AN IN-HOUSE AUTOMATIC OBSERVER SYSTEM IN AUTOMOBILES

The created in-vehicle device works using GPS module and Global system for mobile communication / General Packet Radio Service (GSM/GPRS) technology that is one   the most common ways for vehicle monitoring. The suggested system made good use of a typical technology that mixes a Smart phone application obtaining ARM processor. This will be easy to make and inexpensive in comparison to other people. A dependable vehicle monitoring technique is designed and implemented for monitoring the movement connected getting equipped vehicle within the location anytime. Being used a part of the vehicle whose position is made the decision and supervised in solid-time. The vehicle monitoring system uses the GPS module to get geographic coordinates at regular time intervals. The GSM/GPRS module is used to transmit and update the vehicle location to a database. A Smartphone application is also developed for continuously monitoring the vehicle location. The Google Maps API is used to display the vehicle on the map in the Smartphone application

Automatic Detection of User Abilities through the SmartAbility Framework

This paper presents a proposed smartphone application for the unique SmartAbility Framework that supports interaction with technology for people with reduced physical ability, through focusing on the actions that they can perform independently. The Framework is a culmination of knowledge obtained through previously conducted technology feasibility trials and controlled usability evaluations involving the user community. The Framework is an example of ability-based design that focuses on the abilities of users instead of their disabilities. The paper includes a summary of Versions 1 and 2 of the Framework, including the results of a two-phased validation approach, conducted at the UK Mobility Roadshow and via a focus group of domain experts. A holistic model developed by adapting the House of Quality (HoQ) matrix of the Quality Function Deployment (QFD) approach is also described. A systematic literature review of sensor technologies built into smart devices establishes the capabilities of sensors in the Android and iOS operating systems. The review defines a set of inclusion and exclusion criteria, as well as search terms used to elicit literature from online repositories. The key contribution is the mapping of ability-based sensor technologies onto the Framework, to enable the future implementation of a smartphone application. Through the exploitation of the SmartAbility application, the Framework will increase technology amongst people with reduced physical ability and provide a promotional tool for assistive technology manufacturers

Comparison and Characterization of Android-Based Fall Detection Systems

Falls are a foremost source of injuries and hospitalization for seniors. The adoption of automatic fall detection mechanisms can noticeably reduce the response time of the medical staff or caregivers when a fall takes place. Smartphones are being increasingly proposed as wearable, cost-effective and not-intrusive systems for fall detection. The exploitation of smartphones’ potential (and in particular, the Android Operating System) can benefit from the wide implantation, the growing computational capabilities and the diversity of communication interfaces and embedded sensors of these personal devices. After revising the state-of-the-art on this matter, this study develops an experimental testbed to assess the performance of different fall detection algorithms that ground their decisions on the analysis of the inertial data registered by the accelerometer of the smartphone. Results obtained in a real testbed with diverse individuals indicate that the accuracy of the accelerometry-based techniques to identify the falls depends strongly on the fall pattern. The performed tests also show the difficulty to set detection acceleration thresholds that allow achieving a good trade-off between false negatives (falls that remain unnoticed) and false positives (conventional movements that are erroneously classified as falls). In any case, the study of the evolution of the battery drain reveals that the extra power consumption introduced by the Android monitoring applications cannot be neglected when evaluating the autonomy and even the viability of fall detection systems.Ministerio de Economía y Competitividad TEC2009-13763-C02-0

Activity recognition based on thermopile imaging array sensors

With aging population, the importance of caring for elderly people is getting more and more attention. In this paper, a low resolution thermopile array sensor is used to develop an activity recognition system for elderly people. The sensor is composed of a 32x32 thermopile array with the corresponding 33° × 33° field of view. The outputs of the sensor are sequential images in which each pixel contains a temperature value. According to the thermopile images, the activity recognition system first determines whether the target is within the tracking area; if the target is within the tracking area, the location of the target will be detected and three kinds of activities will be identified. Keywords- Activity Recognition, Raspberry Pi, Thermopile, Imaging Processing

Analysis of Android Device-Based Solutions for Fall Detection

Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions.Ministerio de Economía y Competitividad TEC2013-42711-

Development of tools for the use of Android cell-phones to recognize user activities

Using Android cell-phones, and consequently, having access to the input provided by the GPS receiver and the WI-FI receiver as well, the project will require to develop the necessary software and associated algorithms in order to deduce the user's activities in terms of the location of the user (indoors or outdoors) and those activities derived from detecting if the user is standing still, walking, running, driving a car, riding a bicycle, etc.The goal of this study is developing the fundamental techniques to define activity of the users like walking, running, standing or cycling while the user is using two different type of Network connectivity, GPRS or Wi-Fi by calculating the distance of the user in a period of time by the longitude and latitude of the user´s location which has reached in the location recognizing. Therefore, the main goal of the study to retrieve user’s activity is achieved by requesting location of user for each period of time, from current and previous location of user

Technology-assisted healthcare: exploring the use of mobile 3D visualisation technology to augment home-based fall prevention assessments

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonFalls often cause devastating injuries which precipitate hospital and long-term care admission and result in an increased burden on health care services. Fall prevention interventions are used to overcome fall risk factors in an ageing population. There is an increasing need for technology-assisted interventions to reduce health care costs, whilst also lessening the burden that an ageing population increasingly has on health care services. Research efforts have been spent on reducing intrinsic fall risk factors (i.e. functional ability deficits and balance impairments) in the older adult population through the use of technology-assisted interventions, but relatively little effort has been expended on extrinsic risk factors (i.e. unsuitable environmental conditions and lack of assistive equipment use), considering the drive for healthcare outside of the clinical setting into the patients’ home. In the field of occupational therapy, the extrinsic fall-risk assessment process (EFAP) is a prominent preventive intervention used to promote independent living and alleviate fall risk factors via the provision of assistive equipment prescribed for use by patients in their home environment. Currently, paper-based forms with measurement guidance presented in the form of 2D diagrams are used in the EFAP. These indicate the precise points and dimensions on a furniture item that must be measured as part of an assessment for equipment. However, this process involves challenges, such as inappropriate equipment prescribed due to inaccurate measurements being taken and recorded from the misinterpretation of the measurement guidance. This is largely due to the poor visual representation of guidance that is provided by existing paper-based forms, resulting in high levels of equipment abandonment by patients. Consequently, there is a need to overcome the challenges mentioned above by augmenting the limitations of the paper-based approach to visualise measurement guidance for equipment. To this end, this thesis proposes the use of 3D visualisation technology in the form of a novel mobile 3D application (Guidetomeasure) to visualise guidance in a well-perceived manner and support stakeholders with equipment prescriptions. To ensure that the artefact is a viable improvement over its 2D predecessor, it was designed, developed and empirically evaluated with patients and clinicians alike through conducting five user-centred design and experimental studies. A mixed-method analysis was undertaken to establish the design, effectiveness, efficiency and usability of the proposed artefact, compared with conventional approaches used for data collection and equipment prescription. The research findings show that both patients and clinicians suggest that 3D visualisation is a promising development of an alternative tool that contains functionality to overcome existing issues faced in the EFAP. Overall, this research makes a conceptual contribution (secondary) to the research domain and a software artefact (primary) that significantly improves practice, resulting in implications and recommendations for the wider healthcare provision (primary).The Engineering and Physical Sciences Research Council (EPSRC)