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Background: Unintentional injuries are a leading cause of preventable death and a major cause of ill health and disability in children under 5 years of age. A health promotion mobile phone application, "Grow up Safely" (GUS), was developed to support parents and carers in reducing unintentional injuries in this population of children. Methods:A prototype of the mobile application was developed to deliver health education on unintentional injury prevention linked to stages of child development. In order to explore the usability of the app and refine its content, three focus groups were conducted with 15 mothers. Data were analysed using thematic analysis. Results:The majority of participants reported previous use of health apps, mainly related to pregnancy and recommended by health professionals. The app was considered user-friendly and easy to navigate. Participants in two focus groups found the app informative and offered new information, and they would consider using it. Participants in the "young mum's" group considered the advice to be "common sense" but found the language too complex. All participants commented that further development of push-out notifications and endorsement by a reputable source would increase their engagement with the app. Conclusion:The GUS mobile phone app, aimed at reducing unintentional injuries in children under five, was supported by mothers as a health promotion app. They would consider downloading it, particularly if recommended by a health professional or endorsed by a reputable organization. Further development is planned with pushout notifications and wider feasibility testing to engage targeted groups, such as young mothers, fathers, and other carers. K E Y W O R D Saccidents, app development, health education, health promotion, injuries, parents, prevention, under fives

Understanding human behaviour in an automatic but non-intrusive manner is an important area for various applications. This requires the collaboration of information technology with human sciences to transfer existing knowledge of human behaviour into self-acting tools. These tools will reduce human error that is introduced by current obtrusive methods such as questionnaires. To achieve unobtrusiveness, we focus on exploiting the pervasive and ubiquitous character of mobile devices.In this article, a survey of existing techniques for extracting social behaviour through mobile devices is provided. Initially we expose the terminology used in the area and introduce a concrete architecture for social signal processing applications on mobile phones, constituted by sensing, social interaction detection, behavioural cues extraction, social signal inference and social behaviour understanding. Furthermore, we present state-of-the-art techniques applied to each stage of the process. Finally, potential applications are shown while arguing about the main challenges of the area.

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In this paper the development and architecture of the SocIoTal platform is presented. SocIoTal is a European FP7 project which aims to create a socially-aware citizen-centric Internet of Things infrastructure. The aim of the project is to put trust, user-control and transparency at the heart of the system in order to gain the confidence of everyday users and developers. By providing adequate tools and mechanisms that simplify complexity and lower the barriers of entry, it will encourage citizen participation in the Internet of Things. This adds a novel and rich dimension to the emerging IoT ecosystem, providing a wealth of opportunities for the creation of new services and applications. These services and applications will be able to address the needs of society therefore improving the quality of life in cities and communities.In addition to technological innovation, the SocIoTal project sought to innovate the way in which users and developers interact and shape the direction of the project. The project worked on new formats in obtaining data, information and knowledge. The first step consisted of gaining input, feedback and information on IoT as a reality in business. This led to a validated iterative methodology which formed part of the SocIoTal toolkit and a best practices guide for local policy makers and cities.