Living lab approach for developing massmarket IoT products and services

Internet of Things (IoT) has emerged as a central concept in both the industrial as in the academic world. In this context, Living Lab research has been shown as an effective means for the design, implementation, development, testing and validation of Internet of Things system’s pervasiveness. However, IoT products are not yet designed based on the needs of a larger, non-technical group of end-users. Therefore, in this paper we describe the AllThingsTalk Living Lab research track in which tangible end-user products are defined to be implemented on an online IoT platform. More specifically, by using both qualitative and quantitative methodologies (i.e., desk research, online survey, probe research and co-creation) and by selecting different types of users (i.e., based on Rogers’ adoption profiles) for these interaction moments, we were able to combine the input of these users to define tangible products that meet the needs of a heterogeneous group of end-users

Innovation is created by humans, not by systems: an exploration of user involvement in living labs: user motivation versus lead user criteria

The past few years companies have become more interested in involving users during the production process of their products. On the other hand, a group of users started to innovate on their own. Users also became interested in becoming part of the production processes themselves. Certain users experience certain needs earlier than others and they enjoy finding solutions for these needs. They are called Lead Users (von Hippel, 2005). Living Labs are one possibility for users to realize this interest to innovate. iLab.o, the Living Lab division of iMinds, has been organizing Living Lab research since 2009. To get a better view on the motivations of this panel, we analyzed the behavior of the involved users from September 2009 to December 2013. We tried to detect Lead Users, but it is not obvious to define people as Lead Users because of the different used definitions. Instead, we divided this panel into three types of users based on the intensity of their involvement: passive, sleeping and active users. A small group of users is extremely active and are been defined as “alpha users”. Based on interviews with these alpha users in November and December 2013, a better view on their motivations to keep participating in Living Lab research was made. In this paper we focus on the participation of these different user types in one research phase type within Living Lab research, more specifically co-creation sessions. By means of a comparative case study, we tried to get a better understanding of the behavior of the different user types. It became clear that in order to keep the panel involved it is important to focus on community building

Wireless and Physical Security via Embedded Sensor Networks

Wireless Intrusion Detection Systems (WIDS) monitor 802.11 wireless frames (Layer-2) in an attempt to detect misuse. What distinguishes a WIDS from a traditional Network IDS is the ability to utilize the broadcast nature of the medium to reconstruct the physical location of the offending party, as opposed to its possibly spoofed (MAC addresses) identity in cyber space. Traditional Wireless Network Security Systems are still heavily anchored in the digital plane of "cyber space" and hence cannot be used reliably or effectively to derive the physical identity of an intruder in order to prevent further malicious wireless broadcasts, for example by escorting an intruder off the premises based on physical evidence. In this paper, we argue that Embedded Sensor Networks could be used effectively to bridge the gap between digital and physical security planes, and thus could be leveraged to provide reciprocal benefit to surveillance and security tasks on both planes. Toward that end, we present our recent experience integrating wireless networking security services into the SNBENCH (Sensor Network workBench). The SNBENCH provides an extensible framework that enables the rapid development and automated deployment of Sensor Network applications on a shared, embedded sensing and actuation infrastructure. The SNBENCH's extensible architecture allows an engineer to quickly integrate new sensing and response capabilities into the SNBENCH framework, while high-level languages and compilers allow novice SN programmers to compose SN service logic, unaware of the lower-level implementation details of tools on which their services rely. In this paper we convey the simplicity of the service composition through concrete examples that illustrate the power and potential of Wireless Security Services that span both the physical and digital plane.National Science Foundation (CISE/CSR 0720604, ENG/EFRI 0735974, CIES/CNS 0520166, CNS/ITR 0205294, CISE/ERA RI 0202067

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Quality-aware model-driven service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services

To Frame or Reframe: Where Might Design Thinking Research Go Next?

Design thinking is gaining widespread attention in the practitioner and academic literature. Successful implementation has been documented, and its value shown in empirical studies. There is little examination, however, of how design thinking practices fit with other approaches from which firms might choose to frame and solve problems such as agile, lean startup, scientific method, Six Sigma, critical thinking, and systems thinking. By digging into the basic capabilities underlying design thinking, academic researchers might better understand problem framing and solving in general and provide insight for practitioners as to where alternative approaches might be applied

Information Accountability Framework for a Trusted Health Care System

Trusted health care outcomes are patient centric. Requirements to ensure both the quality and sharing of patients’ health records are a key for better clinical decision making. In the context of maintaining quality health, the sharing of data and information between professionals and patients is paramount. This information sharing is a challenge and costly if patients’ trust and institutional accountability are not established. Establishment of an Information Accountability Framework (IAF) is one of the approaches in this paper. The concept behind the IAF requirements are: transparent responsibilities, relevance of the information being used, and the establishment and evidence of accountability that all lead to the desired outcome of a Trusted Health Care System. Upon completion of this IAF framework the trust component between the public and professionals will be constructed. Preservation of the confidentiality and integrity of patients’ information will lead to trusted health care outcomes

Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices (wearables, home-medical sensors, etc) facilitates data collection and provide cloud storage with a central administration. More recently, blockchain and other distributed ledgers became available as alternative storage options based on decentralised organisation systems. We bring attention to the human data bleeding problem and argue that neither centralised nor decentralised system organisations are a magic bullet for data-driven innovation if individual, community and societal values are ignored. The motivation for this position paper is to elaborate on strategies to protect privacy as well as to encourage data sharing and support open data without requiring a complex access protocol for researchers. Our main contribution is to outline the design of a self-regulated Open Health Archive (OHA) system with focus on quality of life (QoL) data.Comment: DSS 2018: Data-Driven Self-Regulating System