Smart systems fall detector

Smart systems fall detector

ASSESSMENT TASK Smart systems fall detector
You are given a brief case study of an application domain, and you are asked to analyse it and produce a number of deliverables for the final requirements and system design documents.

You need to choose to model only one context-awareness scenario from the case study and you are required to create two diagrams from each kind: one higher-level diagram for the whole system and one lower-level diagram that corresponds to the scenario that you have chosen.

Deliverables and Assessment Criteria / Marking Scheme

Part 1: Requirements identification and modelling for Smart systems fall detector

Produce two SysML Requirements diagrams for the given case study:

The models will be marked against the following criteria:

• Completeness as regards to the chosen scenario (conceptual).
• Appropriate separation of the problem into constituent parts (conceptual).
• Appropriate separation of the problem and solution (conceptual).
• Appropriate level of abstraction (conceptual).
• Correct use of notation, e.g., actors, requirements blocks (structural).

It is important to mention that the models’ assessment criteria contain two parts:
– Structural – SysML language related aspects: this part assesses the understanding and usage of the modelling formalism.
– Conceptual – architecture related aspects: this part assesses the conceptual value of your model and requires careful analysis and research into available and proposed technologies.

You are fundamentally assessed on the conceptual – architecture modelling of smart systems and a very small part on the technicalities of the modelling language. The use of SysML modelling language is to enable a practical approach that will enhance your future employability skills.

The marks for the diagrams are as follows:
• (x2) SysML Requirements Diagrams (20 marks)

(Total marks for Part 1: 20 marks)

Part 2: Design and propose a system solution for this Smart systems fall detector

Propose a technological solution to the context-awareness scenario that you have chosen in Part1 by:
• Researching existing assistive technologies from the viewpoint of context-awareness (30 marks)
• Designing, creating and explaining two (x2) SysML block diagrams for structure (10 marks)
• Designing, creating and explaining one (x1) SysML Sequence diagram for behaviour (10 marks)
• Designing, creating and explaining one (x1) SysML Activity diagram for behaviour (10 marks)
• Smart element identification: you need to identify parts of the system from all diagrams (block, sequence and activity) that make it smart. (10 marks)

Note that you don’t have to implement your proposed system. You need to perform appropriate research and justify your proposal with references and corresponding documentation.

An appropriate and well-justified proposed architecture solution should be modelled using both structural and behavioural diagrams. Ideas could be drawn from similar systems and solutions that you will explore through research (first bullet point of Part2 – Researching existing assistive technologies). Even if your proposed solution is a completely new idea of your own, you still need to do research and compare it with existing solutions.

It is important not to overlook the smart element in your system design. In this case study as in other similar systems, data are collected and processed at several points offering numerous opportunities for automating parts of the system, adding intelligence by using AI algorithms, etc. Note also that you are not expected to implement automation and AI algorithms but to describe where they would be used in the smart system.

The marking criteria for the Requirements modelling requested above also apply to the SysML diagrams of Part2. The viewpoint of context-awareness is very important to be followed in all parts of the assignment (Part1, Part2).

Your diagrams can be created using any online editing software such as drawio, visio, etc.

Upload a zip file with all your diagrams (10 marks).

Also note that the research for existing assistive technologies should not exceed 900 words excluding references and diagrams.

(Total marks for Part 2: 80 marks)

CASE STUDY – Person-Centred Health Management – Smart Homes
At some time in the future, a person will be surrounded by virtual, real-time, around-the-clock health and medical assistance through various wearable, mobile, and implanted sensor devices. All these are partially provided in care homes and will be eventually provided from the comfort of their own home environment. These devices will be connected to an intelligent software virtual agent (Personal Health Application) that is designed to support optimum health and acute/chronic treatment and will probably be implemented on some mobile constantly connected device. This mobile device contains a summary of the person’s medical records, containing e.g. current treatment, chronic diseases, allergies, current medication, which is easily accessible in emergency situations and can easily connect to: in-body, on-body, stationary and environmental sensors giving an up-to-date status of health and potential risks based on physiological processes, biological processes and environmental situation within and surrounding the person; medical databases with historical patient information as well as current diseases and treatments, which include genetic profiles, clinical information; non-medical databases with current as well as historical information about e.g. level of activity, performance information from fitness equipment and eating habits; analysis services, which use patient information and information from certified medical knowledge from the different databases to give personalized advice.

The application empowers the person with the relevant knowledge and with online support allowing him or her to take more responsibility for their own health. Their full state of health (including historical information) consisting of genetic, biological, physiological and environmental information as well as the information stored at systems from professional care givers will be available and combined with access to the relevant medical knowledge, personalised advice will be given for self-treatment or referral to proper professional support with the adequate relevant information at hand, using decision support tools based on an ongoing analysis and synthesis of medical evidence. An important part of self-management is related to the prevention of diseases which can be based on the genetic and molecular warning signs before a disease exposes itself and also on the data collected by non-medical services such as activity management, fitness equipment, eating habits, supporting a person in keeping a healthy lifestyle. Monitoring medication intake and e.g. exercise programs allows checks of adherence to treatment (and react when this is not so), combine with monitoring their status, which provides indications on whether the treatment needs to be adapted.

The application also acts a virtual nurse-doctor who knows the person’s status and needs and is on call at any time and in any place, to guide and support the person. This application acts as a knowledge source, a personal decision-support system, health and fitness coach, personal dietician, and much more, giving instantaneous feedback to the user, raising an alarm or informing professional or informal care givers when needed. This is important for managing people suffering from e.g. chronic diseases, detecting relapses, before they become dangerous, based on monitoring, trend analysis, and raising the alarm and initiating appropriate action like calling a person, or visiting when needed. This will also include the possibility for action related to behaviour management by giving relevant education information and checking adherence to treatment programs (medication or exercise).

If a real emergency happens, it will be detected by the application automatically: it informs the emergency service of all the relevant medical data and the exact location of the patient because one of the environmental sensors is of course a GPS sensor. Knowing that this will be done when necessary also increases the self-confidence of the patients.

The application also communicates with the person’s network of medical professionals who are involved in current treatment plans and link the person to diagnostic and treatment services. All care providers and their supporting facilities like radiology, laboratories and pharmacies use electronic health-record systems that are connected to a secure health-information-exchange network which enables easy access to the relevant data using a role- and task-based access-control system that is inline with the consent rules controlled by the patient. In this way, they all have constant access to up-to-date patient information, which is of course important in emergencies.

The location for a person that uses this health management system is also very important. The reason behind these systems is to enable independent living and provide assistance outside hospitals and from the comfort of one’s home environment.

A good health management system will be able to adjust according to the context that the user is into and provide adaptive services.

A key feature of smart homes is adaption to the environment. In order to do so, the system needs to
(1) understand behaviour of inhabitants
(2) adapt its functionality to the current situation
This ability is known as context awareness of the system.

You are required to create your own scenario of context-awareness requirements and proposed solution and present it through diagrammatic forms.

SUBMISSION FORMAT for Smart systems fall detector
You can submit all your work in one or multiple files which should be in pdf format to enable readability. The submission will be only online through Brightspace assignments.

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