May 2019 International Journal of Innovative Technology and Creative Engineering (ISSN:2045-8711)

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019

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UK: Managing Editor International Journal of Innovative Technology and Creative Engineering 1a park lane, Cranford London TW59WA UK

USA: Editor International Journal of Innovative Technology and Creative Engineering Dr. Arumugam Department of Chemistry University of Georgia GA-30602, USA.

India: Editor International Journal of Innovative Technology & Creative Engineering 36/4 12th Avenue, 1st cross St, Vaigai Coliny Ashok Nagar Chennai , India 600083 Email: editor@ijitce.co.uk

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019

IJITCE PUBLICATION

International Journal of Innovative Technology & Creative Engineering Vol.9 No.5 May 2019

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019

Dear Researcher,

Greetings!

Article in this issue discusses about Industry 4.0. Idea of smart factories where machines are augmented with web connectivity and connected to a system that can visualize the entire production chain and make decisions on its own Cover Story for this month is about SPICON 2019 held in Chennai, India.

SPICON is an annual event from SPIN Chennai (the local chapter of the global network of IT professionals focused in the process, engineering, technology, domain and standards area). SPIN has been a partner and platform for many leading corporates, Tier-1, Tier2 and Tier3 organizations based in India and to an ecosystem of more than 3000 professionals in the IT and BPM industry of India.

The conference saw many senior executives, key decision makers, senior officials from Govt and Industry, Consultants, Practitioners, Middle management, Technologists, Cyber Security experts, Domain experts from various industries including BFSI, Manufacturing, Automotive, ICT and also will have many features like CXO Connect, B2B Connect, SPICON Quiz etc. “IJITCE� was invited to be the Journal Partner for the conference and agreed to publish some important & relevant papers published around the theme.

Thanks, Editorial Team IJITCE

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019

Editorial Members Dr. Chee Kyun Ng Ph.D Department of Computer and Communication Systems, Faculty of Engineering,Universiti Putra Malaysia,UPMSerdang, 43400 Selangor,Malaysia.

Dr. Simon SEE Ph.D Chief Technologist and Technical Director at Oracle Corporation, Associate Professor (Adjunct) at Nanyang Technological University Professor (Adjunct) at ShangaiJiaotong University, 27 West Coast Rise #08-12,Singapore 127470 Dr. sc.agr. Horst Juergen SCHWARTZ Ph.D, Humboldt-University of Berlin,Faculty of Agriculture and Horticulture,Asternplatz 2a, D-12203 Berlin,Germany Dr. Marco L. BianchiniPh.D Italian National Research Council; IBAF-CNR,Via Salaria km 29.300, 00015 MonterotondoScalo (RM),Italy Dr. NijadKabbaraPh.D Marine Research Centre / Remote Sensing Centre/ National Council for Scientific Research, P. O. Box: 189 Jounieh,Lebanon Dr. Aaron Solomon Ph.D Department of Computer Science, National Chi Nan University,No. 303, University Road,Puli Town, Nantou County 54561,Taiwan Dr. Arthanariee. A. M M.Sc.,M.Phil.,M.S.,Ph.D Director - Bharathidasan School of Computer Applications, Ellispettai, Erode, Tamil Nadu,India Dr. Takaharu KAMEOKA, Ph.D Professor, Laboratory of Food, Environmental & Cultural Informatics Division of Sustainable Resource Sciences, Graduate School of Bioresources,Mie University, 1577 Kurimamachiya-cho, Tsu, Mie, 514-8507, Japan Dr. M. Sivakumar M.C.A.,ITIL.,PRINCE2.,ISTQB.,OCP.,ICP. Ph.D. Project Manager - Software,Applied Materials,1a park lane,cranford,UK Dr. Bulent AcmaPh.D Anadolu University, Department of Economics,Unit of Southeastern Anatolia Project(GAP),26470 Eskisehir,TURKEY Dr. SelvanathanArumugamPh.D Research Scientist, Department of Chemistry, University of Georgia, GA-30602,USA. Dr. S.Prasath Ph.D Assistant Professor, Department of Computer Science, Nandha Arts & Science College, Erode , Tamil Nadu, India

Review Board Members Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic& Ceramic Materials,CSIRO Process Science & Engineering Private Bag 33, Clayton South MDC 3169,Gate 5 Normanby Rd., Clayton Vic. 3168, Australia Dr. Zhiming Yang MD., Ph. D. Department of Radiation Oncology and Molecular Radiation Science,1550 Orleans Street Rm 441, Baltimore MD, 21231,USA Dr. Jifeng Wang Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign Urbana, Illinois, 61801, USA Dr. Giuseppe Baldacchini ENEA - Frascati Research Center, Via Enrico Fermi 45 - P.O. Box 65,00044 Frascati, Roma, ITALY. Dr. MutamedTurkiNayefKhatib Assistant Professor of Telecommunication Engineering,Head of Telecommunication Engineering Department,Palestine Technical University (Kadoorie), TulKarm, PALESTINE.

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019 Dr.P.UmaMaheswari Prof &Head,Depaartment of CSE/IT, INFO Institute of Engineering,Coimbatore.

Dr. T. Christopher, Ph.D., Assistant Professor &Head,Department of Computer Science,Government Arts College(Autonomous),Udumalpet, India.

Dr. T. DEVI Ph.D. Engg. (Warwick, UK), Head,Department of Computer Applications,Bharathiar University,Coimbatore-641 046, India.

Dr. Renato J. orsato Professor at FGV-EAESP,Getulio Vargas Foundation,São Paulo Business School,RuaItapeva, 474 (8° andar),01332-000, São Paulo (SP), Brazil Visiting Scholar at INSEAD,INSEAD Social Innovation Centre,Boulevard de Constance,77305 Fontainebleau - France Y. BenalYurtlu Assist. Prof. OndokuzMayis University Dr.Sumeer Gul Assistant Professor,Department of Library and Information Science,University of Kashmir,India Dr. ChutimaBoonthum-Denecke, Ph.D Department of Computer Science,Science& Technology Bldg., Rm 120,Hampton University,Hampton, VA 23688 Dr. Renato J. Orsato Professor at FGV-EAESP,Getulio Vargas Foundation,São Paulo Business SchoolRuaItapeva, 474 (8° andar),01332-000, São Paulo (SP), Brazil Dr. Lucy M. Brown, Ph.D. Texas State University,601 University Drive,School of Journalism and Mass Communication,OM330B,San Marcos, TX 78666 JavadRobati Crop Production Departement,University of Maragheh,Golshahr,Maragheh,Iran VineshSukumar (PhD, MBA) Product Engineering Segment Manager, Imaging Products, Aptina Imaging Inc. Dr. Binod Kumar PhD(CS), M.Phil.(CS), MIAENG,MIEEE HOD & Associate Professor, IT Dept, Medi-Caps Inst. of Science & Tech.(MIST),Indore, India Dr. S. B. Warkad Associate Professor, Department of Electrical Engineering, Priyadarshini College of Engineering, Nagpur, India Dr. doc. Ing. RostislavChoteborský, Ph.D. Katedramateriálu a strojírenskétechnologieTechnickáfakulta,Ceskázemedelskáuniverzita v Praze,Kamýcká 129, Praha 6, 165 21 Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic& Ceramic Materials,CSIRO Process Science & Engineering Private Bag 33, Clayton South MDC 3169,Gate 5 Normanby Rd., Clayton Vic. 3168 DR.ChutimaBoonthum-Denecke, Ph.D Department of Computer Science,Science& Technology Bldg.,HamptonUniversity,Hampton, VA 23688 Mr. Abhishek Taneja B.sc(Electronics),M.B.E,M.C.A.,M.Phil., Assistant Professor in the Department of Computer Science & Applications, at Dronacharya Institute of Management and Technology, Kurukshetra. (India).

Dr. Ing. RostislavChotěborský,ph.d, Katedramateriálu a strojírenskétechnologie, Technickáfakulta,Českázemědělskáuniverzita v Praze,Kamýcká 129, Praha 6, 165 21

Dr. AmalaVijayaSelvi Rajan, B.sc,Ph.d, Faculty – Information Technology Dubai Women’s College – Higher Colleges of Technology,P.O. Box – 16062, Dubai, UAE

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019 Naik Nitin AshokraoB.sc,M.Sc Lecturer in YeshwantMahavidyalayaNanded University Dr.A.Kathirvell, B.E, M.E, Ph.D,MISTE, MIACSIT, MENGG Professor - Department of Computer Science and Engineering,Tagore Engineering College, Chennai Dr. H. S. Fadewar B.sc,M.sc,M.Phil.,ph.d,PGDBM,B.Ed. Associate Professor - Sinhgad Institute of Management & Computer Application, Mumbai-BangloreWesternly Express Way Narhe, Pune - 41 Dr. David Batten Leader, Algal Pre-Feasibility Study,Transport Technologies and Sustainable Fuels,CSIRO Energy Transformed Flagship Private Bag 1,Aspendale, Vic. 3195,AUSTRALIA Dr R C Panda (MTech& PhD(IITM);Ex-Faculty (Curtin Univ Tech, Perth, Australia))Scientist CLRI (CSIR), Adyar, Chennai - 600 020,India Miss Jing He PH.D. Candidate of Georgia State University,1450 Willow Lake Dr. NE,Atlanta, GA, 30329 Jeremiah Neubert Assistant Professor,MechanicalEngineering,University of North Dakota Hui Shen Mechanical Engineering Dept,Ohio Northern Univ.

Dr. Xiangfa Wu, Ph.D. Assistant Professor / Mechanical Engineering,NORTH DAKOTA STATE UNIVERSITY SeraphinChallyAbou Professor,Mechanical& Industrial Engineering Depart,MEHS Program, 235 Voss-Kovach Hall,1305 OrdeanCourt,Duluth, Minnesota 55812-3042 Dr. Qiang Cheng, Ph.D. Assistant Professor,Computer Science Department Southern Illinois University CarbondaleFaner Hall, Room 2140-Mail Code 45111000 Faner Drive, Carbondale, IL 62901 Dr. Carlos Barrios, PhD Assistant Professor of Architecture,School of Architecture and Planning,The Catholic University of America Y. BenalYurtlu Assist. Prof. OndokuzMayis University Dr. Lucy M. Brown, Ph.D. Texas State University,601 University Drive,School of Journalism and Mass Communication,OM330B,San Marcos, TX 78666 Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic& Ceramic Materials CSIRO Process Science & Engineering Dr.Sumeer Gul Assistant Professor,Department of Library and Information Science,University of Kashmir,India Dr. ChutimaBoonthum-Denecke, Ph.D Department of Computer Science,Science& Technology Bldg., Rm 120,Hampton University,Hampton, VA 23688

Dr. Renato J. Orsato Professor at FGV-EAESP,Getulio Vargas Foundation,São Paulo Business School,RuaItapeva, 474 (8° andar)01332-000, São Paulo (SP), Brazil Dr. Wael M. G. Ibrahim Department Head-Electronics Engineering Technology Dept.School of Engineering Technology ECPI College of Technology 5501 Greenwich Road - Suite 100,Virginia Beach, VA 23462

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019 Dr. Messaoud Jake Bahoura Associate Professor-Engineering Department and Center for Materials Research Norfolk State University,700 Park avenue,Norfolk, VA 23504 Dr. V. P. Eswaramurthy M.C.A., M.Phil., Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India.

Dr. P. Kamakkannan,M.C.A., Ph.D ., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India.

Dr. V. Karthikeyani Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 008, India.

Dr. K. Thangadurai Ph.D., Assistant Professor, Department of Computer Science, Government Arts College ( Autonomous ), Karur - 639 005,India.

Dr. N. Maheswari Ph.D., Assistant Professor, Department of MCA, Faculty of Engineering and Technology, SRM University, Kattangulathur, Kanchipiram Dt - 603 203, India.

Mr. Md. Musfique Anwar B.Sc(Engg.)

Lecturer, Computer Science & Engineering Department, Jahangirnagar University, Savar, Dhaka, Bangladesh.

Mrs. Smitha Ramachandran M.Sc(CS)., SAP Analyst, Akzonobel, Slough, United Kingdom.

Dr. V. Vallimayil Ph.D., Director, Department of MCA, Vivekanandha Business School For Women, Elayampalayam, Tiruchengode - 637 205, India.

Mr. M. Moorthi M.C.A., M.Phil., Assistant Professor, Department of computer Applications, Kongu Arts and Science College, India PremaSelvarajBsc,M.C.A,M.Phil Assistant Professor,Department of Computer Science,KSR College of Arts and Science, Tiruchengode Mr. G. Rajendran M.C.A., M.Phil., N.E.T., PGDBM., PGDBF., Assistant Professor, Department of Computer Science, Government Arts College, Salem, India.

Dr. Pradeep H Pendse B.E.,M.M.S.,Ph.d Dean - IT,Welingkar Institute of Management Development and Research, Mumbai, India Muhammad Javed Centre for Next Generation Localisation, School of Computing, Dublin City University, Dublin 9, Ireland Dr. G. GOBI Assistant Professor-Department of Physics,Government Arts College,Salem - 636 007 Dr.S.Senthilkumar Post Doctoral Research Fellow, (Mathematics and Computer Science & Applications),UniversitiSainsMalaysia,School of Mathematical Sciences, Pulau Pinang-11800,[PENANG],MALAYSIA. Manoj Sharma Associate Professor Deptt. of ECE, PrannathParnami Institute of Management & Technology, Hissar, Haryana, India RAMKUMAR JAGANATHAN Asst-Professor,Dept of Computer Science, V.L.B Janakiammal college of Arts & Science, Coimbatore,Tamilnadu, India Dr. S. B. Warkad Assoc. Professor, Priyadarshini College of Engineering, Nagpur, Maharashtra State, India Dr. Saurabh Pal Associate Professor, UNS Institute of Engg. & Tech., VBS Purvanchal University, Jaunpur, India Manimala Assistant Professor, Department of Applied Electronics and Instrumentation, St Joseph’s College of Engineering & Technology, Choondacherry Post, Kottayam Dt. Kerala -686579 Dr. Qazi S. M. Zia-ul-Haque

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019 Control Engineer Synchrotron-light for Experimental Sciences and Applications in the Middle East (SESAME),P. O. Box 7, Allan 19252, Jordan Dr. A. Subramani, M.C.A.,M.Phil.,Ph.D. Professor,Department of Computer Applications, K.S.R. College of Engineering, Tiruchengode - 637215 Dr. SeraphinChallyAbou Professor, Mechanical & Industrial Engineering Depart. MEHS Program, 235 Voss-Kovach Hall, 1305 Ordean Court Duluth, Minnesota 558123042 Dr. K. Kousalya Professor, Department of CSE,Kongu Engineering College,Perundurai-638 052 Dr. (Mrs.) R. Uma Rani Asso.Prof., Department of Computer Science, Sri Sarada College For Women, Salem-16, Tamil Nadu, India.

MOHAMMAD YAZDANI-ASRAMI Electrical and Computer Engineering Department, Babol"Noshirvani" University of Technology, Iran.

Dr. Kulasekharan, N, Ph.D Technical Lead - CFD,GE Appliances and Lighting, GE India,John F Welch Technology Center,Plot # 122, EPIP, Phase 2,Whitefield Road,Bangalore – 560066, India.

Dr. Manjeet Bansal Dean (Post Graduate),Department of Civil Engineering,Punjab Technical University,GianiZail Singh Campus,Bathinda -151001 (Punjab),INDIA Dr. Oliver Jukić Vice Dean for education,Virovitica College,MatijeGupca 78,33000 Virovitica, Croatia Dr. Lori A. Wolff, Ph.D., J.D. Professor of Leadership and Counselor Education,The University of Mississippi,Department of Leadership and Counselor Education, 139 Guyton University, MS 38677

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Contents Bio fertilizers and their role in sustainable Aquaculture with particular reference to Azolla & Spirulina ……………….…..…..[671] An Performance Comparison on Space Complexity of Web User Tracking for Clustering and Classifiers ……………….…..…..[684] SPICON 2019 Cover Story

……………….…..…..[691]

Industry 4.0 Article

……………….…..…..[693]

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019

Bio fertilizers and their role in sustainable Aquaculture with particular reference to Azolla & Spirulina N.R.Chattopadhyay1 & P.P.Ghorai2 1Visiting Research Professor, Dept. of Biotechnology, Govt. of India 2 Department of Zoology, Vidyasagar University, West Bengal, India Corresponding author: nrchatterjee40@gmail.com Abstract – Bio fertilizers are natural fertilizers that are microbial inoculants of bacteria, algae and fungi (separately or in combination), which may help biological nitrogen fixation for the benefit of plants.

They help build up the soil micro-flora and there by the soil health. Bio fertilizer also includes organic fertilizers (manure, etc.) Use of bio-fertilizer is recommended for improving the soil fertility in organic farming. Bio fertilizers are the substance that contains microorganism's living or latent cells. A bio fertilizer increases the nutrients of host plants when applied to their seeds, plant surface or soil by colonizing the rhizosphere of the plant. Bio fertilizers are more cost-effective as compared to chemical fertilizers.

Key words: Bio fertilizers, Azolla , 'symbiotic relationship, Organic fertilizers 2. Introduction Bio fertilizers are defined as preparations containing living cells or latent cells of efficient strains of microorganisms that help crop plants' uptake of nutrients by their interactions in the rhizosphere when applied through seed or soil.

There are five bio fertilizers viz. Rhizobium, Azotobacter, Azospirillum and blue green algae (BGA), traditionally used as Bio fertilizers. Bio fertilizers play an important role in improving soil fertility and boosting crop yields. Besides several microorganisms such as algae and various inorganic compound fixing bacteria, Azolla is also used as bio fertilizer in temperate as well as tropical rice growing areas. Azolla is able to do this

because it has a unique mutually beneficial 'symbiotic relationship' with a cyanobacterium (blue-green alga) called Anabaena. Each partner gives something to the other in this Perfect Marriage. The Azolla - Anabaena symbiosis. Each partner gives something to the other. Azolla is unique because it is one of the fastest growing plants on the planet – yet it does not need any soil to grow.

Unlike almost all other plants, Azolla is able to get its nitrogen fertilizer directly from the atmosphere.

That means that it is able to produce bio fertilizer, livestock feed , food and bio fuel exactly where they are needed and, at the same time, draw down large amounts of CO2 from the atmosphere, thus helping to reduce the threat of climate change. Azolla is able to do this because it has a unique mutually beneficial ‘symbiotic relationship‘ with a cyanobacterium ( blue-green alga) called Anabaena. Azolla provides an enclosed environment for Anabaena within its leaves. In return, Anabaena sequesters nitrogen directly from the atmosphere which then becomes available for Azolla’s growth, freeing it from the soil that is needed by most other land plants for their nitrogen fertilization.

Spirulina is a multicellular spiral shaped chain of cells. It is a blue-green alga belonging to the family oscillatoriaceae. It consists of 6-8 µm diameter cylindrical cells in unbranched helicoid trichomes.

The filaments show movement, gliding along their axis. The trichomes elongate by intercalary cell divisions. They do not have heterocysts. Spirulina

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can grow in widely differing environments such as soils, marshes, brackish and sea waters and thermal springs. It can even grow in waters whose alkalinity is so high (upto pH-11). In this alkalinity, other microorganisms cannot exist (John Jothi, 2006).

There are two species Arthrospira platensis and Arthrospira maxima which is most widely distributed and is mainly found in Africa and Asia. Mant species of spirulina are cultivated for rich protein and carotene they have. Spirulina can be used as a conservator to reclaim alkaline and saline soil ( Venkataraman , 2005 )

3. Categorization of Bio fertilizers •

Symbiotic nitrogen fixers, Rhizobium spp.;

•

Non-symbiotic, free-living nitrogen fixers (Azotobacter, Azospirillum, etc.);

•

Algal bio fertilizers (blue-green algae or blue-green algae in association with Azolla);

•

Phosphate-solubilising bacteria;

•

Mycorrhizae;

•

Organic fertilizers.

4. Working principle of bio fertilizers Bio fertilizers trap atmospheric nitrogen to the soil and convert them into plant usable forms. They also convert the insoluble phosphate forms into plant available forms. They stimulate root growth by producing some hormones and anti metabolites.

5. Azolla as Bio fertilizer

Azolla is a floating pteridophyte, which contains as endosymbiont the nitrogen-fixing cyanobacterium Anabaena azollae (Nostocaceae family). Widely cultivated in the Asian regions, Azolla is either incorporated into the soil before rice transplanting or grown as a dual crop along with rice (Alexander, M. (1974).

A. Azolla as Fish Feed The use of algae as fish feed additives may be limited to the commercial production of high value fish. Laboratory feeding trials on the use of fresh or dried Azolla as a complete diet for fish show inconclusive results.

B. Importance of Azolla as Bio fertilizer in sustainable Aquaculture a. What is Azolla Azolla a dichotomously branched free floating aquatic fern is naturally available mostly on moist soils, ditches marshy ponds and is widely distributed in tropical belt of India. The shape of Indian Species is typically triangular measuring about 1.5 to 3.0 cm in length 1 to 2 cm in breadth. Roots emanating from growing branches remained suspended in water.

The dorsal lobe., which remains exposed to air, is having specific cavity containing its symbiotic cavity contain its symbolic partner, a Blue Green Algae (BGA), Anabaena Azolae. The fern is capable of fixing atmosphere nitrogen in the soil in the form of NH4 and becomes available as soluble nitrogen for the rice crop. The symbiosis Azolla Anabaena is outstanding due to its high productivity combined with its ability to fix nitrogen at high rates. Because of this, in recent decades, countless studies have been conducted on this association, but with insufficient synthesis and coordination (Yatazawa, M. Et.et. al., 1980).

Because of the growing concern about conservation of the environment and the need for deploying renewable, sustainable resources; the application of Azolla as a bio fertilizer on agricultural crops (Anand Titus Pereira, 1984), in order to provide a natural source of the crucial nutrient nitrogen, can be very beneficial to the future of our planet. Besides the environmental appropriateness of the use of Azolla, for multitudes of farmer’s in many parts of the world who cannot afford chemical fertilizers, Azolla application can enhance their economic status, increasing yields while minimizing costs. Due to the fact that rice paddy fields form an ideal environment for Azolla, one of its most suitable applications is on rice. Besides its utilization as a bio fertilizer on a

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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.9 NO.5 MAY 2019

variety of crops, Azolla can be used as an animal feed, a human food, a medicine, and a water purifier.

It may also be used for the production of hydrogen fuel, the production of biogas, the control of weeds, the control of mosquitoes, and the reduction of ammonia volatilization which accompanies the application of chemical nitrogen fertilizer.

Table .1 . Elemental composition of Azolla

Elements Nitrogen

Fig.1. Azolla Fronds freely floating on water surface Azolla partners blue green algae inside its lobes and is capable of harvesting atmospheric nitrogen. Due to this invisible partnership the fern multiplies very fast. The symbiotic association of the algae aids in the creation of a huge amount of biomass on the surface of the water. It is then harvested, dried and used as biofertilizer to supplement the needs of nitrogen in coffee farms. Since Azolla species are commonly found worldwide in coffee producing countries, it could provide the coffee farmers with an in expensive way of supplementing part of their nitrogen requirement, in an eco-friendly manner, without polluting the environment.

Percentage (%) 4.5

Phosphorus

5.0

Patassium

0.5

Calcium

2.0-4.5

Magnesium

0.1-1.0

Manganese

0.65

Iron

0.16

Crude fat

3.0-3.5

Sugar

3.0-3.3

Starch

3.4-3.5

Chlorophill

6.5

CHLOROPHYLL-A

0.25-0.50

Ash

9.0-9.3%

crude lipid crude fiber crude protein content

6.0 to 6.7% 9.2-11.3% 20.3-31.2%

b. Classification (Taxonomy) • • • • •

Class : Pteridophyta Order : Salvinales Family : Azollaceae/ Salvinaceae Genus : Azolla Sub Genus : Eu-Azolla

c. Geographical range Native range: Africa and Madagascar, India, South Asia, China and japan, Malaya and the Philippines, the New Guinea mainland and Australia.

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Known introduced range: Papua New Guinea, Australia, China, Japan, New Zealand, Vietnam, US. d. The Elemental / Nutritive composition for Azolla filiculoides on a dry weight basis Nutrient composition of Azolia Azolla filiculoides cultured in the secondary treated effluent showed a high crude protein content (20.3-31.2%), and comparatively low contents of crude fiber (9.211.3%) and ash (9.0-9.3%) expressed on a dry weight basis. The crude lipid content ranged from 6.0 to 6.7% and the nitrogen-free extract content ranged from 35.1 to 46.2%.

Fig. 2. Azolla isolates from varied coffee Since the fern has a desirable carbon nitrogen ratio, it decomposes rapidly can be used in a very short time. The fern also acts as a store house for potash accumulation and stores more than five times its requirement. The significance of Azolla as a cheap source of nitrogen was first observed in China. The art of feeding the people (Chih Min Tao Shu), a book on agricultural techniques written in 540 A.D. by JiaSsu Hsieh, describes the cultivation and use of Azolla in rice fields. At the beginning of the 17th century, there were many local records of Azolla use as manure both in China and Vietnam. Azolla plants have been described by the Chinese and Vietnamese as being miniature nitrogen fertilizer factories.

On hydrolysis Azolla is found to contain a considerable number of different amino acids.The amount of total amino acids is about 230 g kg- 1 dry weight. An important amino acid, lysine is comparatively more abundant than in the reported amino acid composition of other aquatic plants though the proline, methionine, and histidine levels are lower than those in commercial feed (Shiomi and Kitoh 1987b). As a feed with a higher protein content is considered to be suitable for Tilapia,

e. Azolla – Anabaena Symbiotic Association In the Azolla – Anabaena symbiosis, the fern is generally referred to as the macro symbiont and the blue green algae, namely anabaena is known as the micro symbiont. The two partners live in a very close relationship with one another. The fern provides the protection to the micro symbiont from oxygen damage from the external environment and the anabaena in turn provides the nitrogen to the fern for its growth and multiplication. Both the partners harvest solar energy via photosynthesis and the total nitrogen requirement can be supplied by the assimilation of nitrogen fixed by anabaena, the micro symbiont (Each leaf of azolla has the potential of harboring 75,000 Anabaena cells containing 3 to 3.5 % nitrogen). The beauty of this fern is that it is quite hardy and during favorable environmental conditions multiplies in geometric proportions. The algal symbiont is closely associated with all stages of the fern’s development. The symbiont resides in the cavities formed in the dorsal lobe of the fern.

Rapid multiplication of the fern takes place in summer months.World over there exist different species of Azolla. Azollacaroliniana, A. filiculoides, A. mexicana, A. microphylla, A. pinnata and A. nilotica. In India, A. pinnata is commonly observed.

The algal symbiont belongs to the family Nostocaceae and is generally referred to as Anabaena Azollae.

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f. MORPHOLOGY

Fig.3.

Azolla association

–

Anabena

symbiotic

The Azolla fern is a freely floating fern with multi branches and long roots. Each leaf has two lobes, the ventral and dorsal lobes. The dorsal lobes are chlorophyllous and house the algal symbiont. The nitrogen fixing symbiont is present during all development stages of the fern. More importantly, the micro symbiont exhibits host specificity because no other algal species is found in the leaf cavities.

The fern appears lush green in color but turns orange red under stress conditions. This color comes from anthocyanin pigments ((Anand Titus Pereira et. al., 1987).

Fig. 5. Underwater Root system of Azolla g. PHYSIOLOGICAL REQUIREMENT Fig. 4. Artificial Culture of Azolla The amount of nitrogen, phosphorus (Anand Titus Pereira et. al., 1987) and potassium content in Azolla varies with variety, environment and field management. Different Varieties of Azolla species occur with the desired characteristics. The field requirement of Azolla and its nitrogen fixing symbiont, Anabaena azollae, for growth and nitrogen fixation are complex and strongly related to the biochemistry of each of the components of the association. For the survival of the partners, under adverse environment conditions, the life cycle of both Azolla as well as that of the algae is important.

Air, light, water and mineral nutrients are important factors in determining the growth and development of the fern. A few scientists have worked on a variety of inorganic media to accelerate growth.

Phosphorus and potassium are the major elements along with iron, molybdenum, cobalt. i. pH Our studies point out to the fact that most of the strains collected from coffee growing regions grow well in natural pH. The optimum hydrogen ion concentration for Azolla species found in Joe's sustainable farm is around neutral pH. Azolla species are also sensitive to high temperature and the optimum temperature is between 25 and 30 degree centigrade.

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ii. LIGHT INTENSITY Azolla grows well under semi shaded conditions.

However, strong sunlight for a period of two to three hours is not detrimental for the growth and multiplication of the fern. iii. TEMPERATURE The macro and micro symbiont exhibit growth over a relatively wide temperature range but the optimum range appears to be between 25 and 30 degree centigrade. Very high temperatures are unfavorable for vegetative growth of the fern. iv. PHOTOSYNTHESIS The macro and the micro symbiont consist of photo synthetically active pigments. The light harvesting pigments of the individual partners are complementary. The Azolla contains chlorophylls a and b while the alga contains chlorophyll a and phycobilins. Both partners contain carotenoids..

viii. DOUBLING TIME Under favorable conditions the fern multiplies in geometric proportions and doubles in three to four days with an average nitrogen content of 3%. ix. EFFECT OF HERBICIDES &PESTICIDES Observations point out to the fact that the presence of Azolla is more markedly reduced in intensive crop management than in traditional zones where sustainable agriculture is practiced. Herbicides and pesticides have a deleterious effect on the occurrence of Azolla (Anand Titus Pereira et. al., 1987 ). g. HOW TO GROW AZOLLA •

• •

v. NITROGEN FIXATION The atmospheric nitrogen is harvested by the algal symbiont. Heterocysts are the sites of nitrogen fixation. Heterocyst frequency increase along the stem from apex to base in the successive leaves.

•

vi. SURVIVAL The sporocarps produced by azolla can be endure long periods of desiccation. Under natural conditions proliferation of azolla is entirely through vegetative reproduction. However, Sexual reproduction, which is essential to the survival of the population during temporary adverse conditions, also occurs. A combination of favorable environmental conditions favors the germination of spores.

•

•

vii. WATER TURBULENCE Plant density and turbulence of the water surface markedly influences growth rate and nitrogenous activity of the fronds.

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In low land, field is ploughed; leveled and small bunds of 50cm width are made to make small ponds of 3 x 2 a 1 M size.

Only 10-15 cm standing water is allowed in the ponds.

The green azolla @ 50-200 g/sqm + PO through SSP @ 20 kg/ha along with Furadan 1 g/kg of Azolla is mixed and released in the pond maintaining a 10-15cm of water level, for further growth and multiplication of Azolla.

Azolla multiplies rapidly and form a green mat like a carpet on water surface of ponds in just two weeks. This green Azolla is harvested in bamboo basket and transferred and released in the transplanted rice field for further multiplication, as dual cropping with rice for fixing nitrogen to rice crop.

Harvested green Azolla could be converted in to compost by pounding in pits for a month which is then used like FYM for other crops grown under upland situation.

During summer, green Azolla is harvested at an interval of 15-20 days but during winter growth of Azolla becomes slow due to moisture stress and low winter temperature, hence Azolla can be harvested at 25-30 days interval during winter.

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azolla each day; whereas, crucian crap and lotus carp eat about 8% of their body weight in Azolla (Anand Titus Pereira & Gowda, T.K.S. (1991). j.

Fig. 6 Formation of Dense Azolla Mat in Successive Stages h. HOW AZOLLA NITROGEN

FIXES

ATMOSPHERE

The remarkable feature of Azolla is that its symbiotic relationship with Cyanobacterium (Anabaena azollae) which remained on the dorsal leaf cavity of Azolla.Thre fern provides protein substances to Anabaena (BGA). The BGA then absorbed the atmospheric nitrogen and decomposes it through enzymic activity and converted in to soluble ammonia (NH+) (Anand Titus Pereira & Gowda, T.K.S. (1987) . i. Contribution of Azolla in Aquaculture • Azolla reduces evaporation from water surface and increases water use efficiency in rice (Watanabe, I., et. al., 1977).

• Dry Azolla flakes can be used as poultry feed and green Azolla is also a good feed for fishes.

• Effect of azolla. Four fish species (grass carp, tilapia, crucian carp, and lotus carp) are raised with azolla for 110-112 days. The fish species best suited to the rice – azolla – fish system are grass carp and tilapia. Both like to eat azolla and adapt easily to the rice field environment. The omnivorous crucian carp and lotus carp (which are benthic and planktivorous feeders) can be raised in the rice field in lower numbers. Grass carp and tilapia eat over 60% of their body weight in

MULTIPLE USES OF AZOLLA • Basal application on green Azolla manure @ 10-12 t/ha increase soil nitrogen by 5060 kg/ha and reduces 30-35 kg of nitrogenous fertilizer requirement of rice crop ((Watanabe, I., et. al., 1977).

• Release of green Azolla twice as dual cropping in rice crop @ 500 kg/ha enriches soil nitrogen 50 kg/ha and reduces N requirement by 20-30 kg/ha.

• Use of Azolla increase rice yield by 20 to 30%.

• Rice varieties like DR-92, RCPL-1-87-8, Mendri, H-2850 and Manipuri produced more than 30 q / ha rice yield when grown with Azolla as dual cropping under natural soil fertility (Paul, E.A. and Clark, F.E., 1996) .

• Under low land condition a thick Azolla mat does not allow the weeds to grow in rice field thus, Azolla suppresses the weed growth and creates congenial condition for rice production (Michelle and Jude Fanton., 1990)

Fig. 7. Formation of dense Azolla Mat

The potential uses of Azolla are numerous. Azolla is a nutrient rich fern and has traditionally been used throughout Asia and parts of Africa as feed for livestock, poultry and fishes. Azolla contains very 677

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high levels of protein and fat and promote the development of both grain production and stock breeding. In some countries the fern is used for ornamental purposes. At times Azolla is also used as human food.

K. RECOMENDATIONS FOR RESEARCH • •

• • •

Establishment of Azolla germplasm collection in coffee growing regions.

Characterization of various Azolla isolates should be undertaken so as to determine their nitrogen fixing efficiency.

Package of practices for Azolla production should be standardized.

Development of techniques for the germination of Azolla spores.

Since various Azolla cultures are present in various agro climate coffee regions, we need to develop techniques for the differentiation of Anabaena azollae strains.

70% protein (more than beef, chicken, and soybeans), 9 essential and 10 non-essential amino acids, as well as high levels of gamma - linolenic acid (GLA), beta-carotene, linoleic acid, arachidonic acid, vitamin B12, iron, calcium, phosphorus, nucleic acids RNA & DNA, chlorophyll, and phycocyanin, a pigment-protein complex that is found only in blue green algae.

Fig.9. Microscopic view of Spirulina platensis in 40X magnification b. Benefits of Spirulina Spirulina provides a wide range of health benefits almost immediately upon ingestion. It provides a near-instantaneous boost to one's energy, while helping to improve endurance and reduce fatigue. It helps improve the immune system, and provides exceptional support for the heart, liver, and kidneys. Spirulina is also a

Fig.8. Azolla Mother Culture 6. Spirulina as Bio fertilizer a. What exactly spirulina is Spirulina is one of the oldest life forms on Earth. In fact, this blue-green microalgae is partly responsible for producing the oxygen in the planet's atmosphere that billions of years ago allowed the planet's originating life forms to develop. Spirulina is the world's first super food, and one of the most nutrientrich foods on Earth. Spirulina has between 55 and

natural detoxifier, oxygenating the blood, and helping cleanse the body of toxins and other impurities that may be causing illnesses or other health complications. Spirulina is also a natural appetite suppressant, and it helps to improve the body's digestive system. It also has very powerful antioxidant properties and it helps to balance the body's pH, thereby reducing inflammation throughout the body in a safe and chemical-free way.

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c. Sources of Spirulina Spirulina is a spiral-shaped microalga that grows naturally in the wild in warm, fresh water lakes. Its deep blue-green color is what gives the water its greenish hue. Spirulina is also cultivated and harvested in man-made reservoirs like those used

by Nutrex Hawaii, on the Kona coast of Hawaii.

This particular type of spirulina is the only one of its kind to be cultured in a Bio Secure Zone that is free of pesticides, herbicides, and GMOs. Available in both powder and tablet forms, Nutrex Hawaii's 100% vegan Hawaiian Spirulina PacificaÂŽ is a unique, superior strain of Spirulina, with the highest known nutritional content in the world.

however, contain iodine, so those allergic or sensitive to iodine should avoid taking it. e. Pigments: Spirulina contains distinctive natural pigments, including carotenoids and C-phycocyanin (C-PC). Phycocyanin is a pigment-protein complex from the light-harvesting phycobiliprotein family, along with allophycocyanin and phycoerythrin. It is an accessory pigment to chlorophyll. All phycobiliproteins are water-soluble, so they cannot exist within the membrane like carotenoids can. It is a blue pigment that is important in the photosynthesis (food production) of cyanobacteria. It assists the function of chlorophyll especially during low light conditions. Spirulina is reported to contain diverse type of pigments as well as essential fatty acids as below -

d. Side Effects of Spirulina Spirulina is a safe and effective super food that is highly digestible, with no side effects. It does, Table. 2. Nutritive and Medicinal importance of Spirulina

SL No.

Minerals

Quantity (mg / Kg)

SL No.

Vitamins

Quantity (mg / Kg)

1.

Calcium

10,000

1.

Beta Carotene

1400

2.

Phosphorus

8,000

2.

Vitamin E

100

3.

Magnesium

4,000

3.

Thiamine

35

4.

Iron

1,500

4.

Reboflavin (B-2)

40

5.

Zinc

30

5.

Niacin (B-3)

140

6.

Copper

12

6.

Vitamin B-6

8.0

7.

Manganese

50

7.

Vitamin B-12

3.2

8.

Chromium

2.8

8.

Folic Acid

0.1

9.

Sodium

9,000

9.

Biotene

0.05

10

Potassium

1,400

10.

Pantothenic Acid

1.0

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Phycocyanin -iii. Cosmetics -1

C-phycocyanin (C-PC) - 29.7 to 86.1 mg g . allophycocyanin (A-PC) - 2.53 to 6.11% R-phycocyanin (R-PC) 5.75 to 12.35% Chlorophyll - 1.1042 - 3.3004 mg/ml Total Carrotinoids beta-carotene 49.6 to 319.5 μg g-1 lutein 0.06 to17.21 μg g-1 astaxanthin 6.61 to 160.27 μg g-1 zeaxanthin 1.25 to 18.55 μg g-1 cryptoxanthin 1.41 to 20.13 μg g-1

Spirulina is used as pimple lotions, Facial asks, Hair oil, Shampoo, Mineral bath, Skin cleaner, Tooth paste. iv. In Pisciculture Speciality feed for aquarium fish, Colour enhancement feed for Gold fish, Formulation with existing feeds for augmentation of vitamins, High protein feed for table variety fishes (fresh water), and Special feed for shrimp farming.

f. Essential Fatty Acids (gm/Kg) v. In Poultry Linolinic Acid α Linolinic Acid

8.0 10.0

As a feed supplement for enhancing production of broilers / Table birds.

g. Application Areas vi.

Extraction from Spirulina

i. Food Supplement – The World Health Organisation (WHO) has found Spirulina to be an excellent food for human consumption and Spirulina has the approval of the Food & Drugs Authority of the United States for being sold as a natural food.

In Japan and in the United States, business executives take Spirulina tablets to combat stress. Athletes and joggers take Spirulina for quick energy synthesis.

ii. Health &Medicine

Beta-carotene for medicinal & laboratory use, Cphycocyanin colouring agent in food, microbiological areas cosmetics, C-phycocyanin - colouring agent in food, cosmetics, etc. Chlorophyll -colouring agent, Essential amino acids - for microbiological & chemical essays mulberry consuming silk worm, Specialty feed for breeding. vii.

Process of Cultivation

Spirulina Cultivation essentially consists of four major steps which are -1. Development of inoculum 2. Culturing the Spirulina in the production ponds 3. Separation and washing of the bio-mass from the growth medium 4. Drying or dehydration of bio-mass

Non insulin dependent diabetes; Cholesterol control; Vitamin ‘A’ deficiency & malnutrition; Adjunct to cancer patients undergoing chemotherapy; Formulations with other natural products as a general health supplement; Liver corrective for liver disorder; Burns therapy, skin grafting; Control obesity; Lactating agent for mothers.

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7. CONCLUSION From time immemorial, farmers all over the world have used compost, green manures and other organic residues as major sources of nitrogen to promote plant growth and increase crop production.

In recent year’s commercial fertilizer have supplied the bulk of the coffee industry's fertilizer needs. Both economic and environmental considerations strongly favor biological nitrogen fixation as the process of choice in the future. Azolla has the potential of supplying part of the nitrogen requirement of coffee through biological means. In approximately 75 days, a hectare of azolla can produce three layers of green manure. The value of this amount to 25 kg nitrogen per hectare. The azolla can be harvested and either incorporated into soil or used in the preparation of compost.

We have interviewed a number of second generation and third generation farmers from coffee growing regions and they are of the opinion that the farming communities in the early 1930’s and 1960’s were familiar with the use of Azolla as a green manure. However, with the discovery of synthetic fertilizers, the fern slowly lost its prominence. They also point out to its present disappearance from its natural environs due to the indiscriminate use of herbicides, pesticides and weedicides.

Unfortunately, today, the fern is present in only a few pockets and need to be carefully nurtured like an endangered species. We are confident that in the coming years, the combined efforts of scientists and planners will stimulate the interest of coffee farmers, in the use of azolla as an ecofriendly bio fertilizer in supplying the nitrogen needs of coffee.

Spirulina represents a biomass of cyanobacteria that can be consumed by humans and other animals.

The two species are Arthrospira platensis and A. maxima. Cultivated worldwide, Arthrospira is used as a dietary supplement or whole food. Spirulina Plankton (Spirulina platensis) is a blue-green vegetable micro-algae found in the highly alkaline lakes of Africa and Mexico. The natives of these places have been using Spirulina as part of their diet for centuries. Today, Spirulina cultivation is becoming a world-wide phenomena owing to its

extra-ordinary nutritional qualities.

The various considerations that highlight the importance of Spirulina under present day context are: The only single, natural source providing the highest amount of protein ever known to man is Spirulina which contains 71% protein. The protein content in Spirulina is three times that of soybean, five times which of meat and the protein quality is among the best with a good degree of amino gram. The protein yield per unit area per year is the highest compared to other protein yielding crops. Like all other microbial cells, Spirulina contains all natural vitamins including the 'B’complex range, minerals and growth factors including gramlinolenic acid (highest after milk).

It contains the highest amount of β -carotene a precursor of Vitamin 'A'. It is the only vegetable source of vitamin 'B-12' containing two and half times that of liver. The concentration of nucleic acids is among the lowest recorded for microbial cells considered as food or feed. The other micro organisms including those pathogenic to humans and other animals are eliminated in the production process of Spirulina due to its requirement of a very high alkaline growth medium. The only single, natural source providing the highest amount of protein ever known to man is Spirulina which contains 71% protein. The protein content in Spirulina is three times that of soybean, five times that of meat, and the protein quality is among the best with a good degree of amino gram. The protein yield per unit area per year is the highest compared to other protein yielding crops. Like all other microbial cells, Spirulina contains all natural vitamins including the 'B' complex range, minerals and growth factors including gram-linolenic acid (highest after milk and ‘evening prime rose oil‘ ). It contains the highest amount of b - carotene a precursor of Vitamin 'A'. It is the only vegetable source of vitamin 'B12' containing two and half times that of liver. The concentration of nucleic acids is among the lowest recorded for microbial cells considered as food or feed. The other micro organisms including those pathogenic to humans and other animals are eliminated in the production

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process of Spirulina due to its requirement of a very high alkaline growth medium. Spirulina's preference for tropic and sub tropic climatic conditions offers a best land use in arid areas.

Experimental use of Azolla as Tilapia feed indicates highly satisfactory results when fed for 3 weeks with diets containing Azolla as filler. Four dietic.

Component ( A,B,C,D) Diet/composition (%) were tested. The feeding results are expressed as the percentage of the weight gain of the fish. The control diet (A) containing 68.9% flour as filler exerted a slightly unfavourable effect on the percentage of weight gain (56.4%) in Tilapia for 3 weeks, compared with the diet containing a-starch and cellulose powder (Shiomi and Kitoh 1987b). Other diets with increasing concentrations of Azolla were not suitable. Diet B which contained 20.7% Azolla, displayed the same effect as the control for 2 weeks, then induced a 5.2% decrease in Tilapia weight after 3 weeks. Diets C and D exerted the same effect on the growth of Tilapia after 3 weeks of feeding with a 17% decrease of growth compared to the control.

Diet A consisting of only flour as a filler would be ideal. Hence, the fact that the diet containing 20.7% of Azolla (B) induced the same effect on growth as that of the control is highly significant. Attempts were made to improve the food of Tilapia using various mixtures. It is envisaged that about 10% of commercial fish meal can be replaced by soybean refuse. The results indicate that Azolla can replace about 20% of Tilapia feed, which indicates the beneficial effect of the use of aquatic plants. Though Azolla could become a potential source of fish feed, factors such as nutritional value of various species or changes with aging, edibility, stable yield of Azolla, and storage techniques require further studies.

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References: 1.

2.

3.

4.

5.

6.

8.

Anand Titus Pereira (1984) Multiplication of Azolla isolates in soils of Karnataka. Thesis submitted to the University of Agricultural Sciences, Bangalore for the Degree of Master of Science in the Agricultural Microbiology.

Anand Titus Pereira & Shetty K.S. (1987) Physiological Properties and response to different levels of phosphorus by four azolla isolates. Seventh Southern Regional conference on Microbial Inoculants, U.A.S, Bangalore.

Anand Titus Pereira & Shetty K.S. (1987) Studies on the morphological & physiological characteristics of five azolla isolates (Azolla pinnata). Seventh Southern Regional conference on Microbial Inoculants, U.A.S, Bangalore.

Anand Titus Pereira & Shetty K.S. (1987) Effect of pesticides on the growth and nitrogen fixation of Bidadi isolate of Azolla pinnata. Seventh Southern Regional conference on Microbial Inoculants, U.A.S, Bangalore.

Anand Titus Pereira & Gowda, T.K.S. (1987) Hydrogen supported Di Nitrogen fixation in bacteria associated with wetland rice endorhizosphere. International Symposium and workshop on Biological Nitrogen Fixation associated with rice production, Central rice research Institute , Cuttak, India.

Anand Titus Pereira & Gowda, T.K.S. (1991) Occurrence and distribution of hydrogen dependent chemolithotropic nitrogen fixing bacteria in the endorhizosphere of wet land rice varieties grown under different agroclimatic region of Karnataka. (Eds. Dutta, S.K. and Charles Sloger, U.S.A) in biological nitrogen Fixation Associated with Rice production. Oxford and I.B.H Publishing Company Pvt. Ltd. India.

9.

10.

11.

12.

13.

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15.

16.

17.

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Alexender, M. (1974) Microbial Ecology, New York, John Wiely and sons.

Alexender, M. (1977) Introduction to soil Microbiology, 2nd edition, New York, John Wiley and Sons.

Atlas, R.M. & R. Bartha. (1993) Microbial Ecology: Fundamentals and application. Third edition.

Benjamin/Cummings Pub. Co. Newyork.

Brock, T.D. (1979) Biology of Microorganisms Third Edition. Englewood Cliffs. Prentice-Hall.

Kotpal , R.L. and N.P. Bali (2003) Concepts of Ecology : Environmental and Field Biology. Vishal Publishing Company. India.

Khilam, K (1994) Soil Ecology. Cambridge University Press, Cambridge, England.

Paul, E.A. and Clark, F.E. (1996) Soil Microbiology and Biochemistry, Academic Press. Jiaa Sy Spier. 6th century A.D. Chi Min Yao Shu. Michelle and Jude Fanton. (1990) Azolla-fertilizer, mulcher and weed suppressant. 1990 International Permaculture Journal, 35. March- May. Nobuyuki Shiomi and Shunji Kitoh, 2001. Culture of Azolla in a Pond, Nutrient Composition, and Use as Fish Feed. Soil Sci. Plant Nutr., 47 (I), 27-34.

Venkataraman , L.V., 2005. Algal Industrial application – Does it has a future ? Indian Hydrobiology . 7, 43 – 47.

Yatazawa, M., Tomomatsu, N., Hosoda, N., and Nomura, K. 1980: Nitrogen fixation in Azolla-Anabaena symbiosis as affected by mineral nutrient status. Soil Sci. Plant Nutr., 26, 415-426. Watanabe, I., Espinas, e.R., Berja, N.S., and Alimagno, B.V. 1977: Utilization of the Azolla-Anabaena complex as a nitrogen fertilizer for rice. IRRI Res. Paper Ser., No. ll, p. 1-15

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AN PERFORMANCE COMPARISON ON SPACE COMPLEXITY OF WEB USER TRACKING FOR CLUSTERING AND CLASSIFIERS Mr. N . Ulaganathan Ph.D. (Part-Time) Research Scholar Department of Computer Science Nandha Arts and Science College Erode, Tamil Nadu, India E-mail ID: ulaganathanjdk@gmail.com Dr. S. Prasath Research Supervisor & Ass.Professor, Department of Computer Science Nandha Arts and Science College Erode, Tamil Nadu, India E-mail ID: softprasaths@gmail.com Abstract- Web usage mining is the process of examining the web access logs navigation patterns which comprise browsing behaviors of all users over web. The activities of each user on web are stored in the form of weblog files or weblog database. The access activity on web signifies that the number of web pages and the number of times are sequentially visited by the user at different sessions. Through the examination of behavioral navigation patterns, the traffic patterns are mined from weblog database and the future access of the web user is predicted as well as the location of web user is tracked in a significant manner. During the web user behavior analysis, the mining of web traffic pattern is a challenging task. Also, the lack of web traffic pattern mining leads to reduce the performance in the identification of web user location. For the extraction of traffic patterns, the machine learning of clustering and classification techniques are utilized in the mining process to provide accurate results. With this intention, the proposed research work is implemented with web user by effectively mining the patterns from weblog database. The clustering was developed with the aim of predicting the frequent web pages on weblog database browsed by a user but the prediction time remained unaddressed. In order to address the existing issues, three proposed techniques Clustering and Classifier technique based Web Pattern Clustering technique are implemented. The goal of attaining effective web data usage analysis by achieving higher clustering efficiency with less latency. At the beginning process of proposed method to collect the information of all users from weblog database by using server log

files. Further, clustering approach is employed to perform similar user interest web pages from the obtained relevant the space complexity.

Keywords: Web Data, Clustering, Classifier, Space complexity.

I.INTRODUCTION An existing web usage mining approach predicts the online navigational behavior and failed to provide efficient results on prediction performance of web user behavior. The main aim of web service ranking approach is developed with collaborative filtering to identify the potential user behavior after determining user behavior with their past access. The performance of clustering is not carried out in an effective manner.

An existing Hybrid Sequence Alignment Measure (HSAM) is implemented in order to estimate the distance among session pair by considering the user navigated paths but it failed to minimize the latency for analyzing the web user data.

The aim of addressing the existing issues related to the prediction rate and time. In the initial step, the web patterns in a weblog database are grouped based on the different session by performing preprocessing. By grouping the web patterns into a number of sessions based on access time, the time consumption for performing effective web traffic pattern mining is reduced. Further, the classifier is performed in order to classify the web patterns as frequent or non-frequent patterns by measuring the hit ratio. Finally, the analysis determines the correlation of web patterns on different

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II.

RELATED WORKS

Amit Dipchandji Kasliwal et al. [3] discussed web usage mining method. The process of deletion is carried out on insignificant data and mining log file is provided with mining tool for obtaining adapted access and executed this by making different user to visit the website through processing. Web usage mining is utilized for frequent model in which user visits the website for managing website structure and recommends for users but Web usage mining method failed to improve their true positive rate.

Pablo Loyola et al. [5] designed an ant colony optimization-based algorithm for identifying web usage patterns. A number of data sources namely web content and structure and web usage is incorporated.

This followed continuous learning approach is where artificial ants attempt to fit their sessions with actual sessions by alteration of a text preference vector. The trained ants are set to free onto a web graph and artificial sessions are compared with actual sessions. An exact identification of aggregated patterns of actual usage is achieved and quantitative representation of keywords is attained with navigational sessions. The response time are not reduced to desired level.

Preeti Sharma et al. [6] considered web mining techniques for attaining a viable edge in business. Web mining is employed for electronic means of functions to perform business. Web mining is relevant to the data mining approaches employed for identifying patterns from web by means of content mining, structure mining and usage mining. A competitive merit was achieved in business by web mining but Web traffic prediction did not facilitate in improving the efficiency.

Rekha Jain et al. [7] considered Page Rank, Weighted Page Rank and Hyper-link Induced Topic Search (HITS) algorithms for ranking web pages. Page Rank and Weighted Page Rank are Web Structure Mining. HIT was utilized in both structure Mining and Web Content Mining. The score at indexing time was estimated by Page Rank and Weighted Page Rank for arranging with respect to page significance. HITS could evaluate the hub and ability score of appropriate pages but

the computational complexity is not reduced for attaining efficient results.

Lu Dai et al. [8] considered efficient particle swarm chaos optimization mining approach. The chaos optimization mining approach employed feedback model of user for offering superiormatching web pages for user. An initial population of particles moving in D-dimensional search space is considered. Every particle vector is represented to a probable resolution through a subset of web pages. Though the performance of chaos optimization approach is evaluated in terms of response time, execution time, precision and recall for achieving better performance, chaos optimization approach failed in optimization issues.

Maryam Jafari et al. [9] analyzed Web Usage Mining (WUM) and pattern extraction approaches. The patterns obtained after discovery are employed in pattern investigation phase. Followed by investigation of Web user navigational patterns, user behaviors and Web structure are recognized for modeling improved Web machinery and Web relevance.

Classification accuracy is minimized by using Web Usage Mining.

Satpal Singh et al. [10] explained web usage mining for user identification. Web mining with distinct approaches are proposed for various applications. The classification of web-user was discovered with various dimensions of temporal web mining. Clustering efficiency got minimized by using web usage mining.

Sergio Hernandez et al. [11] described lineartemporal logic model checking technique for structured e- commerce web logs. E-commerce configuration based general mapping log records and web logs are transformed into event logs in which the user behavior is extracted. Various predefined queries are carried out for discovering distinct behavioral patterns with user performance at the time of a session. Specific enhancements are made in website modeling to improve their efficiency. However, Computational complexity is

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high when compared to other conventional checking methods.

Shilpa Mahajan et al. [12] discussed user behavior pattern investigation through the estimation of web users in websites. The essential data source in web browsing is web logs which accumulates the user behavior on web pages. The produced logs are examined in phases and classification methods are implemented for identifying the upcoming user behavior. The identified data are employed by Ecommerce organizations for recognizing customer necessities to enhance the website data and associations. In addition, E-commerce companies also employed the user behaviors for recognizing customers and employee actions.

However, the quality of extracted data decreased.

Tania Cerquitelli et al. [13] discussed Mining Neubot Data (MiND) for examining the features of periodic internet measurements gathered at end user location. MiND is enabled for identifying group of users with an identical internet access behavior and anomalous service. The user measurements are designed by histograms and two-level clustering strategy. A maximum set of users are collected into homogeneous and cohesive clusters with respect to internet access service and users with anomalous services are represented as outliers. Internet Service Provider (ISP) is observed by the users in which ISP effectively discovered anomalous behaviors and acts respectively but MiND failed in reducing the prediction time to desired level.

Vagner Figueredode Santana et al. [14] discussed an identification tool for discovering usage patterns which depended on client-side event logs and event stream composition distinctiveness. A system is employed in recording the usage information at actual utilization and usage patterns are predicted for addressing probable user interface design issues.

In addition, discovery of usage patterns and categorization of event streams is performed. The time consumed for identifying the users behavior is increased.

Zheng Xu et al. [15] suggested personalized web search using semantic context. The technique collected user context to present accurate preferences of users in personalized search. The short-term query context was generated to identify related concepts of query. The user context was produced depended on click through the data of users. A forgetting factor was developed for combining the self-governing user context in user session to preserve the evolution of user preferences. Clustering and classification methods of web pages were not included to get accurate outcomes.

III.

METHODOLOGY

In order to overcome the limitations in the existing methodology proposed a method for performing effective web mining.

3.1

Web Usage Mining Approach

Abdelghani Guerbas et al. [1] designed Web Usage Mining Approach for web log mining and online navigational behavior prediction. The design of Web Usage Mining Approach includes different phases such as data cleaning and preparation, density based clustering and online pattern prediction. In the initial phase, the approach allows the raw log data and cleans it to provide page views. In this phase, the designed approach uses the time-based heuristic for session’s identification to obtain better quality results.

Then, density based clustering algorithm is developed to mine for detecting navigational patterns. Instead of association rules detection and sequential patterns mining techniques, clustering algorithm is employed for designed approach as these techniques are unable to get low frequent and meaningful patterns. In addition, the clustering algorithm was highly sensitive to the input metric (minimum support) and finds the outliers. Finally, efficient online prediction approach called k- Nearest-Neighbors (kNN) approach is designed for obtaining relevant

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sessions. The online pattern prediction was very useful. The k-Nearest-Neighbors helped to minimize the server processing time through caching pages where the pages are demanded by a user. It also recommended products, links, online services and so on. Based on the concept of detecting sessions as documents, page references and Web Usage Mining Approach have been designed. This helped to perform pattern prediction of an online session for most relevant documents to a query with higher accuracy. However, the process of clustering could not be carried out in an efficient manner.

3.2

Web Service Ranking Method

Guosheng Kang et al. [4] developed an effective Web service ranking approach for analyzing the user log. Depending on the collaborative filtering (CF), the ranking approach is developed through examining the user behavior. This was done by considering invocation and query history to gather the potential user behavior. With the aid of CF, the similarity between related invocations and related queries are determined. During collaborative filtering, if two users invoke the identical Web services, it is considered to be related to some degree. In case, if the invocations are from similar queries including functional and QoS queries, the value of user similarity tends to be higher, since it denoted similar usage behavior pattern or similar intention from the two users. In Web service selection system, if the user requests a web service, then the services are ranked based on the similar behavior.

Different web services like functional significance, CF based score and Quality of Service (QoS) applicability web services are able to perform efficient web service ranking. The CF based score of a web service is obtained according to the historical functional query, and the recent functional query. Functional relevance was obtained depending on the current functional query and web Services of users. QoS applicability of a web service was achieved based on recent QoS query and its information. Finally, the rank aggregation procedure is employed to

integrate the web services to ignore the impact of range and distribution of variables for web service ranking. The rank aggregation generates the ranking score which appeared in the top-k web service ranking record to the user. However, the developed approach failed to efficiently extract the relevant information from web log.

3.3 Hybrid Method

Sequence

Alignment

Measure

Poornalatha et al. [POO2013] developed Hybrid Sequence Alignment Measure (HSAM) method to discover the distance among user sessions. The main aim of HSAM method was to find out the distance between a pair of sessions on the user navigation paths for web session clustering and assess the quality of clustering. The sequence alignment is denoted as the association of two sessions. The hybrid distance measure considers navigation path information in order to calculate the distance between two sessions without changing the order. The statistic measure is employed in HSAM method to make a decision regarding the number of clusters to be constructed. Jaccard Index and Davies–Bouldin validity index are applied to evaluate the clustering process. The results obtained through these standard statistic indices prove the goodness of the HSAM method.

3.4

Fuzzy Clustering Technique

Anandhi [2] developed Fuzzy Clustering techniques for detecting patterns like path detection, page aggregation, fuzzy clustering, ant-based clustering and graph separation, etc.

Fuzzy Clustering is employed to help the web administrators and web users in order to detect and extract required information in an effective way. The developed Fuzzy Clustering includes preprocessing, user identification, classification and clustering phase. In preprocessing phase, raw data cleaning is carried out to eliminate the unnecessary data and for detecting user and session. The detection of feasible users

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minimizes the processing time for robot entries since it does not contain any irrelevant data. In the next phase, classification techniques are employed to categorize the three types of users from log files. The developed technique classifies whether the user is a frequent user, synthetic user or potential user from web log data. Through the classification process, the attributes or class in a web log data like time stamp and users are taken for detecting the class. Moreover, the potential user was taken for identifying navigation pattern.

Finally, based on the sequence of primarily accessed pages, the clustering techniques are applied to group the next page which is accessed through the web site user. Thus, clustering provides maximum prediction accuracy while predicting navigation pattern. However, the time taken for predicting web patterns failed to minimize.

are effectively classified with higher accuracy by using Classifier. The performance is effectively predicted the web traffic patterns with minimized time consumption.

3.5

4.1 Performance Analysis of Space Complexity

Proposed Methodology

Improved K-means clustering algorithm is developed for finding the browsing activities of user on web. The efficiency for performing the clustering did not increase and the space complexity remained unaddressed. Besides, Hybrid Sequence Alignment Measure (HSAM) was implemented with objective of detecting the distance between any two sessions by utilizing the access path information on website and the reduction of latency remained unaddressed. A novel method was implemented with the objective of providing better results in the web usage pattern detection by the implementation of clientside logging. It failed to minimize the time consumption for detecting the web usage patterns. The proposed Clustering is developed with the aim of extracting the similar web pages which is visited by user with improved clustering efficiency, less latency and space complexity.

Hence, the proposed Classifier technique is introduced with the objective of effectively predicting the web traffic patterns from weblog database with improved accuracy and less time.

In the proposed technique, the frequent or the non-frequent web patterns on weblog database

IV. EXPERIMENTATION AND RESULTS An effective Clustering framework is implemented in Java language using Apache log samples dataset. The Apache log samples datasets identifies the access activities of several web users namely IP address, Date, Time of Access, Port Number and accessed Web page. The performance evaluation of proposed method is compared with the existing Web usage mining approach, Web service ranking approach and HSAM method. The tables and the graphs generated depend on the performance values obtained from experiments to assure the effectiveness of the proposed technique.

The space complexity is defined as the amount of memory space required to store the similar web pages from the web server log files. The space complexity is measured as the difference between the entire memory space and the unused memory space on weblog database. The mathematical expression of space complexity is given a SC = Total memory space – unused memory space …(4.1) In the above equation (4.1), the space complexity is represented as ‘SC’ which is measured in terms of Mega Bytes (MB). The lower value of space complexity enhanced the performance of DFCDPG framework.

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Table 4.1 Performance of Space Complexity

Fig.4.1 Performance of Space Complexity

Space Complexity (MB) Number of web patterns

Web usage mining approach

Web service ranking approach

30

20

22

60

25

27

90

26

120

HSAM method

Fuzzy Clustering

Proposed technique

25

23

14

30

28

19

28

31

29

20

27

29

32

31

21

150

32

34

37

36

26

180

33

35

38

38

27

210

34

36

39

40

28

240

35

37

40

42

29

270

36

38

41

43

30

300

37

39

42

45

31

V. According to the different number of web patterns, the experimental result of space complexity is determined as shown in table 4.1. While carrying out the experiment, the number of web patterns considered ranges from 30 to 300 which are taken as input.

After the experiment, the proposed method is compared with the existing methods for analyzing the results of the space complexity. From table 4.1 shows that the four methods could successfully reduce the space complexity for storing the similar web pages. Comparatively, the proposed method needs less memory space to store the web pages than the other existing methods.

CONCLUSION

The proposed method during web user data extraction from the web database. Through this method user with the visited pages is examined in a sequence manner and the relevant web pages from the web server log files to the web user are stored in memory with less space consumption.

The result is that the space consumed for storing web pages is effectively reduced in the proposed method by 14% and 19% when compared to Web usage mining approach and Web service ranking approach. Similarly, the proposed method reduced the space complexity by 26% when compared to HSAM method and Fuzzy Clustering.

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REFERENCES [1] Abdelghani Guerbas, Omar Addam, Omar Zaarour, Mohamad Nagi, Ahmad Elhajj, Mick Ridley and Reda Alhajj, “Effective Web log mining and online navigational pattern prediction”, Knowledge Based Systems,Elsevier,Vol.49, Pp.No.50-62, 2013.

[2] D. Anandhi and M. S. Irfan Ahmed, “Prediction of user’s type and navigation pattern using clustering and classification algorithms”, Cluster Computing, Springer, Pp.No.1-10, 2017.

[3] Amit Dipchandji Kasliwal and Girish S. Katkar, “Web Usage mining for Predicting User Access Behaviour”,International Journal of Computer Science and Information Technologies, Vol. 6 , Iss. No:1, Pp No.201204,2015.

[4] Guosheng Kang , Jianxun Liu, Mingdong Tang , Buqing Cao and Yu Xu, “An Effective Web Service Ranking Method via Exploring User Behavior”, IEEE Transactions on Network and Service Management, Vol.12,Iss.No:4,Pp.No.554-564,2015.

[5] Pablo Loyola, Pablo E.Roman and JuanD.Velasquez, “Predicting web user behavior using learning-based ant colony optimization”, Engineering Applications of Artificial Intelligence, Elsevier,Vol.25, Iss.No:5, Pp. No.889-897, 2012.

[10] Satpal Singh and Vivek Badhe, “An Exclusive Survey on Web Usage Mining for User Identification”,International Journal of Innovative Research in Computer and Communication Engineering, Vol. 2, Iss. No:11,Pp. No. 6852-6859, 2014.

[11] Sergio Hernández, Pedro Álvarez, Javier Fabra and Joaquín Ezpeleta, “Analysis of Users’ Behavior in Structured e-Commerce Websites”, IEEE Access, Vol.5, Pp. No. 11941 – 11958, 2017.

[12] Shilpa Mahajan and Shilpa Yadav, “Analyzing HTTP Traffic Patterns for Monitoring and Analyzing User Behavior”, Indian Journal of Science and Technology, Vol. 9, Iss. No:48, Pp. No. 1-7, 2016.

[13] Tania Cerquitelli , Antonio Servetti and Enrico Masala, “Discovering users with similar internet access performance through cluster analysis”, Expert Systems with Applications, Elsevier,Vol.64,Pp.No.536–548, 2016.

[14] Vagner Figueredo de Santana and Maria Cecília Calani Baranauskas, “WELFIT: A remote evaluation tool for identifying Web usage patterns through client-side logging”, International Journal of Human-Computer Studies, Elsevier, Vol. 76, Pp. No. 40-49, 2015.

[15] Zahid Ansari, Syed Abdul Sattar, A. Vinaya Babu and M. Fazle Azeem, “Mountain density-based fuzzy approach for discovering web usage clusters from web log data”, Fuzzy Sets and Systems, Elsevier, Vol. 279, Pp.No. 40–63, 2015.

[6] Preeti Sharma and Sanjay Kumar,“An Approach for Customer Behavior Analysis Using Web Mining”, International Journal of Internet Computing, Vol. 1, Iss. No: 2, Pp. No. 1-6, 2011.

[7] Rekha Jain and G. N. Purohit, “Page Ranking Algorithms for Web Mining”, International Journal of Computer Applications, Vol. 13, Iss. No:5, Pp. No. 22-25, 2011.

[8] Lu Dai,WeiWang and Wanneng Shu, “An Efficient Web Usage Mining Approach Using Chaos Optimization and Particle Swarm Optimization Algorithm Based on Optimal Feedback Model”, Hindawi Publishing Corporation, Mathematical Problems in Engineering,Vol.2013, Pp.No.1-8, 2013.

[9] Maryam Jafari, Farzad SoleymaniSabzchi and Shahram Jamali,“Extracting Users’Navigational Behavior from Web Log Data: a Survey”, Journal of Computer Sciences and Applications,Vol. 1, Iss. No.:3, Pp. No. 3945,2013.

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SPICON 2019 summit SPIN International conference and Exhibition was held at Hotel Hilton, Guindy, Chennai on April 20, 2019 with the theme “AgilityAutomation and Cloudification”. The one day conference saw nearly 250+ delegates participating across the IT Industry as well as other industries including Banking, Manufacturing, Automotive, Telecom, Utilities, Retail, Travel etc and with speakers (senior thought leaders) from leading IT services, product and SAAS companies. There was an exhibition which saw participation from Honda, The New Indian Express, Cast Software, Bayline Infocity, Indium Software, Infocareer etc. The supporters of this conference included 15+ industry bodies and institutions including SPIN Bangalore, SPIN Hyderabad, TiE Chennai, IOD, ISACA, CSI-IEEE, CIOKlub, CXOClub, TCC, PMI, Veltech TBI, ACM, ISC2,Cyber Society of India, eWIT, CCICI and CSPF[Cyber Security and Privacy Foundation].

of SPIN Chennai, CEO of Veltech TBI entrepreneurship ecosystem, Founder of Navya Insights), Mr. Pradeep Shilige, EVP of Cognizant, Ms. Sangita Agarwal, CIO Lead, Accenture, Mr.Sreeram Iyer, COO, ANZ Bank, Singapore and Mr.Major Chandrasekaran, Secretary, SPIN Chennai. The conference also saw Special addresses being delivered by David Norton, Director, ex. Gartner, UK and Executive Director, Consortium for IT Software Quality (CISQ) and Suresh Sambandan, Founder and CEO, Orangescape.

Dr.Velan, ED and CEO of Tata Infrastructure and Realty (Ramanujan IT Park, Chennai) was the chief guest and while inagurating and delivering his Chief Guest address, mentioned about how the real estate industry has been working on Agility and Automation as well as AI. He also threw open a challenge to the delegates to come back with solutions to problems that he has at his facility (Rapid growth with smart infrastructure and UK Awards winner etc) which can be potential opportunities for start-ups as well as solution companies.

The discussions and deliberations included focused tracks on Agility, Automation and Cloudification with industry experts as well as SPIN Chennai steering committee members participating. The conference also saw the presentations on case studies which won the top 2 honors during the 2018 Watts Humphrey Awards initiated by SPIN Chennai. Apart from this, there was a “Awards function” for 3 veterans of SPIN Chennai (Dr.L.N.Rajaram, Major Chandrasekaran and Rajamanickkam) who have served the SPIN organization for the Some of the other renowned speakers who last 20 years or so, almost since inception. The participated in the inaugural session include conference also saw some unique surround Dr.L.N.Rajaram (Founding member of SPIN events like CIO and B2B connect, Facebook Chennai), Dr.Bill Curtis (Co-creator of CMM contest, SPICON2019 mega raffle (Amazon model), Mr.Rajaram Venkataraman (President

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kindles were given away), an introductory talk by our International journal partner IJITCE etc.

The Print partner “The New Indian Express” published the inaugural speaker photos, the speakers from various plenaries and 2 post event summaries with one of them a full page coverage of the whole event with group photos, award photos etc.

About SPIN Chennai Software Process Improvement Network, Chennai (www.spinchennai.org) also known as SPIN Chennai is a leadership forum for open exchange of software process improvement experiences and ideas and was established 20 years ago in affiliation with Watts Humphrey Institute, USA as well as Software Engineering Institute of Carnegie Mellon University. Chennai SPIN is one of the oldest of the 130 SPINs in the world today. SPIN Chennai has been the pioneer in promoting various high maturity quality and management practices, processes, frameworks and models including CMMI, ISO, People CMM, Six Sigma, Lean, TOC, BS7799, GDPR, Agile, SAFE, Kanban, Malcolm Baldridge, Balanced Score Card, Blue Ocean Strategy, 5S, 7QC Tools, TQM, Design Thinking, Soc2, Security and Privacy frameworks etc in India.. Some of the world renowned gurus who have given guidance and have visited SPIN Chennai for various sessions include Watts Humphrey (USA), Lewis Trigger (Israel), Bill Curtis (USA)….SPIN Chennai’s partner organizations include FICCI, Nasscom, CII, IEEE, CSI, CIOKlub, CXO Club, ISACA, PMI, CYSI, CSPF, IOD, eWIT, Veltech TBI ecosystem, TiE Chennai, ACM, ISC2 and IJITCE as Journal Partner.

Over the years, SPIN Chennai has evolved itself as a dynamic ecosystem with a nearly 3000 strong community of “whos who” you can think of including Domain experts, SME’s, Thought leaders, leading practitioners, researchers, academics, trainers, mentors, start-ups, consultants, publishers and journal partners like the Internationally renowned IJITCE, HR experts, Operations experts, infrastructure people, marketing experts, supply chain experts, media partners etc.

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Industry 4.0 Premanand Narasimha FIET,MBCS(UK),MIEEE,FIoD(Ind),MIITP(NZ) transition is so compelling that it is being called Industry 4.0 to represent the fourth revolution Industry 4.0 is the combination of digital that has occurred in manufacturing. From the technology into all areas of a business, first industrial revolution (mechanization fundamentally changing how you operate and through water and steam power) to the mass deliver value to customers. production and assembly lines using electricity Industry 4.0 is a name given to the idea of smart in the second, the fourth industrial revolution will factories where machines are augmented with take what was started in the third with the web connectivity and connected to a system adoption of computers and automation and that can visualise the entire production chain enhance it with smart and autonomous systems and make decisions on its own. The trend is fueled by data and machine learning. towards automation and data exchange in manufacturing technologies which include cyber-physical systems Industry 4.0 fosters what has been called a "smart factory". Within modular structured smart factories, cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the Internet of Things, cyberphysical systems communicate and cooperate with each other and with humans in real-time both internally and across organizational services offered and used by participants of the value chain.

With the help of cyber-physical systems that monitor physical processes, a virtual copy of the physical world can be designed. Thus, these systems have the ability of making decentralized decisions on their own and reach a high degree of autonomy (for more information, see “Industry 4.0 characteristics).

As a result, Industry 4.0 networks a wide range of new technologies to create value. We’re in the midst of a significant transformation regarding the way we produce products thanks to the digitization of manufacturing. This

Many organizations might still be in denial about how Industry 4.0 could impact their business or struggling to find the talent or knowledge to know how to best adopt it for their unique purposes, several others are implementing changes today and preparing for a future where smart machines improve their business.

Since connected machines collect a tremendous volume of data that can inform maintenance, performance and other issues, as well as analyze that data to identify patterns and insights that would be impossible for a human to do in a reasonable time, Industry 4.0 offers the opportunity for manufacturers to optimize their operations quickly and efficiently by knowing what needs attention.

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