Mobile Device Processing and Food Allergy Application

The assignment details the use of a mobile device application that helps users with food allergies by providing information on safe food joints and analyzing location or distances of food joints. The app requires 12 MB of on-installation storage memory and stores login details in the device's internal memory. It uses online database servers for further processing. The document also mentions the importance of time management in completing the assignment.

Running head: ANTI-ALLERGIC: A HEALTHY EATING APP
Anti-Allergic: A Healthy Eating App
Name of student:
Name of the University:
Author note:

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ANTI-ALLERGIC: A HEALTHY EATING APP
Table of Contents
The Anti-Allergic App...............................................................................................................2
The Information System.............................................................................................................2
Mobile Device Specification......................................................................................................5
Input Devices.........................................................................................................................5
Output Devices.......................................................................................................................6
Reflective Commentary.............................................................................................................6

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ANTI-ALLERGIC: A HEALTHY EATING APP
The Anti-Allergic App
The daily routine of billions of lives around the world depend upon how they wish to
eat and stay fit. However, every human being are not born with the luck to eat whatever he or
she want. There are obese people, who have to control their diet (Zarnowiecki et al. 2012).
Then there are allergic people. To avoid allergic contamination, individuals are needed to be
cautious of what he or she eats and the quantity of it (Sicherer and Sampson 2014).
Information technology is crucial for human health in the modern generation (Jones et al.
2014). In the prospect to warning people off their allergies, the Anti-Allergic app helps a
great deal.
The Anti-Allergic application is available for both android and IOS mobile platforms.
This app is the common person’s guide to find eating joints that serve food according to their
allergic intolerance. They surf through their database to present the user with the best
restaurants that cater for their food allergies. The app developers believes in the concept of
hassle free eating. This app gives the customers the choice to select their food preferences,
measure the level of allergies they behold and then visit them with confidence.
The Information System
A user after downloading the application from their respective app stores first requires
signing up into the system. This application provides quite a handsome number of features to
enhance user health and experience. The information processing system of the application
aims to provide allergy free eating experience, right at the user’s fingertips. Users need to
securely sign in with their personal details like name, password, contacts, and food
preferences and so on. Health information security is important (Agaku et al. 2013). Users are
also given the option to login into the system without an account. However, this will not save
their food preferences.

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ANTI-ALLERGIC: A HEALTHY EATING APP
Fig 1. Home Screen
Once the user has logged in, they are allowed to select what they are allergic to, from
a list of graphic images of the most common allergens. They can also enter other allergens
that do not appear in the provided list. This data then is saved in the app’s server database, for
processing references.

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ANTI-ALLERGIC: A HEALTHY EATING APP
Fig 2. Allergy Preference Page
Once the user has saved their allergic boundaries, the application can finally start its
duty. The application surfs through its server database to present the user with all restaurants
and or food joints that cater food according to the allergic constraints. This section is divided
into three categories based on the distance of the restaurants from the user’s location.
Restaurant names and their respective location is shared with the customer based the 1 mile, 5
miles and 10 miles distance radius. The application uses the GPS feature of the mobile to spot
the user’s location and calculate distances accordingly (Cetateanu and Jones 2016). Here, the
customer choses a particular restaurant as per their wish. This takes them into the particular
restaurant’s Anti-Allergic portal. The grouped menu from the restaurant’s account is then

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ANTI-ALLERGIC: A HEALTHY EATING APP
displayed. Users are required to click on one of the menu groups to view the items that they
cater under each. The system also counts the number of specific menus that these groups can
cater abiding by the allergic constraints. On clicking each item, the user can view the
allergens that these food items contain. Here is where, the application’s information gathering
helps a great zeal. The server has direct connection to the chef’s kitchen. Here, the restaurants
are liable towards updating the database with the ingredients of each item that they cater for
the day. The application surfs through this, analyses the data to filter out the menus that the
user is allergic to and displays the rest.
Users of the apps can also upload pictures of food or write in text the names of foods,
to check the allergens that these items generally contain. Image processing and bar-code
reading is a major aspect of this application. The users are given the ability to scan barcodes
from the food packets to gather information about the ingredients that it contain (Pagoto et al.
2013). The application right away aware them off any allergen. In addition, the restaurants
are rated and reviewed by the customers. This data is used by the Big Data analytic system to
generate popularity index for the restaurants.
Mobile Device Specification
Input Devices
The application requires the mobile’s screen keyboard to take user input of the
required data and search elements. In addition to that, the mobile camera helps to take
pictures of respective foods or restaurants and upload them on the app. It is always
recommended to have a high quality camera that can take clear images to scan bar codes off
the food packages for better image processing (Sonka, Hlavac and Boyle 2014). The camera
records the bar codes from the food packets and decoding is done inside the CPU according
to the underlying software technologies extract information from each of the PD147 codes.

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ANTI-ALLERGIC: A HEALTHY EATING APP
The mobile GPS system helps in finding and analyzing location or distances of food joints.
However, the mobile internet connection is always necessary.
Output and Storage Devices
The mobile screen is basically the only output medium of the application. The outputs
from the CPU are primarily stored inside the RAM. The RAM generates Red, Green and
Blue codes to determine the color and position of display output. Once this data is sent out to
display, the RAM sometimes empties itself to ready itself for more. The RAM forms the
bridge between the processor and graphics unit. From here, the images are flashed onto the
screen at required intervals. More is the RAM size and the buffering speed, faster can the
CPU dump its outputs into it. Figure below shows the working of the RAM, a dual core CPU
and the display unit.
As for storage, the application uses the device’s internal memory to store the login
details of the user. Furthermore, all other work is done off the online database server of the

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ANTI-ALLERGIC: A HEALTHY EATING APP
company. The app requires about 12 MB of on-installation storage memory. Further, it stores
its necessary data as per the processing circumstances.
Reflective Commentary
Being allergic to a certain food items, I myself gained ample help while researching
and using this application. I decided to go with this application to know more about the use of
information technology in health and hygiene. I got the opportunity to surf through a wide
range of internet resources and research materials.
Nevertheless, time was a demeaning factor for me to compile my project. I would
have loved to spend more time with the application and experience more features of it, but I
was held back by time. This is a lesson that I take forward from this assignment.
I also plan to use the mobile device processing knowledge that I gained through this
assignment in the coming future, to cater me more knowledge on information systems.

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ANTI-ALLERGIC: A HEALTHY EATING APP
References
Agaku, I.T., Adisa, A.O., Ayo-Yusuf, O.A. and Connolly, G.N., 2013. Concern about
security and privacy, and perceived control over collection and use of health information are
related to withholding of health information from healthcare providers. Journal of the
American Medical Informatics Association, 21(2), pp.374-378.
Cetateanu, A. and Jones, A., 2016. How can GPS technology help us better understand
exposure to the food environment? A systematic review. SSM-population health, 2, pp.196-
205.
Jia, M.Y., Wu, Q.S., Li, H., Zhang, Y., Guan, Y.F. and Feng, L., 2015. The calibration of
cellphone camera-based colorimetric sensor array and its application in the determination of
glucose in urine. Biosensors and Bioelectronics, 74, pp.1029-1037.
Jones, S.S., Rudin, R.S., Perry, T. and Shekelle, P.G., 2014. Health information technology:
an updated systematic review with a focus on meaningful use. Annals of internal
medicine, 160(1), pp.48-54.
Pagoto, S., Schneider, K., Jojic, M., DeBiasse, M. and Mann, D., 2013. Evidence-based
strategies in weight-loss mobile apps. American journal of preventive medicine, 45(5),
pp.576-582.
Sicherer, S.H. and Sampson, H.A., 2014. Food allergy: epidemiology, pathogenesis,
diagnosis, and treatment. Journal of Allergy and Clinical Immunology, 133(2), pp.291-307.
Sonka, M., Hlavac, V. and Boyle, R., 2014. Image processing, analysis, and machine vision.
Cengage Learning.

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ANTI-ALLERGIC: A HEALTHY EATING APP
Zarnowiecki, D., Sinn, N., Petkov, J. and Dollman, J., 2012. Parental nutrition knowledge
and attitudes as predictors of 5–6-year-old children's healthy food knowledge. Public health
nutrition, 15(7), pp.1284-1290.