Event Management Process system project in python

 

Event Management Process system project in python

PROJECT ID: PYTHON44

PROJECT NAME: Event Management Process system in python

PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING

PROJECT ABSTRACT:

Event management is a process of organizing a professional and focused event, for a particular target audience. It involves visualizing concepts, planning, budgeting, organizing and executing events such as wedding, musical concerts, corporate seminars, exhibitions, birthday celebrations, theme parties, etc. Event Management is a multi-million dollar industry, growing rapidly, with events hosted regularly. Surprisingly, there is no formalized research conducted to access the growth of this industry. The industry includes fields such as the MICE (Meetings, Incentives and Events), exhibitions, conferences and seminars as well as live music and sporting events. On the profession side, event management is a glamorous and exciting profession that demands a lot of hard work and dynamism. The logistics side of the industry is paid less than the sales/sponsorship side, though some may say that these are two different industries.

Event management is the application of project management to the creation and development of large scale events. The process of planning and coordinating the event is usually referred to as event planning and which can include budgeting, scheduling, site selection, acquiring necessary permits, coordinating transportation and parking, arranging for speakers or entertainers, arranging decor, event security, catering, coordinating with third party vendors, and emergency plans. The events industry now includes events of all sizes from the Olympics down to business breakfast meetings. Many industries, charitable organizations, and interest groups hold events in order to market themselves, build business relationships, raise money, or celebrate achievement. An event refers to a social gathering or activity, such as a festival,( for example a musical festival), a ceremony( for example a marriage ) and a party(for example a birthday party).There are mainly 3 types of event management:

EVENT MANAGER

The Event Manager is the person who plans and executes the event. Event managers and their teams are often behind-the-scenes running the event. Event managers may also be involved in more than just the planning and execution of the event, but also brand building, marketing and communication strategy. The event manager is an expert at the creative, technical and logistical elements that help an event succeed. This includes event design, audiovisual production, scriptwriting, logistics, budgeting, negotiation and, of course, client service. It is a multidimensional profession.

EVENT MANAGEMENT PROCESS

There are 2 stages of event management process namely, Event planning and Event control.

Event Planning: To plan an event we must consider the following areas of an event, viz, feasibility, promotion, site choice/design, staging, shutdown, site map, event proposal.

Event Control: To control an event we must look on the following areas logistics, negotiations, costing & cash flow, event manual, I.T, decision making and change, risk management.

 SCOPE OF THE PROJECT

The objective of this application is to develop a system that effectively manages all the data related to the various events that take place in an organization. The purpose is to maintain a centralized database of all event related information. The goal is to support various functions and processes necessary to manage the data efficiently.

EXISTING SYSTEM

 This existing system is not providing secure registration and profile management of all the users     properly. This system is not providing on-line help. This system doesn’t provide tracking of users activities and their progress. This manual system gives us very less security for saving data and some data may be lost due to mismanagement. This system is not providing event management through internet. This system is not providing proper events information. The system is giving manual information through the event management executer.

FEASIBILITY STUDY

A feasibility study is a high-level capsule version of the entire System analysis and Design Process. The study begins by classifying the problem definition. Feasibility is to determine if it’s worth doing. Once an acceptance problem definition has been generated, the analyst develops a logical model of the system. A search for alternatives is analyzed carefully. There are 3 parts in feasibility study.

Operational Feasibility

Operational feasibility is the measure of how well a proposed system solves the problems, and takes advantage of the opportunities identified during scope definition and how it satisfies the requirements identified in the requirements analysis phase of system development.The operational feasibility assessment focuses on the degree to which the proposed development projects fits in with the existing business environment and objectives with regard to development schedule, delivery date, corporate culture and existing business processes.To ensure success, desired operational outcomes must be imparted during design and development. These include such design-dependent parameters as reliability, maintainability, supportability, usability, producibility, disposability, sustainability, affordability and others. These parameters are required to be considered at the early stages of design if desired operational behaviours are to be realised. A system design and development requires appropriate and timely application of engineering and management efforts to meet the previously mentioned parameters. A system may serve its intended purpose most effectively when its technical and operating characteristics are engineered into the design. Therefore, operational feasibility is a critical aspect of systems engineering that needs to be an integral part of the early design phases.

Technical Feasibility

This involves questions such as whether the technology needed for the system exists, how difficult it will be to build, and whether the firm has enough experience using that technology. The assessment is based on outline design of system requirements in terms of input, processes, output, fields, programs and procedures. This can be qualified in terms of volume of data, trends, frequency of updating inorder to give an introduction to the technical system. The application is the fact that it has been developed on windows XP platform and a high configuration of 1GB RAM on Intel Pentium Dual core processor. This is technically feasible .The technical feasibility assessment is focused on gaining an understanding of the present technical resources of the organization and their applicability to the expected needs of the proposed system. It is an evaluation of the hardware and software and how it meets the need of the proposed system.

Economical Feasibility

Establishing the cost-effectiveness of the proposed system i.e. if the benefits do not outweigh the costs then it is not worth going ahead. In the fast paced world today there is a great need of online social networking facilities. Thus the benefits of this project in the current scenario make it economically feasible. The purpose of the economic feasibility assessment is to determine the positive economic benefits to the organization that the proposed system will provide. It includes quantification and identification of all the benefits expected. This assessment typically involves a cost/benefits analysis.

SOFTWARE REQUIREMENTS:

OS                                : Windows

Python IDE                  : Python 2.7.x and above

Language                             : Python Programming

Database                             : MYSQL

 

HARDWARE REQUIREMENTS:

 RAM                :  4GB and Higher

Processor          :  Intel i3 and above

Hard Disk         : 500GB Minimum

Setting up Software Environment

Python is a high level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable and has fewer syntactical constructions than other languages. Python is used in the development of this model. In this experiment, the following python libraries are used to develop the machine learning models:

• NLTK: It is a python package which works with human language data and provides an easy-to-use interface to different lexical resources like WordNet and text processing libraries. These lexical resources are used for classification, tokenization, stemming, tagging, parsing, and semantic reasoning.

• Pandas: It is a python package which acts as a data analysis tool and deals with data structures. Pandas carry out entire data analysis workflow in Python without having to switch to a more domain specific language like R.

• Tweepy: It is used in accessing the Twitter API by establishing the connection and to gather tweets from Twitter. This module is used to stream live tweets directly from Twitter in real-time.

• Numpy: NumPy is the fundamental package for computing with Python. It is used to add support to multi-dimensional arrays and matrices, with a large collection of high-level mathematical functions.

• scikit-learn: It is a simple and efficient tool for data mining and data analysis. 

• matplotlib python library which generates plots, histograms, power spectra, bar charts, etc.

In this work matplotlib.pyplot module is used to plot the metrics.

• Gensim It is used to automatically extract semantic topics from documents, as efficiently as possible. Gensim is designed to process raw, unstructured text data. The algorithms in Gensim, such as Word2Vec where it automatically discovers the semantic structure of phrase by examining statistical co-occurrence patterns within a corpus of training documents. These algorithms are unsupervised. Once these statistical patterns are found, any plain text documents can be succinctly expressed in the new, semantic representation and queried for topical similarity against other documents.

• Keras: Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research a system of supervised learning and anomaly detection system a system of unsupervised learning. What is the difference between supervised learning and unsupervised learning? The answer is that supervised learning studies labeled datasets. They use labeled datasets to train and to render it accurate by changing the parameters of the learning rate. After that, they apply parameters of learning rate to the dataset, the techniques that implement supervised learning such as multilayerperceptron (MLP) to build the model based on the history of the database. This supervised learning has a disadvantage, since if new fraud transactions happen that do not match with the records of the database, then this transaction will be considered genuine. While, unsupervised learning acquires information from new transactions and finds anomalous patterns from new transaction. This unsupervised learning is more difficult than supervised learning, because we have to use appropriate techniques to detect anomalous behavior.

TABLE OF CONTENTS

·        Title Page      

·        Declaration

·        Certification Page

·        Dedication

·        Acknowledgements

·        Table of Contents

·        List of Tables

·        Abstract

CHAPTER SCHEME

CHAPTER ONE: INTRODUCTION

CHAPTER TWO: OBJECTIVES

CHAPTER THREE: PRELIMINARY SYSTEM ANALYSIS

·         Preliminary Investigation

·         Present System in Use

·         Flaws In Present System

·         Need Of New System

·         Feasibility Study

·         Project  Category

CHAPTER FOUR: SOFTWARE ENGINEERING AND PARADIGM APPLIED   

·         Modules

·         System / Module Chart

CHAPTER FIVE: SOFTWARE AND HARDWARE REQUIREMENT

CHAPTER SIX: DETAIL SYSTEM ANALYSIS

·         Data Flow Diagram

·         Number of modules and Process Logic

·         Data Structures  and Tables

·         Entity- Relationship Diagram

·         System Design

·         Form Design 

·         Source Code

·         Input Screen and Output Screen

CHAPTER SEVEN: TESTING AND VALIDATION CHECK

CHAPTER EIGHT: SYSTEM SECURITY MEASURES

CHAPTER NINE: IMPLEMENTATION, EVALUATION & MAINTENANCE

CHAPTER TEN: FUTURE SCOPE OF THE PROJECT

CHAPTER ELEVEN: SUGGESTION AND CONCLUSION

CHAPTER TWELE: BIBLIOGRAPHY& REFERENCES          

Other Information

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