App that rates fitness apps - dissertation example

App that Rates Fitness Apps

App that rates Fitness Apps Insert Insert Introduction The market have varying apps designed to help different people with different fitness practices. However, some of them cannot enable the users to monitor their progress as they continue to carry out the exercises. In this documentation, the design focuses on objectives for building an app that lists fitness apps in terms of positive and negative feedbacks. The application follows a reward-point system for positive results and negative points for negative results. It uses previous data to list sport exercises for any user on the applications with the most success. The development will be on android. The application will run in virtually all gadgets that are android enabled.
Aims and Objectives
Aims
The dissertation seeks to build an application that lists fitness apps used and rated by previous users.
Objectives
To design an application that lists all other fitness apps and their rating in terms of feedbacks accumulated from users.
To integrate fitness applications in the listing app proposed
To institute a positive reward system for positive results and a negative reward system for negative results
To integrate recommendation capability based on previously gathered data
To design and develop the application
Methodology
The process will begin by a feasibility study of the requirements to carry out the process of developing the application. It includes designing specifications of the application, coming up with the right platform and language. The website and links that will be integrated with the app evaluated and collected. The app will be a collection center for all other fitness app by giving rates according to likes and dislikes. The algorithm for incrementing and rating the app will be designed. Upon gathering all the materials, tools and specifications, the coding process will be started. Artificial intelligence ideas concerning app likes and rating will be made an inherent feature in the design. System will be tested and maintained routinely. Stability will be checked against time, varying platforms and processor speeds. A fully developed system will be rolled out and launched into the market.
Literature Review
There are many applications and websites that use the same concept to make recommendations to their customers. The concept regarded here is a ranking system that makes content and collaborative predictions (Gedikli, 2013). An example is Goodreads. It is a huge site for readers and makes suggestions to its readers based on what they had done previously. The proposed application will borrow a lot from the way these applications were implemented. Smart Phones are always with among humans thus it can be monitored for progress and advance in the course of action. Some applications link us to the wider community through support or motivation via races (Snell, 2015). There are numerous applications for every other fitness program including the walking, weight building or lose, general workout, muscle development and running.
Scope
Scope
The scope of this project will be the development of a mobile app with the sole function of keeping track of feedback left by sport exercise users on a fitness app. It will contain all other fitness app, positive feedback tally, negative feedback tally and overall score that an app accrues.
Resources
The development process will require a computer and operating system and integrated development. Skilled labor will be utilized throughout the development divisions.
Timetable
The timetable has been designed to fit the academic semester to avoid other inconveniences as shown below:
Days to Complete the activity
Activity
5
Supervisor gives a go-ahead
10-15
Carrying out a literature review
5
Working on chapter one
3
Working on chapter two
2
Working on chapter three
4
Writing chapter four
2
Review and writing chapter 5
1
Conclusion of the project
2
Feedback on the write-up
3
Doing final revisits, proofreading, printing, binding and submission
List of References
Gedikli, F. (2013). Recommender systems and the social web. Wiesbaden: Springer Vieweg.
Hammersley, M. (2010). Methodology. London: SAGE Publications. Smartphone app is ready for South Australia. (2012). ECOS.
Snell, J. (2015). Fitbit fitness app. Nursing Standard, 29(24), pp. 31-31.