This individual assignment forms the first part of the coursework for this unit, and covers (or partially fulfils) learning outcomes, 1, 3, 4 and 5.
Deliverables and Assessment Criteria / Marking Scheme
You have been given a brief description of a particular application domain (Internet of Things application for fall-detection for the elderly), and have been asked to produce a number of deliverables, for the final requirements document.
Requirements identification and modelling
Produce Volere templates, Use Cases with diagrams and SysML Requirements diagrams for the given scenario(s).
The models will be marked against the following criteria:
Additional Note for breakdown of marks for diagrams:
Reflections on the tools for Requirements modelling
Discuss and evaluate critically each of the two requirements modelling tools (Use Cases and SysML Requirements diagrams) used by presenting the advantages/disadvantages of each one. Compare and contrast them in general and as regards to their suitability for our case study. (20 marks)
(Maximum 500 words for reflections on requirements modelling tools)
Design and propose an IoT solution for this case study Propose a technological solution to the case study by:
Note that you don’t have to implement your proposed system or prove its correctness and suitability. You need to perform appropriate research and justify your proposal with references and corresponding documentation.
The marking criteria for the Requirements modelling requested above also apply for the SysML block diagram model.
Note: This Case Study was set in collaboration with Technological Educational Institute of Western
Greece (TWG), and more specifically with the Embedded System Design and Application Laboratory (ESDA lab) of the Computer Engineering and Informatics Department. The TWG/ESDA Lab has expertise in research & development in IoT applications and assisted living systems.
It has been identified that fall detection for the elderly is a major issue. Falls represent a significant threat for the elderly over the age of 65 and the problem is getting worse as the elderly might have to be alone in their homes, care homes or outdoors for a significant period of time.
Age Concern owns a group of care homes in Britain with hundreds of elderly people resident. They experience 60% of their residents’ deaths due to falls. Recently, there has been a change of management with new strategic directions and one of the improvements has been the funding of an automatic fall detection system.
Generally, all the residents in Age Concern, have several medical problems and all the related information needs to be kept using electronic means so that patients, their relatives and the Age Concern personnel (doctors, nurses, carers) can access/update and consistently maintain information that is related to each resident. Security and privacy issues should be maintained for medical data and each user of the system should have different priviledges in using the stored information. For example, relatives shouldn’t be able to alter the information and shouldn’t be able to read all the information stored. The data should be handled according to the relevant UK data protection act and ethics rules and considerations for medical information (note: the student is expected to extract the corresponding requirements through online research of the corresponding regulations).
Elderly people that spend time alone represent a large target group for such systems. In case a person tumbles and nobody is around to help, an independent fault detection and alarming system could automatically call for help by activating an emergency response infrastructure even if the person is unable to trigger an alarm by themselves. Also, the person should be able to trigger the alarm themselves bypassing the automatic fall detection system.
Two different types of fall detection systems have been identified: an indoor fall detection system as well as an outdoor one (garden, roads). Age Concern was initially interested only in the indoor fall detection system. However, the outdoor and mainly “out of range” fall detection is a new requirement for them that should be taken into account. For example, when the residents are in the garden, mobile technology could assist with triggering the alarm in case of fall detection.
The resulting system should be able to address the normal usage behaviour of elderly people that have been observed through discussions with health care professionals: Normal usage: The desired use case is when a person is wearing an emergency wireless transmitter like a wristwatch, a necklace or a pendant permanently during the whole daytime. There are other types of elderly behaviour that have been observed such as the non-usage (the device is stored away from the owners) or the refused-usage (even if a fall occurs and the person is reluctant to call for help). The device will address only the normal usage.
There is a requirement to continuously monitor information regarding the location and the movement of the elderly person that would lead to the immediate detection of abnormal movement in real time.
The fall detection system will perform real-time and transparent evaluation of the movement situation of the person and will make decisions through related algorithms regarding the type of alarm that will be created. For example, the following alarms could be created:
The medical professionals (nurses, carers) should have access to the system for observing the level and recharging the batteries of the fall detection system.
Also, the elderly person should be able to have a choice of communicating directly with corresponding carers, nurses, relatives in addition to the automatic alarms.
In the case of a false automatic alarm, the elderly person should be able to designate that the alarm was false through an appropriately designed interface.
Last but not least, a major requirement for the future would be that to add an intelligent software agent that would be able to make decisions at the fall detection device and at the information storage level.
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