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ENGR9742 Systems Engineering Assignment Sample

Assignment Brief:

For this assignment, you will work individually. The purpose of this assignment is for you exercise your understanding and knowledge of systems engineering principles to develop a product of your choice.

Task:

Now, imagine that you alone have been tasked with the responsibility to design a product for a customer. In your report, you must:

1. The introduction clearly explains the nature of your product. There must be a top-level system diagram, fully annotated, and referred to in the body of the introduction text.

2. Concise explanation of the application of ethics and standards throughout the testing, integration and eventual de-commissioning of the system.

3. A detailed description of the Stakeholder requirements.

4. A clear explanation of the System Requirements.

5. A clear description of the Functionality analysis.

6. A clear explanation of the development of suitable system architecture.

7. Concise application of the assignment template. Grammar, spelling, punctuation, and use of figures are appropriate. All figures are introduced in the text and their relevance is explained. Identify any safety issues and how they are addressed. Include discussion about any potential undesirable emergent system-behaviour.

Key assumptions and choices are described. There understands of the importance and necessity for feedback from testing phase that informs potential modifications to the requirements or to the functionality.

8. A well-developed architecture is presented. If appropriate, (mathematical) models should be used to explore/optimise parameter settings.

9. There is a clear appreciation and understanding of the products potential failure mode

10. Testing and Verification of the system

11. Validation of the system

12. Factory Acceptance testing and Commissioning Process

13. An informative conclusion that describes the status of the system.

Prepare a detailed report, no more than 20, on the delivery of a successful system to your very wealthy customer. Your report must comply with the template provided. Consult the information regarding the writing of a formal report, available on FLO. Identify your major contribution in the report. Have an introduction and conclusion.

Solution

INTRODUCTION

Smart health prediction system

Anyone may have experienced the frustrating reality that a doctor is needed right away yet none are accessible. The Health Prediction system is an opportunity to help that aims to provide end-user assistance and virtual medical advice. This study focuses on and suggests a method through which people may obtain immediate advice on medical matters via a smart online health care system. A variety of symptoms and the diseases or illnesses they represent are input into the system (Sapkal et al. 2020). Users are able to communicate their problems and symptoms to one another via the system. The system then analyses the user's symptoms to look for potential diseases. In this case, the system employs smart data mining algorithms to determine the most likely diagnosis that corresponds to the patient's symptoms. In the event that it is unable to do so, the system will notify the user of the illness or ailment with which it believes the user's symptoms are most strongly connected. Diseases that the user is most likely to have based on his or her symptoms are shown if there is no precise match in the database. Feedback and an administrator's dashboard are also included, as are doctors' addresses and phone numbers (Nevon Projects 2022).
System diagram


Figure 1: System diagram of health prediction system

ETHICS STANDARDS IN SYSTEM TESTING

In the development and implementation of the Smart health prediction system, many guidelines and regulations have been established for software testing that developers must adhere to in order to ensure that their products are both reliable and up to par with international norms. Moreover, testers are obligated to adhere to a variety of codes of conduct to protect the privacy and security of the data they have access to. Furthermore, they shall comply with the following code of ethics to guarantee the integrity of the works, which includes considering the safety and welfare of the public and the customer. Among the many moral compass systems are-

1. Public: The public interest and benefit should take precedence over business and personal gain throughout the health prediction system development and testing process. They should always make decisions that benefit the public (Professionalqa.com 2018).

2. Product: the software product actually is the most critical thing to think about while evaluating software. The testers' work should be carried out with the goal of assuring the highest possible quality and efficiency of the final product.

3. Employer & Client: In addition to the public interest, health care system testers need to take into account the needs of their company and the people who will be using the programme. They need to behave in a way that satisfies their customers' wants and demands.

4. Profession: the testers' team should uphold the honour of their profession by adhering to a strict code of ethics.

5. Management: team managers and leaders are tasked with taking on the responsibilities and following the ethical procedures necessary to manage the software testing, development, and maintenance process. This will enable them to thoroughly evaluate each part of the programme without causing any misunderstanding (Center for Ethical Practice 2020).

STAKEHOLDER REQUIREMENTS

In the context of a project- Smart health prediction system, the term "stakeholder requirements" is used to describe the aggregated expectations of many different stakeholders. Example stakeholder requirements for Smart health prediction system inspection are shown below.

• Operations: As an example of a capability that is essential to operations is the ability to service technological equipment. As an example, the capabilities of a production line are only one kind of limitation that might originate in the operations division.

• Business units: As an example, the capabilities of a production line are only one kind of limitation that might originate in the operations division. Depending on the nature of the project, product lines may proceed with user stories comprehensive specifications that specify the features, quality, needs, and functionality of the product.

• Customers: as the primary end-user, will provide input in the form of user stories or suggestions to enhance the Smart health prediction system initial usability, quality, and functionality.

• Subject matter expert: the requirements of specialists in fields such as architecture, engineering, layout, accessibility, technology, construction, legislation, and safety System Requirements
Functional requirements

• Creating the user account

• User must enter their authentic details

• User must enter the symptoms and select the options given for evaluation of their condition

• The application should allow the users for changing their profiles when required

• The app must retain the information and ensure top security and privacy

• The user must be able to access the previous reports and have he new one Non-functional requirements

• The app must maintain the privacy of the users and integrity

• It should have a proper database management

• The data must be quickly analysed

• The app must be easy to use and accessible anytime anywhere  

DESCRIPTION OF THE FUNCTIONALITY ANALYSIS

• Patient login- Accessing the system by entering a user id and password.

• Patient registration- If one patient is a new user, the system will ask for his or her information before issuing a client ID and a secret key for entry.

• Prediction of the disease- As a consequence of his illness, the patient will exhibit the symptoms that have been predicted for him. The system will ask specific questions about his condition, analyse the answers to produce a prognosis, and then recommend doctors who specialise in treating the patient's specific sickness.

• Inquiry about Doctor- Patients may do a name, address, or specialty scan to find a doctor. Remark: Data collection: The patient will provide feedback, which will be considered by the administration. Module Position 2: Medically-Trained Expert in the Module Doctor

• Login- to enter the system, Dr. will enter his User Name and Password.

• Details of the patient- Data about the patient: When a patient registers, the specialist may access the information they provide (Reddy et al. 2019).

• Notifications- Alerts The doctor will be informed of how many patients have been admitted to the system and of the full range of symptoms to be expected from the system. 

EXPLANATION OF DEVELOPMENT OF A SUITABLE SYSTEM ARCHITECTURE

To aid professionals in doing their jobs better, we have developed the Smart Health Prediction platform. An initial patient evaluation is performed within a framework that then suggests potential disorders. The process starts with the patient obtaining data about their symptoms; if the system correctly identifies their illness, it will then recommend a specialist who is conveniently located in their area. If the system isn't confident enough, it doesn't ask many questions, and if it's still not confident enough, it'll show the patient certain tests (Wang and Dong 2021). The framework will display the outcome based on the available total data. The study apply some smart mining techniques to determine the most accurate disease that may be related with the patient's outward appearance, and the study base this determination on a database of a few patients' restorative records, to which a calculation (Nave Bayes) is attached for tracing the side effects with possible diseases. Increased efficiency in the delivery of care to patients is a side benefit of this system's design (Li et al. 2021).


Figure 2: Block diagram of the system
(Source: Author 2022)

SAFETY ISSUES AND POTENTIAL UNDESIRABLE EMERGENT SYSTEM-BEHAVIOUR

• Patient data privacy concerns - With the use of Internet of Things (IoT) devices and the increasingly connected structure of the healthcare setting, doctors and nurses may provide better preventative and emergency care for their patients. The health records kept by SHSs are very private. However, SHS make individuals' health records susceptible to a wide variety of assaults. The major obstacles for intelligent medical systems are keeping patients' health information safe and private (Zeadally et al. 2019).

• Inter-realm authentication and interoperability issues- In order to build confidence for the sake of conducting digital health transactions, it is crucial that organisations operating in distinct domains be able to authenticate with one another across multiple realms. Lack of interoperability across countries planning to collaborate on ehealth Infrastructural facilities is another problem that needs attention as a prevalent digital health concern for nations. Lack of legislation for global collaboration among states on the sharing of sensitive medical information is also a contributing factor to this gap, along with insufficient ICT infrastructures and a shortage of IT professionals (Zeadally et al. 2019).

• Abuse of right to access and unauthorised access- By facilitating the safe and trustworthy electronic exchange of health-care information across a wide range of healthcare institutions, health information exchange (HIE) improves the quality of treatment provided to patients. Security and privacy concerns are major reasons why HIE systems haven't been widely used yet. The following are some problems that are experienced by contemporary HIE systems: The first is when trusted insiders misuse their position. The former may exploit their access to the HIMS to steal sensitive information, while the latter may opt to sabotage the system as a means of getting back at their former employers. Third, an outsider tries to hack into the system or pose as a member of the medical staff in order to get access (Zeadally et al. 2019).  

TESTING AND VERIFICATION OF THE SYSTEM

System of test cases drawn from requirement specification to a working system is a common definition of system verification. Creating test cases that accurately represent the objectives in range and special significance after translating the requirements document is a time-consuming process. Man-in-the-loop checking with some little automated processes is the standard, even though automation (test fixtures) must be developed in most cases for engineering assignment help.

• System tests: Like the criteria that inform them, testing procedure are (mostly) transparent. But certain specifications need an amount of internal covering equal to those test cases. That means further requirements need to be added if any portion of the design or the implementation can't be confirmed by the testing process that encapsulates all the needs.

• Wafer test: Initial production testing begins with a wafer test. A wafer prober is often used to provide electrical stimulation to dies on a wafer during a wafer test. Wafer final test (WFT), circuit probe (CP), and electronic die sort are examples of assessment techniques used in this process (EDS). Wafer testing is the last step before final packaging.

• Manufacturing defects test: The second phase involves a test designed to detect problems caused by production. In order to differentiate between the right and defective behaviour of a circuit, a test engineer employs an automatic test pattern generation (ATPG) software to build test patterns. Automatic test equipment (ATE) is used to continuously administer training examples and verify replies.

• Characterisation test: The third stage aims to describe and filter chips before sending them out to consumers. Finding the optimal operational parameters of the device, such as voltage and frequency is the goal of the characterisation procedure.

• Functional test: The fourth stage, the functional test, is the process of applying functional test procedures to a chip in order to locate functional faults. To obtain the required coverage, the various components of the chip are put through their paces using functional test patterns that operate at real-world rates.

REFERENCES

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