid electricity markets with uncertain loads,”Electric Power Systems Research, vol. 82, no. 1, pp. 68 – 80, 2012.
[21] M. Dorigo, V. Maniezzo, and A. Colorni, “The ant system: Optimization by a colony of cooperating agents,” IEEE Transactions on System, Man, and Cybernetics, Part B, vol.26, pp. 29-41, 1996.
[22] IEEE, “IEEE 118, 300 -test systems”, (1993), http://www.ee.washington.edu/trsearch/pstca/.
[23] S. Surender Reddy, “Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm”, International Journal of Electrical and Computer Engineering , Vol. 7, No. 5, pp. 2349-2356. 2017
[24] S.S. Reddy, et al., “Faster evolutionary algorithm based optimal power flow using incremental variables”, Electrical Power and Energy Systems, vol. 54, pp. 198-210, 2014.
Citation
Kanagasabai Lenin, "Real Power Loss Reduction by Ant Colony Search Algorithm," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.911-914, 2019.
Mind-Reading Computers: towards a new horizon in Medical Science
Research Paper | Journal Paper
Vol.7 , Issue.1 , pp.915-927, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.915927
Abstract
Mind reading is the ability to infer other people’s mental state and use that to make sense of and predict their behaviour and intensions. Though it seems impossible to read someone’s mind, the modern neuroscience is able to do just that with the help of Mind Reading Computers. Over the years, many Brain Machine Interface (BMI) tools have been invented and they have been put to use in different areas of research, but the most effective and useful applications of mind reading computers probably have been in the field of medical science. Starting from mind controlled robotic arms for disabled persons to today’s ‘Neuralink’ which is expected to treat serious brain diseases, scientists have always been up to create better replacement for the current, conventional way of treatment in neurology with the help of mind reading computers. In the present paper the author discusses about how mind reading computers are being used in development of human health and wellness and also about the future scopes of the on-going researches in this field. The author has also tried to find out the risks related to BMI devices.
Key-Words / Index Term
electroencephalogram, Mind-Controlled Robotic Arm, locked-in syndrome, Emotiv EPOC, deep brain stimulation
References
[1] Los Angeles Times, “Mind Reading Machine Tells Secrets of the Brain, Sci-Fi Comes True”, March 29, 1976.
[2] Baron-Cohen, S., Wheelwright, S., and Jolliffe, T., “Is There a “Language of the Eyes”? Evidence from Normal Adults, and Adults with Autism or Asperger Syndrome.”, Visual Cognition , Vol.4, No.3, pp. 311- 331, 1997.
[3] Van Erp, F. Lotte, M. Tangermann, “Brain-computer interfaces: beyond medical applications”, Computer -IEEE Computer Society-, IEEE, Vol.45, Issue.4, pp. 26-34, 2012.
[4] Sarah N. Abdulkader,Ayman Atia,Mostafa-Sami M. Mostafa, “Brain computer interfacing: Applications and challenges”, Egyptian Informatics Journal, Vol.16, Issue.2, pp. 213-230, 2015.
[5] Morshed, Bashir I. and Abdulhalim Khan. “A Brief Review of Brain Signal Monitoring Technologies for BCI Applications: Challenges and Prospects.”, Journal of Bioengineering & Biomedical Science, Vol.4, No.128, 2014. doi:10.4172/2155-9538.1000128
[6] Bamford, Sim., “A framework for approaches to transfer of a mind`s substrate”, International Journal of Machine Consciousness, Vol.4, No.01, pp.23-34, 2012.
[7] Goertzel, B., & Ikle, M.,“Special issue on mind uploading: Introduction”, International Journal of Machine Consciousness, Vol.4, No.01, pp.1–3, 2012. doi:10.1142/S1793843012020015
[8] Sandberg, A. & Bostrom, N., “Whole Brain Emulation: A Roadmap”, Technical Report #2008‐3, Future of Humanity Institute, Oxford University, pp. 1-130, 2008.
[9] Clerc., M., Bougrain, L. and Lotte, F., “ Brain-Computer Interfaces 1”. 1st ed., John Wiley & Sons, Inc., pp.133-134, 2016.
[10] Kołodziej, Marcin & Majkowski, Andrzej & Rak, Remigiusz. “Matlab FE-Toolbox - An universal utility for feature extraction of EEG signals for BCI realization”, Przeglad Elektrotechniczny, Vol. 86, pp.44-46, 2010.
[11] Spataro, Rossella & Sorbello, Rosario. “Reaching and Grasping a Glass of Water by Locked-In ALS Patients through a BCI-Controlled Humanoid Robot”, Frontiers in Human Neuroscience, Vol. 11, 2017. doi:10.3389/fnhum.2017.00068.
[12] Fabien Lotte, Marco Congedo, Anatole Lécuyer, Fabrice Lamarche, Bruno Arnaldi, “A review of classification algorithms for EEG-based brain–computer interfaces”, Journal of Neural Engineering, IOP Publishing, Vol. 4, pp.24, 2017.
[13] Chin JH, Vora N, “The global burden of neurologic diseases”, Neurology, Vol. 83, Issue. 4, pp. 349–351, 2014.
[14] World Health Organization (WHO), “Neurological Disorders: Public Health Challenges”, Geneva, WHO, 2006.
[15] Panuccio, G., Semprini, M., Natale, L., Buccelli, S., Colombi, I., & Chiappalone, M., “Progress in Neuroengineering for brain repair: New challenges and open issues”, Brain and Neuroscience Advances, Vol. 2, 2018.
[16] Graybiel, A., & Knepton, J., "Sopite Syndrome - Sometioes Sole Manifestation of Motion Sickness", Aviation, Space, and Environmental Medicine, Vol. 47, No.8, pp. 873-882, 1976.
[17] European Commission, “Fatigue”, European Commission, Directorate General for Transport, September 2015.
[18] Kvet, Michal, and Karol Matiaško. "Brain Tumour Detection", Journal of Biomedical Engineering and Technology, Vol.1, No. 3, pp. 40-49, 2013.
[19] Lv W, Wu Q, Liu X, Chen Y, Song H, Yang L and Zhang X , “Cue Reactivity in Nicotine and Alcohol Addiction: A Cross-Cultural View”, Front. Psychol. Vol.7, No.1335, 2016. doi: 10.3389/fpsyg.2016.01335, 2016.
[20] Leij, A. , Bergen, E. , Zuijen, T. , Jong, P. , Maurits, N. and Maassen, B., “Precursors of Developmental Dyslexia: An Overview of the Longitudinal Dutch Dyslexia Programme Study”, Dyslexia, Vol.19, pp. 191-213, 2013.
[21] M. Bridges, J. Beaty, F. Tenore, M. Para, M. Mashner, V. Aggarwal, S. Acharya, G. Singhal, N. Thakor, "Revolutionizing prosthetics 2009: Dexterous control of an upper-limb neuroprosthesis", Johns Hopkins APL Tech. Dig., Vol. 28, pp. 210, 2010.
[22] Hochberg, Leigh & Bacher, Daniel & Jarosiewicz, Beata & Masse, Nicolas & Simeral, J.D. & Vogel, Jörn & Haddadin, Sami & Liu, Jie & S Cash, Sydney & Van der Smagt, Patrick & Donoghue, John. “Reach and grasp by people with tetraplegia using a neurally controlled robotic arm”, Nature, Vol.485, pp. 372-375, 2012. doi:10.1038/nature11076
[23] Abiyev, Rahib H et al. “Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks”, BioMed research international, Vol. 2016, 2016, Art. no.9359868.
[24] Jing Wang, Vladimir L. Cherkassky, and Marcel Adam Just, “Predicting the Brain Activation Pattern Associated With the Propositional Content of a Sentence: Modeling Neural Representations of Events and States”, Human Brain Mapping, Vol. 38, Issue. 10, pp. 4865-4881, 2017. doi: 10.1002/hbm.23692
[25] Chaudhary U., Xia B., Silvoni S., Cohen L.G., Birbaumer N., “Brain–Computer Interface–Based Communication in the Completely Locked-In State”, PLoS Biology, Vol. 15, Issue. 1, 2017, Art. no. e1002593.
[26] Guger C., Spataro R., Allison B.Z., Heilinger A., Ortner R., Cho W., La Bella V., “Complete locked-in and locked-in patients: Command following assessment and communication with vibro-tactile P300 and motor imagery brain-computer interface tools”, Frontiers in Neuroscience, Vol. 11, 2017, Art. no. 251.
[27] Kim J.H., Min K.S., Jeong J.S., Kim S.J., “Challenges for the Future Neuroprosthetic Implants. In: Jobbágy Á”. (eds) 5th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, Springer, Berlin, Heidelberg, Vol. 37, 2011.
[28] American Associates, Ben-Gurion University of the Negev, "Students develop thought-controlled, hands-free computer for the disabled", ScienceDaily, April 2011.
[29] M. Parastarfeizabadi and A. Z. Kouzani, “Advances in closed-loop deep brain stimulation devices”, Journal of NeuroEngineering and Rehabilitation, Vol. 14, No. 1, August 2017.
[30] Lyons, Mark K. “Deep brain stimulation: current and future clinical applications”, Mayo Clinic proceedings, Vol. 86, Issue. 7, pp. 662-672, 2011.
[31] F. Meng, K. Tong, S. Chan, W. Wong, K. Lui, K. Tan, et al., “BCI-FES training system design and implementation of rehabiliation of stroke patients”, IEEE International Joint Conference on Neural Networks, 2008 (IEEE World Congress on Computational Intelligence), Hong Kong, China, pp. 4103-4106, 2008.
[32] Presacco A, Forrester L, Contreras-Vidal JL., “Towards a non-invasive brain-machine interface system to restore gait function in humans”, In: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, IEEE, Boston, MA, USA, pp. 4588–4591, 2011.
[33] Donati ARC, Shokur S, Morya E, Campos DSF, Moioli RC, Gitti CM, Augusto PB, Tripodi S, Pires CG, Pereira GA, Brasil FL,Gallo S, Lin AA, Takigami AK, Aratanha MA, Joshi S, Bleuler H, Cheng G, Rudolph A, Nicolelis MAL, “Long‐term training with a brain‐machine interface‐based gait protocol induces partial neurological recovery in paraplegic patients”, Science Report, Vol. 6, 2016, Art. no. 30383.
[34] Hakim Si-Mohammed, Ferran Argelaguet, Géry Casiez, Nicolas Roussel, Anatole Lécuyer, “Brain-Computer. Interfaces and Augmented Reality: A State of the Art”, Graz Brain-Computer Interface Conference, Graz, Austria, Sep 2017. doi: 10.3217/978-3-85125-533-1-82
[35] G. Pfurtscheller, F.H. Lopes da Silva, “Event-related eeg/meg synchronization and desynchronization: basic principles.” Clin Neurophysiol, Vol. 110, Issue.11, pp. 1842-1857, 1999.
[36] Pew Research Center, “U.S. Views of Technology and the Future”, April 2014.
Citation
Soumi Mitra, Asoke Nath, "Mind-Reading Computers: towards a new horizon in Medical Science," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.915-927, 2019.
A Survey Study of Various Software Cost Effort Estimation in Perspective of India
Survey Paper | Journal Paper
Vol.7 , Issue.1 , pp.928-933, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.928933
Abstract
According to Current scenario of India cost estimation plays a vital role in the whole cycle of software development. Software development process involves various techniques and skills which help for accurate estimation, overall charges, early delivery date, required effort and assurance of project acceptance or denial. This paper presents current scenario of knowledge in the field of software development methodologies through conducting systematic survey of cost estimation in Agile Software Development, which will be useful to understand current trends in cost estimation in Agile Software Development stages. Stages are building blocks of any software development methodology which are presented graphically. Software development methodologies are compared by highlighting strengths and weaknesses from the stakeholder’s point of view. This research is related to software cost and effort estimation in software development.
Key-Words / Index Term
Effort, Cost, Estimation, Software, Agile Technology, Survey, Analyze
References
[1]. Rashmi Popli, Dr. Naresh Chauhan, “Research Challenges of Agile Estimation” International Journal of IT and Knowledge management”, Vol- 7, Issue- 1 , pp. 108-111 ,2013
[2]. Samson Wanjala Munialo, Geoffrey MuchiriMuketha,” A Review of Agile Software Effort Estimation Methods”, International Journal of Computer Applications Technology and Research Volume 5–Issue 9, 612-618, 2016.
[3]. Trendowicz, Adam, Jeffery, Ross, ”Software Project Effort Estimation-Foundations and Best Practice Guidelines”, Springer, 2014
[4]. Jyoti G. Borade, ”Software Project Effort and Cost Estimation Techniques”, International Journal of Advanced Research in Computer Science and Software Engineering 3(8), pp. 730-739, August - 2013
[5]. Poonam, Sonal, Dharmesh,”Software Effort Estimation: A Comparison Based Perspective”, by
International Journal of Application or Innovation in Engineering & Management, Volume 3, Issue 12, PP- 18-29, 2014.
[6]. M Jongerson, “A review of studies on expert estimation of software development effort”, The Journal of Systems and Software 70 (2004) 37–60.
[7]. Pilot experiment - Wikipedia https://en.wikipedia.org/wiki/Pilot_experiment
[8]. Kitchenham, B., & Charters, S. “Guidelines for performing systematic Literature Reviews in Software Engineering”, by Kitchenham, B., & Charters, S. (2007) (Tech. Rep.)
[9]. Scaling Lean & Agile Development: Thinking and Organizational Tools for Large-scale Scrum. Pearson Education by Larman, C., &Vodde, B. (2008).
[10]. Leandro L. Minku and Xin Yao, "Ensembles and locality: Insight on improving software effort estimation", Information and Software Technology, Elsevier, Vol. 55, No. 8, 2013, pp. 1512-1528.
[11]. P.Abrahamsson, Koskela, J., "Extreme Programming: A Survey of Empirical Data from a Controlled Case Study", Proceedings of International Symposium on Empirical Software Engineering, pp. 73-82, 2004.
[12]. L. Layman, L. Williams, and L. Cunningham, "Motivations and Measurements in an Agile Case Study", Proceedings of ACM SIGSOFT Foundation in Software Engineering Workshop Quantitative Techniques for Software Agile Processes (QTESWAP), Newport Beach, CA, 2004.
[13]. Dr. Shalini Rajawat, and Anooja A, “Analyzing Agile Estimation Techniques and software development”, International Journal on Future Revolution in Computer Science & Communication Engineering”, Vol-4, Issue-4, PP-264-267, 2018.
[14]. Dr. Shalini Rajawat, and Anooja A, “Comparative analysis of software cost effort estimation and agile in perspective of software development”, International journal of advanced research in computer science, Vol-8, Issue-8, PP-121-125, 2017
Citation
Anooja A, Jameel Ahmad Qurashi, Sanjay Kumar, "A Survey Study of Various Software Cost Effort Estimation in Perspective of India," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.928-933, 2019.
Secure Routing Algorithm Forwireless Sensor Networks- Impact & Survey
Survey Paper | Journal Paper
Vol.7 , Issue.1 , pp.934-937, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.934937
Abstract
Prominence of wireless sensor networks (WSNs) is expanding ceaselessly in various spaces of day by day life, as they give productive strategy for gathering significant information from the surroundings for use in various applications. Steering in WSNs is the essential usefulness that permits the stream of data created by sensor hubs to the base station, while considering the extreme vitality imperative and the constraints of computational and capacity assets. In fact, this usefulness might be helpless and must be in itself anchored, since regular directing conventions in WSNs give productive steering strategies with low power utilization, yet they don`t consider the conceivable assaults. As sensor hubs might be effortlessly caught what`s more, traded off, we present a vitality effective secure information transmission in WSNs where we separate the region of enthusiasm for four quadrants and afterward utilizes the methods of both open and private key cryptography utilizing four Mobile Base stations for vitality sparing. We additionally utilize information pressure systems for diminishing the measure of bit transmission. We likewise utilize Monitor Hubs to recognize the inward assaults
Key-Words / Index Term
Cluster Based Wireless Sensor Network, Cryptographic Techniques, Data Compression technique, Mobile Sink nodes, Monitor Nodes
References
[1] Gay, D., Levis, P., and Culler, D. 2007. Software design patternsforTinyOS.PublishedinJournalACMTransactions onEmbeddedComputingSystems(TECS),Volume.6,2007.
[2] Dr. A. Senthilkumar, ?Energy Efficient Secure Multipath Routing Protocol For Wireless Sensor Networks ?, InternationalJournalofEngineeringResearch&Technology (IJERT)Vol. 2 Issue 4, April ?2013
[3] Nidal Nasser and Yunfeng Chen, Secure Multipath Routing Protocol for Wireless Sensor Networks, 27th International Conference on Distributed Computing Systems Workshops (ICDCSW`07), 2007,IEEE
[4] THEODORE ZAHARIADIS, HELEN C. LELIGOU, STAMATIS VOLIOTIS,SOTIRIS MANIATIS, PANAGIOTISTRAKADAS,PANAGIOTISKARKAZIS,An EnergyandTrust-awareRoutingProtocolforLargeWirelessSensorNetworks,Proceedingsofthe9thWSEASInternational Conference on APPLIED INFORMATICS AND COMMUNICATIONS , (AIC`09).
[5] ShivaMurthyG,RobertJohnD?Souza,andGollaVaraprasad.: Digital Signature-Based Secure Node Disjoint Multipath Routing Protocol for Wireless Sensor Networks, IEEE SENSORS JOURNAL, VOL. 12, NO. 10, (2012)
[6] A. Abduvaliyev, et al, ?On the Vital areas of Intrusion Detection Systems in Wireless Sensor Networks?, IEEE Communications Surveys & Tutorials, Vol. 15, No. 3, pp. 1223-1237,2013.
[7] Somia Sahraoui, Souheila Bouam , Secure Routing Optimization in Hierarchical Cluster-Based Wireless Sensor Networks,International Journal of CommunicationNetworks and Information Security (IJCNIS), Vol. 5, No. 3, December 2013.
Citation
Suresh Kumar, Kalpana Midha, "Secure Routing Algorithm Forwireless Sensor Networks- Impact & Survey," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.934-937, 2019.
Consumer Satisfaction among the Young Youth Using Smart Phones: A Study
Research Paper | Journal Paper
Vol.7 , Issue.1 , pp.938-943, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.938943
Abstract
The smart phone industry is the fastest growing sector in India. During this 25 years of journey mobile phones were transformed into personal computers. It is growing at a very rapid pace and has a significant contribution to the Gross Domestic Product of India every year. There is a great evolution of varied smart phones by different brands depending upon customer awareness and customer satisfaction. The new smart phones are featured with artificial intelligence, HD display, virtual assistant features like SIRI, Google assistant etc., high powered cameras, HD quality photos, Cloud storage feature and better battery life. As per study conducted by the mobile ecosystem forum, highest penetration rate of smart phone users was in the age group of 16-35 years of old. The study of customer satisfaction is relevant for organizations to maintain long term and healthy relationship with customers. In the carried out study, a survey was presented to understand the significant relationship between smart phone features and Indian youth customer. Presented paper also presents the comparative analysis which gives an overview of key findings by various researches along with their concept used for analysis.
Key-Words / Index Term
Word of Mouth, Customer Satisfaction, Smart Phones, Smart phone Features, Awareness, Perceived Image
References
[1]. Andrew, O. (2018). The History and Evolution of the Smartphone: 1992-2018. [online] Textrequest.com. Available at: https://www.textrequest.com/blog/history-evolution-smartphone/.
[2]. Statista. (2021, June 29). Smartphone users in India 2015–2025. https://www.statista.com/statistics/467163/forecast-of-smartphone-users-in-india/.
[3]. India Smartphone Market Share: By Quarter. (2021, June 1). Counterpoint Research. https://www.counterpointresearch.com/india-smartphone-share/.
[4]. Statista. (2019). India: smartphone users by age group 2019 | Statista. [online] Available at: https://www.statista.com/statistics/1135692/india-smartphone-users-by-age-group/.
[5]. Wang, L. and Prompanyo, M. (2020). Modeling the relationship between perceived values, e-satisfaction, and e-loyalty. Management Science Letters, pp.2609–2616.
[6]. Smartphone Brands American Customer Satisfaction Index. (2021). Retrieved 8 July 2021, from https://www.theacsi.org/acsi-benchmarks/benchmarks-by-brand/benchmarks-for-smartphones.
[7]. X. Yang, X. Zhang and F. Zuo, "Word of Mouth: The Effects of Marketing Efforts and Customer Satisfaction," 2009 International Joint Conference on Artificial Intelligence, 2009, pp. 687-690, doi: 10.1109/JCAI.2009.45.
[8]. D. Han, Y. Wang and H. Xu, "Service customization, customer perceived value, and satisfaction: From the perspective of customers` self-efficacy," ICSSSM11, 2011, pp. 1-4, doi: 10.1109/ICSSSM.2011.5959376.
[9]. M. Moslehpour, K. Amri and P. Promprasorn, "Factors influencing intention to use of smartphone applications in Thailand," 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2017, pp. 1108-1112, doi: 10.1109/IEEM.2017.8290064.
[10]. F. Ho, C. N. Wang, C. T. Ho, Y. C. Chiang and Y. F. Huang, "Evaluation of Smartphone feature preference by a modified AHP approach," 2015 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2015, pp. 591-594, doi: 10.1109/IEEM.2015.7385716.
[11]. J. Bauer, S. Thelen and A. Ebert, "Evaluation of large display interaction using smart phones," 2011 IEEE Conference on Visual Analytics Science and Technology (VAST), 2011, pp. 265-266, doi: 10.1109/VAST.2011.6102466.
[12]. I. Zamzami and M. Mahmud, "User Satisfaction on Smart Phone Interface Design, Information Quality Evaluation," 2012 International Conference on Advanced Computer Science Applications and Technologies (ACSAT), 2012, pp. 78-82, doi: 10.1109/ACSAT.2012.68.
[13]. A. Inoue, M. Saito and M. Iwashita, "Behavior Analysis on Mobile-Carrier Choice & Mobile-Phone Purchase," 2015 3rd International Conference on Applied Computing and Information Technology/2nd International Conference on Computational Science and Intelligence, 2015, pp. 422-427, doi: 10.1109/ACIT-CSI.2015.79.
[14]. Ling, C., Hwang, W. & Salvendy, G. Diversified users’ satisfaction with advanced mobile phone features. Univ Access Inf Soc 5, 239–249 (2006). https://doi.org/10.1007/s10209-006-0028-x
[15]. Colleen Page. 2005. Mobile research strategies for a global market. Commun. ACM 48, 7 (July 2005), 42–48. DOI:https://doi.org/10.1145/1070838.1070864
[16]. Thilagavathi, A., & Kanchana*, V. S. (n.d.). A STUDY ON CUSTOMER SATISFACTION TOWARDS SMARTPHONE USERS. PARIPEX INDIAN JOURNALRESEARCH,1.https://www.academia.edu/37947295/A_study_on_customer_satisfaction_towards_smart_phone_users
[17]. Haque, A., Nuruzzaman and Kalam, A. (2011). Customer Satisfaction Mobile Phone Services: An Empirical Study on Grameen Phone (GP) and Banglalink (BL) in Bangladesh. International Business Management, 5(3), pp.140–150.
[18]. Dr.S.NAMASIVAYAM, Dr.S.NAMASIVAYAM., M.PRAKASH, M.PRAKASH. and M.KRISHNAKUMAR, M.KRISHNAKUMAR. (2011). A Study on Customer Satisfaction Towards Samsung Smart Phones with Reference to Coimbatore City. Indian Journal of Applied Research, 4(5), pp.91–93.
[19]. Ijumba, B. (2021). Factors affecting choice of and satisfaction with mobile phones: an investigation of university of KwaZulu-Natal (Pietermaritzburg) students. Retrieved 8 July 2021, from https://researchspace.ukzn.ac.za/handle/10413/15172.
[20]. Kajarekar, R. (2019, August 28). Oppo, OnePlus Users Are Most Satisfied In India; 42% Indians Own More Than 1 Smartphone! Trak.in - Indian Business of Tech, Mobile & Startups. https://trak.in/tags/business/2019/08/28/oppo-oneplus-users-are-most-satisfied-in-india-42-indians-own-more-than-1-smartphone/
[21]. Team. (2020, December 21). 91mobiles The Great Indian Smartphone Survey 2020: a summary | 91mobiles.com. 91mobiles.Com |. https://www.91mobiles.com/hub/91mobiles-great-indian-smartphone-survey-2020/
[22]. Chauhan, V. (2020). STUDY OF CUSTOMER SATISFACTION TOWARDS SMARTPHONE USERS. International Journal of Advanced Research in Commerce, Management & Social Science (IJARCMSS), 03, 25–31. https://inspirajournals.com/uploads/Issues/1895492360.pdf
[23]. Matti Haverila. Mobile phone feature preferences, customer satisfaction and repurchase intent among male users. Australasian Marketing Journal (AMJ),Volume 19, Issue 4,2011, Pages 238-246,ISSN 1441-3582,https://doi.org/10.1016/j.ausmj.2011.05.009. (https://www.sciencedirect.com/science/article/pii/S1441358211000462).
[24]. Dongwon Lee, Junghoon Moon, Yong Jin Kim, Mun Y. Yi.Antecedents and consequences of mobile phone usability: Linking simplicity and interactivity to satisfaction, trust, and brand loyalty, Information & Management, Volume 52, Issue 3, 2015, Pages 295-304, ISSN 0378-7206, https://doi.org/10.1016/j.im.2014.12.001.
[25]. Hossain, M. M. & Suchy, N. J. (2013). INFLUENCE OF CUSTOMER SATISFACTION ON LOYALTY: A STUDY ON MOBILE TELECOMMUNICATION INDUSTRY. Journal of Social Sciences, 9(2), 73-80. https://doi.org/10.3844/jssp.2013.73.80
[26]. Ahmad, F., & Sherwani, N. U. (2015). An Empirical Study on the effect of Brand Equity of Mobile Phones on Customer Satisfaction. International Journal of Marketing Studies, 7(2). https://doi.org/10.5539/ijms.v7n2p59
[27]. Almossawi, M. M. (2012). Customer Satisfaction in the Mobile Telecom Industry in Bahrain: Antecedents and Consequences. International Journal of Marketing Studies, 4(6). https://doi.org/10.5539/ijms.v4n6p139
[28]. Singh, J. (2020, December 1). Indians Spend Rs. 2,400 on Average for Servicing Out-of-Warranty Smartphones: Counterpoint. NDTV Gadgets 360. https://gadgets.ndtv.com/mobiles/news/india-smartphones-after-sales-service-spend-customer-satisfaction-rate-counterpoint-report-2332611.
[29]. Erkan Bayraktar, Ekrem Tatoglu, Ali Turkyilmaz, Dursun Delen, Selim Zaim.Measuring the efficiency of customer satisfaction and loyalty for mobile phone brands with DEA, Expert Systems with Applications,Volume 39, Issue 1,2012, Pages 99-106,ISSN 0957-4174,https://doi.org/10.1016/j.eswa.2011.06.041. (https://www.sciencedirect.com/science/article/pii/S0957417411009419).
[30]. Dongwon Lee, Junghoon Moon, Yong Jin Kim, Mun Y. Yi.Antecedents and consequences of mobile phone usability: Linking simplicity and interactivity to satisfaction, trust, and brand loyalty, Information & Management, Volume 52, Issue 3, 2015, Pages 295-304, ISSN 0378-7206, https://doi.org/10.1016/j.im.2014.12.001.
Citation
Stuti Jain, Shiv Singh Sarangdevot, "Consumer Satisfaction among the Young Youth Using Smart Phones: A Study," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.938-943, 2019.
Text Mining Techniques for Information Extraction: Issues and Applications
Review Paper | Journal Paper
Vol.7 , Issue.1 , pp.944-950, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.944950
Abstract
Text mining research area has become very popular among researchers from various disciplines today. Text mining is one of the major areas of research for natural language documents. In this review, a comprehensive introduction and overview of text mining and existing research status is discussed. The major issue in text mining is the discovery of relevant information and patterns that are used to analyze text documents from the huge volume of information available over the internet. A number of tools and numerous methods exist for determining the relevant text and identifying valuable information for future research analysis and decision making. The correct and effective methods and tools for text mining helps in speed up the extraction of valuable information and it also decreases the effort and time required for the analysis. The paper describes the methods, applications and issues of text mining in various fields of life. These results based on the text mining information from the various cited research articles and publications will be very useful for the researchers working in this research area. In addition, various issues related to text mining are identified that affect the accuracy and relevancy of results.
Key-Words / Index Term
Text mining, Information extraction, Information Retrieval, Applications, NLP.
References
[1]. Sumathy K.L. & Chidambaram M. Text Mining: Concepts, Applications, Tools and Issues – An Overview, International Journal of Computer Applications (0975 – 8887), 80(4), 29-32, 2013.
[2]. Ah-Hwee Tan. Text Mining: The state of the art and the challenges. Procedings of the pakdd 1999 workshop on knowledge discover from advance data bases. 1999.
[3]. Gupta V. & Lehal Gurpreet S. A Survey of Text Mining Techniques and Applications, Journal Of Emerging Technologies In Web Intelligence, 1(1),60-76, 2009.
[4]. Duriau, V.J., Reger, K.R., & Pfarrer, M.D. A content analysis of the content analysis literature in organization studies: research themes, data sources, and methodological refinements. Organizational Research Methods, 10 (1), 5–34, 2007.
[5]. Jamiy, F.E., Daif, A., Azouazi, M., & Marzak, A. The potential and challenges of big data – recommendation systems next level application. arXiv preprint arXiv:1501.03424. 2015.
[6]. Kobayashi, V.B., Mol, S.T., Berkers, H.A., Kismihók, G., & Den Hartog, D.N. Text classification for organizational researchers: a tutorial. Organizational Research Methods, 21(3), 766–799, 2018.
[7]. Janasik, N., Honkela, T., & Bruun, H. Text mining in qualitative research: application of an unsupervised learning method. Organizational Research Methods, 12 (3), 436–460, 2009.
[8]. Wiedemann, G. Opening up to big data: computer- assisted analysis of textual data in social sciences.Historical Social Research/Historische Sozialforschung, 38(4), 332–357, 2013.
[9]. Arvinder Kaur & Deepti Chopra . Comparison of Text Mining. 5th Internaional conferenceon Relaibility,info com technology & optimization (Trends & Fture directions), 2016.
[10]. Henriksson A., Zhao J., Dalianis H., & Bostrom H. Ensembles of randomized trees using diverse distributed representations of clinical events, BMC Medical Informatics and Decision Making, 16 (2), 69-78, 2016.
[11]. Solanki H. Comparative study of data mining tools and analysis with unified data mining theory,International Journal of Computer Applications, 75(16), 2013.
[12]. Kaklauskas A., Seniut M., Amaratunga D., Lill I., Safonov A., Vatin N., Cerkauskas J., Jackute I., Kuzminske A., & Peciure L. Text analytics for android project, Procedia Economics and Finance, 18, 610–617, 2014.
Citation
Babita Verma, Jyothi Pillai, "Text Mining Techniques for Information Extraction: Issues and Applications," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.944-950, 2019.
Farm Automation and Cloud Integration by using SPROUT Framework
Research Paper | Journal Paper
Vol.7 , Issue.1 , pp.951-955, Jan-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i1.951955
Abstract
SPROUT is the coordinated framework which execute a few activity all the while to determine the issues of cultivating, which are bringing an enormous hardship now a days in the general public of ranchers. In India, farming assumes a significant part for advancement of food creation. Horticulture relies upon the rainstorm which isn`t adequate wellspring of water. So the water system is utilized in horticulture field. In water system framework relies on the dirt sort, water accessibility, dampness content, and so forth. In this paper programmed water system framework which depends on IoT arrangement. The model shows the essential exchanging framework system of water engine utilizing sensors from any piece of field by detecting the dampness, water source, and so on. In present days particularly ranchers are dealing with serious issues in watering their agribusiness fields, this is on the grounds that they have no appropriate thought regarding when the power is free so they can siphon water. Indeed, even after then they need to hold on until the field is appropriately watered, which makes them to quit doing different exercises. Here is a thought which assists not just ranchers with evening for watering the nurseries likewise, which detects the dirt dampness and switches the siphon consequently why the power is `ON`. Consistently a SMS warning is shipped off the rancher`s versatile about the current state of the homestead. Current temperature, pH(potential of Hydrogen) level of the dirt and probability of downpour information can be gotten to the Web-interface
Key-Words / Index Term
IoT, Sprout, Agriculture, Automation
References
[1] Dr. P. Bhanumathi, D. Saravanan, M. Sathyapriya ,V. Saranya “An Android Based Automatic Irrigation System Using Bayesian Network with SMS and Voice Alert” Vol. 2, Issue 2, pp.573-578,2017
[2] Ms.P.Sindhuja,M.Prathusha,M.C.Kalaiselvi,S.Jaya udhaa, R.Velthai, “Solar Driven Arduino Based Automatic Irrigation System using GSM” Vol. 2,Issue 10,pp.175-183,2016
[3] Sanjay Kumawat, Mayur Bhamare, Apurva Nagare , Ashwini Kapadnis”Sensor Based Automatic Irrigation System and Soil pH Detection using Image Processing” ,Vol.4,Issue .4 ,pp.3673-3675,2017
[4] R.Vagulabranan1, M.Karthikeyan,V. Sasikala ,”Automatic Irrigation System on Sensing Soil Moisture Content”,Vol. 3, Issue .3 ,pp.206-208,2016
[5] Prof. Rashmi Jain, Shaunak Kulkarni, Ahtesham Shaikh, Akash Sood, “Automatic Irrigation System Agriculture Field using Wireless Sensor Network (WSN)”,Vol .3,Issue .4,pp. 1602-1605,2016
[6] , Prof. S. Devi Mahalakshmi, Prof. P. Rajalakshmi,“IOT based crop-field monitoring and irrigation automation” In IEEE proceedings 10th International Conference on Intelligent Systems and Control (ISCO),Coimabatore,2016
[7] H, Rajan G. Mavekari, Prashant A. Shinde,”Web based automatic irrigation system using wireless sensor network and embedded Linux board. Pandurang “,In IEEE International Conference on Circuits, Power and Computing Technologies [ICCPCT-2015], Nagarcoil,2015
[8] Pandurang H, Rajan G. Mavekari, Prashant A. Shinde,” Web based automatic irrigation system using wireless sensor network and embedded Linux board”
Citation
Sujitha M, Jinu P Sainudeen, Nimmymol Manuel, Neena Joseph, "Farm Automation and Cloud Integration by using SPROUT Framework," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.951-955, 2019.