Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

ADHD Remote Technology study of cardiometabolic risk factors and medication adherence (ART-CARMA): a multi-centre prospective cohort study protocol

Attention deficit hyperactivity disorder; Digital phenotyping; Remote monitoringTrastorno por déficit de atención con hiperactividad; Fenotipado digital; Monitoreo remotoTranstorn per dèficit d'atenció amb hiperactivitat; Fenotipat digital; Monitorització remotaBackground Emerging evidence points at substantial comorbidity between adult attention deficit hyperactivity disorder (ADHD) and cardiometabolic diseases, but our understanding of the comorbidity and how to manage cardiometabolic disease in adults with ADHD is limited. The ADHD Remote Technology study of cardiometabolic risk factors and medication adherence (ART-CARMA) project uses remote measurement technology to obtain real-world data from daily life to assess the extent to which ADHD medication treatment and physical activity, individually and jointly, may influence cardiometabolic risks in adults with ADHD. Our second main aim is to obtain valuable real-world data on adherence to pharmacological treatment and its predictors and correlates during daily life from adults with ADHD. Methods ART-CARMA is a multi-site prospective cohort study within the EU-funded collaboration ‘TIMESPAN’ (Management of chronic cardiometabolic disease and treatment discontinuity in adult ADHD patients) that will recruit 300 adults from adult ADHD waiting lists. The participants will be monitored remotely over a period of 12 months that starts from pre-treatment initiation. Passive monitoring, which involves the participants wearing a wrist-worn device (EmbracePlus) and downloading the RADAR-base Passive App and the Empatica Care App on their smartphone, provides ongoing data collection on a wide range of variables, such as physical activity, sleep, pulse rate (PR) and pulse rate variability (PRV), systolic peaks, electrodermal activity (EDA), oxygen saturation (SpO2), peripheral temperature, smartphone usage including social connectivity, and the environment (e.g. ambient noise, light levels, relative location). By combining data across these variables measured, processes such as physical activity, sleep, autonomic arousal, and indicators of cardiovascular health can be captured. Active remote monitoring involves the participant completing tasks using a smartphone app (such as completing clinical questionnaires or speech tasks), measuring their blood pressure and weight, or using a PC/laptop (cognitive tasks). The ART system is built on the RADAR-base mobile-health platform. Discussion The long-term goal is to use these data to improve the management of cardiometabolic disease in adults with ADHD, and to improve ADHD medication treatment adherence and the personalisation of treatment.The ART-CARMA study has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 965381. This communication reflects the views of the authors, and the European Commission is not responsible for any use that may be made of the information it contains. HD is supported by the UK Medical Research Council (MR/N013700/1) and King’s College London member of the MRC Doctoral Training Partnership in Biomedical Sciences

Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey

The integration of things’ data on the Web and Web linking for things’ description and discovery is leading the way towards smart Cyber–Physical Systems (CPS). The data generated in CPS represents observations gathered by sensor devices about the ambient environment that can be manipulated by computational processes of the cyber world. Alongside this, the growing use of social networks offers near real-time citizen sensing capabilities as a complementary information source. The resulting Cyber–Physical–Social System (CPSS) can help to understand the real world and provide proactive services to users. The nature of CPSS data brings new requirements and challenges to different stages of data manipulation, including identification of data sources, processing and fusion of different types and scales of data. To gain an understanding of the existing methods and techniques which can be useful for a data-oriented CPSS implementation, this paper presents a survey of the existing research and commercial solutions. We define a conceptual framework for a data-oriented CPSS and detail the various solutions for building human–machine intelligence

Merging current health care trends: Innovative perspective in aging care

Current trends in health care delivery and management such as predictive and personalized health care incorporating information and communication technologies, home-based care, health prevention and promotion through patients’ empowerment, care coordination, community health networks and governance represent exciting possibilities to dramatically improve health care. However, as a whole, current health care trends involve a fragmented and scattered array of practices and uncoordinated pilot projects. The present paper describes an innovative and integrated model incorporating and “assembling” best practices and projects of new innovations into an overarching health care system that can effectively address the multidimensional health care challenges related to aging patient especially with chronic health issues. The main goal of the proposed model is to address the emerging health care challenges of an aging population and stimulate improved cost-efficiency, effectiveness, and patients’ well-being. The proposed home-based and community-centered Integrated Healthcare Management System may facilitate reaching the persons in their natural context, improving early detection, and preventing illnesses. The system allows simplifying the health care institutional structures through interorganizational coordination, increasing inclusiveness and extensiveness of health care delivery. As a consequence of such coordination and integration, future merging efforts of current health care approaches may provide feasible solutions that result in improved cost-efficiency of health care services and simultaneously increase the quality of life, in particular, by switching the center of gravity of health delivery to a close relationship of individuals in their communities, making best use of their personal and social resources, especially effective in health delivery for aging persons with complex chronic illnesse

Multi-Dimensional-Personalization in mobile contexts

During the dot com era the word "personalisation” was a hot buzzword. With the fall of the dot com companies the topic has lost momentum. As the killer application for UMTS or the mobile internet has yet to be identified, the concept of Multi-Dimensional-Personalisation (MDP) could be a candidate. Using this approach, a recommendation of mobile advertisement or marketing (i.e., recommendations or notifications), online content, as well as offline events, can be offered to the user based on their known interests and current location. Instead of having to request or pull this information, the new service concept would proactively provide the information and services – with the consequence that the right information or service could therefore be offered at the right place, at the right time. The growing availability of "Location-based Services“ for mobile phones is a new target for the use of personalisation. "Location-based Services“ are information, for example, about restaurants, hotels or shopping malls with offers which are in close range / short distance to the user. The lack of acceptance for such services in the past is based on the fact that early implementations required the user to pull the information from the service provider. A more promising approach is to actively push information to the user. This information must be from interest to the user and has to reach the user at the right time and at the right place. This raises new requirements on personalisation which will go far beyond present requirements. It will reach out from personalisation based only on the interest of the user. Besides the interest, the enhanced personalisation has to cover the location and movement patterns, the usage and the past, present and future schedule of the user. This new personalisation paradigm has to protect the user’s privacy so that an approach supporting anonymous recommendations through an extended "Chinese Wall“ will be described

Towards Smart and Sustainable Multimodal Public Transports Based on a Participatory Ecosystem

International audienceLeveraging on the recent availability of open data about public transports, the last generation of smartphone applications provide highly personalised guidance to passengers during their trips. This smart assistance definitely improves the passenger comfort and streamlines their trips, especially in case of infrastructure incidents and/or multimodal trips. However, there are important limitations stemming from the unidirectional flow of information going from transport operators to passengers: (1) waste of computing resources, partially defeating the purpose of sustainability, and (2) missed opportunities of optimisations by the transport operators, which do not exploit detailed real-time passengers information. This paper presents ongoing work towards smarter and more sustainable multimodal transports based on a full-duplex ecosystem in which passengers and transport operators actively exchange information and react correspondingly. As first steps in this direction, we show how this integration can lead to greener computing applications by varying the balance between the smartphone and the cloud, and present a few concrete optimisations enabled in this model, during the trip itself or on a longer term by improving the transport infrastructure. We illustrate this ecosystem with a smartphone/cloud application prototype, and elaborate the remaining challenges for fully implementing this vision, including issues like interoperability, scalability, and acceptability