SocIoTal - The development and architecture of a social IoT framework

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.This work was supported by the SocIoTal project under grant agreement No 609112

Opportunistic sensing platforms to interpret human behaviour.

Understanding human behaviour in an automatic but also non-intrusive manner, constitutes an important and emerging area for various fields. This requires collaboration of information technology with humanitarian sciences in order to transfer existing knowl- edge of human behaviour into self-acting tools to eliminate the human error. This work strives to shed some light in the area of Mobile Social Signal Processing by trying to understand if today’s mobile devices, given their advanced sensing and computational capabilities, are able to extract various aspects of human behaviour. Although one of the core aspects of human behaviour are social interactions, current tools do not pro- vide an accurate, reliable and real-time solution for social interaction detection, which constitutes a significant barrier in automatic human behaviour understanding. Towards filling the aforementioned gap in order to enable human behaviour under- standing through mobile devices, particular contributions were made. Firstly, an interpersonal distance estimation technique is developed based upon a non-intrusive opportunistic mechanism that solely relies on sensors and communication capabilities of off-the-shelf smartphones. Secondly, based on user’s interpersonal distance and relative orientation, a pervasive and opportunistic approach based on off-the-shelf smartphones for social interaction detection system is presented. Leveraging information provided by psychology, analytical and error models are proposed to estimate the probability of people having social interactions. Then, to showcase the ability of mobile devices to infer human behaviour, a trust relationship quantification mechanism is developed based on users’ behavioural traits and psychological models. Finally, a prediction and compensation mechanism for the device displacement error that leverages human loco- motion patterns to refine the device orientation is introduced. The above contributions were evaluated through experimentation and hard data collected from real-world environments to prove their accuracy and reliability as well as showing the applicability of the proposed approaches in daily situations. This work showed that mobile devices are able to accurately detect social interactions and further social and trust relationships among people, despite the noise induced in real-world situations. Close collaboration between informatics and social sciences is imperative, to overcome the significant barrier in the development of human behaviour understanding. This work could constitute a fundamental building block, as the computational power and battery autonomy of mobile devices increases, for the development of novel techniques towards understanding human behaviour, by including multiple behavioural traits and enabling the creation of socially-aware information systems

Reducing Unintentional Injuries in under Fives: Development and Testing of a Mobile Phone App

Background: Unintentional injuries are a leading cause of preventable death and a major cause of ill health and disability in children under five years of age. A health promotion mobile phone application, ‘Grow up Safely’, 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, 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 ‘Grow Up Safely’ 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 organisation. Further development is planned with push‐out notifications and wider feasibility testing to engage targeted groups, such as young mothers, fathers and other carers.</p