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Determine Access Point Locations
Jim Billingsley, Darren Daves, Saida Hossain
University of Phoenix
CYB/360 Week 2: Access Point Locations
1/24/2022
Russ Hann
Access Point Locations
Introduction
The purpose of this document is to identify locations for wireless access points for International Plastics, Inc., corporate headquarters. The overall objective will be to include a logical network diagram of the wireless network and the technical specifications outline in the future.
Corporate Floor Plan and Buildings
IPP Corporate headquarters has one main building with 6 floors, each floor measures 16,000 square feet. Offices are located around the perimeter, with cubicles located internally. The environment while large and open will still encounter interference with internal devices and machines as well as potential signal loss in stair wells and the transition from the main headquarters to the 2 adjacent manufacturing buildings. The wireless access points must be installed in specific locations to ensure optimal coverage and signal strength to ensure the devices and employees are able to connect and perform their routine functions with limited interference and degradation of the signal.
Recommended Wireless Access Point Locations
The wireless access points should be located above the ceiling tiles or along the walls at ceiling height with omnidirectional MIMO antennas to provide adequate access points. Using a grid pattern wireless access points should be installed approximately every 1,600 square feet. This will require 10 wireless access points to be installed on all 6 floors of the corporate headquarters for a total of 60 wireless access points.
For building A, at 20,000 square feet single level facility will require 13 wireless access points installed above the ceiling tiles or high up on a wall. Building B measures 24,000 square feet which will require 15 wireless access points installed above the ceiling tiles or high up on walls in a secure manner. This makes for a total of 88 industrial wireless access points.
References
University of Phoenix. (). CWNA Certified Wireless Network Administrator Study Guide: Exam CWNA-108 Ch. 5. https://bibliu.com/app/#/view/books/9781119734536/epub/OPS/c05.html#page_197
University of Phoenix. (). CWNA Certified Wireless Network Administrator Study Guide: Exam CWNA-108 Ch. 14. https://bibliu.com/app/#/view/books/9781119734536/epub/OPS/c14.html#page_581
University of Phoenix. (2022). IPP Corporate Buildings. IPP Corporate
University of Phoenix. (2022). International Plastics, Inc., Network Description. International Plastics Network Description
University of Phoenix. (2022). IPP Network Headquarters Diagram. IPP Network Headquarters Diagram
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IPP Corporate Headquarters –�ϭϲ͕ϬϬϬ�square feet @ 6 floorsVisio of Wireless Access Points locations for each floor
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IPP Corporate Headquarters – 16,000 square feet @ 6 floors
Visio of Wireless Access Points locations for each floor
IPP Corporate Building A –�ϮϬ͕ϬϬϬ�square feetVisio of Wireless Access Points locations for each floor
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IPP Corporate Building A – 20,000 square feet
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IPP Corporate Building B –�Ϯϰ͕ϬϬϬ�square feetVisio of Wireless Access Points locations for each floor
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IPP Corporate Building B – 24,000 square feet
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ERD Model
Charlena Johnson
02/27/2022
Lindsay Nardi
University of Phoenix
Data being collected
The data collected pertains to medical details (Ramadhany & Azwir, 2020).
This is to help identify a patient and what they are suffering from.
Collection of this data is as a guideline of tables and attributes given in Patton Fuller Website.
This exercise involves the collection of data about a patient. Collecting data about a patient is very important at the initial stages of starting medication. It helps understand who can be contacted by the family of friends, so offer family support to a patient. It also helps document the names of physicians or, rather, doctors involved in the treatment of a patient. Furthermore, data collection makes it easy to keep reference documents used for future references. Thus, in a nutshell, the data being collected makes it easy to make references in the future when accounting for health improvement for a patient.
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Requirements being met
The requirements being met are:
Collect information about a patient.
The name of their guardian (Bhattacharjee, Benjafield, Armitstead, Cistulli, Nunez, Pepin & Malhotra, 2020).
The details of the physician being involved.
The treatment plan and.
The result was diagnosed.
From the Pattonfuller Community Virtual Organization website, there are different goals to be achieved in collecting these data. These goals can be categorized into three. One, this is the goal of the information about a patient. This involved the attributes of patient names and their parents of guardians. The second goal to be achieved is to ascertain the details of the sector that will be giving a treatment. The third requirement that has to be achieved is health and medical details. This pertains to the tests, results, and the medication approved to manage an ailment.
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Use of data in decision making
Data collected in this exercise can decide different levels (Moser & Korstjens, 2018).
One, the medical diagnosis can be used to determine the treatment plan.
The treatment plan can be used to decide on how the effectiveness of the medication can be ascertained.
Once the data has been collected, it can be used to decide as the patient receives medication. Take, for instance, the detail about a patient and their guardian. This data can be used to decide on the best way to reach a guardian or a patient. This could be advising them to visit a hospital near their state or even contacting them via the phone details that they have available. Information about medication and tests can be used in deciding how to do follow-ups on patients’ recovery. Take, for instance, where a patient has been administered a dosage that should last for a predetermined time. This could be used at the end to determine if the patient’s status as per the patient’s expectation is still under threat of the ailment they were suffering.
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Entity Relationships Diagram (ERD)
Patient information
Name
Address
City
State
Zip
Phone
Date of birth
Gender
Parent/guardian name
Address
City
State
Zip
Registration ID
Primary physician name
Address
City
State
Zip
Registration ID
Issuer Name
Address
City
State
Zip
Phone
Fax
Patient group ID
Patient subscriber ID
Attending physician
Medical Diagnosis
Treatment plan
Medication name
Dosage
Frequency
Duration
Start date
Comments
Procedure
Date of procedure
Performed by
Results
Blood pressure
Questions
The above figure shows the Entity Relationships Diagram (ERD) in the medical setting. In a medical setting, data collection starts with the patient himself. There are many attributes about a patient, and they might differ from one patient to another. After the patient’s data has been collected, it is followed by the primary physician’s name. This should be followed by the issue’s name and the actual physician attending a patient. This is important in helping to understand who did what in attending to the clinical needs. Once the attending physician has been identified, they conduct the medical diagnosis, decides on the treatment plan and later does tests to ascertain how well a patient is recovering from the treatment plan settled upon.
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Attributes
There are eight attributes in this ERD as shown in the ERD relationship diagram.
These are:
Patient Information
Parent/guardian name
Primary physician name
Issuer name
Attending physician
Medical Diagnosis
Treatment plan
Results
Attributes are the primary and secondary keys in the above Entity Relationship Diagram. The primary key is the starting point of an ERD, while the secondary key is the ending point of the relationship is the ERD. In the above given ERD model, the primary key for the medical ERD is the patient information. All other attributes from parent or guardian information to the results are the secondary keys in the ERD model. They are strictly determined and dependent on who the patient is.
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Fields in Attributes
Each of the attributes named above has fields in it.
Fields are the precise information filled in the collection of data and information.
These fields are categorized together in an attribute, and together they are formulated in an ERD diagram and relationship.
A field in an attribute is the actual data to be filled. An attribute can have single or multiple fields. In other cases, some attributes do not have fields that follow them. From the ERD model above., both the attending physician and the medical diagnosis have no fields. This does not make these two attributes less important. They are equally important and regarded as complete even without fields below them. The other attributes have fields, and fields are dependent on the nature of the attribute. An attribute on identity is followed by a field on identification, while fields about medical administration follow an attribute on medication.
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Tables, entities and relationships
The relationship in this ERD diagram shows how information is collected right from the patient to the results (Karami & Hafizi, 2021).
Patient information in this relationship is considered the primary key.
The rest attributes from parent information to the results are considered as the secondary key in the ERD diagram.
Together, tables, fields, and even entries make the ERD model. The model cannot stand on its own without any of these. Thus, tables, attributes, fields, and entities are the conglomerate of the ERD model. They are relied upon to establish the order of events to follow from receiving a patient in a hospital setting and deciding the best medication to be issued to such a patient. This is helpful to ensure there is no conflict of interest due to conflict of the order of entities and relationships when handling a patient.
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Conclusion
In conclusion, ERD is very important in the understanding collection of data.
The above scenario shows how data can be collected in a hospital setting.
This ERD shows how the scenario can collect data from patients and be relied upon to decide a medical setting.
To conclude the ERD model above, it is important to understand its use, as discussed above. The ERD model above is used to collect patient information about their identity and diagnosis in a medical setting. The ERD model is characterized by tables, attributes, fields, and entities. Together, these make the ERD model and relationship, as discussed in the above slides.
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REFERENCES:
Ramadhany, S. E., & Azwir, H. H. (2020). Developing database system for managing medical insurance claims in the human resource department. Performa: Media Ilmiah Teknik Industri, 19(2).
Bhattacharjee, R., Benjafield, A. V., Armitstead, J., Cistulli, P. A., Nunez, C. M., Pepin, J. L. D., … & Malhotra, A. (2020). Adherence in children using positive airway pressure therapy: a big-data analysis. The Lancet Digital Health, 2(2), e94-e101.
Moser, A., & Korstjens, I. (2018). Series: Practical guidance to qualitative research. Part 3: Sampling, data collection and analysis. European journal of general practice, 24(1), 9-18.
Karami, M., & Hafizi, N. (2021). Health Information from Management to Technology: Development of a Radiology Patient Safety Monitoring System.