Thing Theory

As healthcare professionals and others embrace the Internet of Things (IoT) and smart environment paradigms, developers will bear the brunt of constructing the IT relationships within these, making sense of the big data produced as a result, and managing the relationships between people and technologies. This chapter explores how PolySocial Reality (PoSR), a framework for representing how people, devices and communication technologies interact, can be applied to developing use cases combining IoT and smart environment paradigms, giving special consideration to the nature of location-aware messaging from sensors and the resultant data collection in a healthcare environment. Based on this discussion, the authors suggest ways to enable more robust intra-sensor messaging through leveraging social awareness by software agents applied in carefully considered healthcare contexts.

The Internet of Things and Assistive Technologies for People with Disabilities

With the Americans with Disabilities Act (ADA), the past two decades have seen a proliferation of Assistive Technology (AT) and its enabling impact on the lives of people with disabilities in the areas of accessing information, communication, and daily living activities. Due to recent emergence of the Internet of Things (IoT), the fields of rehabilitation, healthcare, and education are challenged to incorporate the IoT applications into current AT services. While IoT applications continue to be developed and integrated into AT, they are still at a primitive stage where clear guidelines are yet to be developed and benefits are yet to be substantiated to ensure the quality of lives of people with disabilities. This chapter provides an overview of the IoT and AT integrated applications based on the building blocks of the IoT, along with recent trends and issues relevant to accessing technology for people with disabilities.

Hybrid Integration Technology for Wearable Sensor Systems

Personalized and pervasive healthcare devices help seamlessly integrate healthcare and wellness into the daily life, independent of time and space. Silicon Integrated Circuit (IC) has been used in many advanced healthcare applications due to the compact size and ultra-low power consumption. Meanwhile, printed electronics (PE) is considered as a promising approach enabling cost-effective manufacturing of thin, flexible, and light-weight devices. A hybrid integration of IC and PE provides a new solution for the future wearable healthcare devices. In this chapter, firstly a customized bio-sensing IC is demonstrated, which can detect and process various bio-signals; secondly, the feasibility and performance of using inkjet printing technology as enabling technology has been examined for the fabrication of flexible bio-sensing devices. Finally, a wearable and flexible Bio-Patch is presented by leveraging hybrid integration of PE and bio-sensing IC. In-vivo test results show that the flexible Bio-Patch provides high quality ECG signal comparable with the one gained by bedside ECG machine.

Reliability of IoT-Aware BPMN Healthcare Processes

BPMN (Business Process Model and Notation) has become the de-facto business process modelling language standard. Healthcare processes have been increasingly incorporating participants other than humans, including Internet of Things (IoT) physical devices such as biomedical sensors or patient electronic tags. Due to its critical requirements, IoT-aware healthcare processes justify the relevance of Quality of Services aspects, such as reliability, availability, and cost, among others. This chapter focuses on reliability and proposes to use the Stochastic Workflow Reduction (SWR) method to calculate the reliability of IoT-aware BPMN healthcare processes. In addition, the chapter proposes a BPMN language extension to provide processes with reliability information. This way, at design time, modellers can analyse alternatives and, at run time, reliability information can be used to select participants, execute services, or monitor process executions. The proposal is applied to an Ambient Assisted Living system use case, a rich example of an IoT-aware healthcare process.

The Role of Time in Health IoT

As the biological processes in the body change constantly, comparable measurements should be taken simultaneously in time and place. In practice, this is hard to achieve. Synchronicity is required to certify medical accuracy for a new device by reference to a certified one. In a typical health IoT, synchronicity cannot be enforced procedurally and timing needs to be part of the network architecture. Popular examples are in blood pressure measurement. Putting the blood flow in a known pinch-off situation performs synchronization. But this principle cannot be extended to other non-invasive measurements. Hence the chapter proposes to synchronize on basis of the heart rate extracted from the blood flow at arbitrary positions on the body. This models the blood flow in the body and relates all to the rhythm of the heart. It brings existing phenomena into a single, multi-level model that allows wireless networked wearables into a single health-monitoring scheme.

Background on Context-Aware Computing Systems

This chapter is consecrated to provide background information that encompass the basic concepts of context-aware pervasive computing systems. The major challenges that researchers need to consider when conducting research in context-aware pervasive computing systems and the most interesting approaches that can be used in order to deal with these challenges are reviewed. This chapter describes also the basic design principles of context-aware pervasive systems and depicts different models for representing and reasoning upon contextual information and an overview of the most known development frameworks of context-aware systems and application adaptation is presented too. Moreover, this chapter describes the usefulness of using context-awareness in ubiquitous healthcare domain and the major challenges in using context-awareness in this domain. The well-known works that have been proposed in the field of Ubiquitous healthcare are discussed too.

Social Internet of Things in Healthcare

This chapter presents a future vision for healthcare, which will involve smart devices, Internet of Things, and social networks, that make this vision a reality. The authors present the necessary background by introducing the Social Internet of Things paradigm. Agent technology seems to be a promising approach in the adoption of the Social Internet of Things in collaborative environments with increased autonomy and agility, like healthcare is. Also, it is examined challenges to the adoption of the Social Internet of Things in healthcare in order to facilitate new applications and services in more effective and efficient ways.

Citizen Science, Air Quality, and the Internet of Things

This chapter discusses the emergence of the Internet of Things, using a case study of a citizen science initiative, focusing in particular on issues involved in measuring air quality. The core of the citizen science initiative was formed by a world-wide network of early adaptors of the Internet of Things who, motivated by public health issues, set out to create widely available tools for air quality measuring. With these tools, they established a global, citizen-led, air quality measurement network. Besides highlighting a number of social and technological issues which are involve any such enterprise, this chapter engages with the discourse surrounding the use of IoT in collective sensing projects. Two questions are salient here. Firstly, can IoT technology be used in a citizen science context to monitor air quality? And secondly, does the construction of these devices lead to a successful mobilisation around issues of air quality?

Preventing Health Risks Caused by Unhealthy Air Quality Using a CEP-Based SOA 2.0

Air quality has been a recurrent issue in recent years since it can seriously impact citizens' health and their life quality. Nowadays, the different ways to provide end users with air quality information do not provide real-time data and lack accessibility. Besides, they do not automatically adapt to the particular circumstances of each citizen. In this chapter, an event-driven service-oriented architecture is proposed for detecting air quality changes in real time as well as making this information available to end users in a user-friendly way, notifying them with customized alerts upon detecting any potentially hazardous level for their health, thereby helping to prevent health risks.

IoT for Ambient Assisted Living

Research activities on healthcare support systems mainly focus on people in their own homes or nurses and doctors in hospitals. A limited amount of research aims at supporting caregivers that work with people with disabilities in assisted living facilities (ALFs). This chapter explores and applies the Internet of Things to the ALF context. In particular, it presents the design, the implementation, and the experimental evaluation of Care4Me, a system supporting the daily activities of assistants. The requirements for designing and implementing Care4Me derive from a literature analysis and from a user study. The solution combines wearable and mobile technologies. With this healthcare support system, caregivers can be automatically alerted of potentially hazardous situations. Furthermore, inhabitants can require assistance instantly and from any point of the facility. The system was evaluated in two ways. The authors performed a functional test with a group of professional caregivers, and deployed the system in an ALF in Italy, collecting the opinions of caregivers and inhabitants.