Designing the Sensing as a Service Ecosystem for the Internet of Things

Abstract

The Internet of Things (IoT) envisions the creation of an environment where everyday objects (e.g. microwaves, fridges, cars, coffee machines, etc.) are connected to the internet and make users' lives more productive, efficient, and convenient. During this process, everyday objects capture a vast amount of data that can be used to understand individuals and their behaviours. In the current IoT ecosystems, such data is collected and used only by the respective IoT solutions. There is no formal way to share data with external entities. We believe this is very efficient and unfair for users. We believe that users, as data owners, should be able to control, manage, and share data about them in any way that they choose and make or gain value out of them. To achieve this, we proposed the Sensing as a Service (S 2 aaS) model. In this paper, we discuss the Sensing as a Service ecosystem in terms of its architecture, components and related user interaction designs. This paper aims to highlight the weaknesses of the current IoT ecosystem and to explain how S 2 aaS would eliminate those weaknesses. We also discuss how an everyday user may engage with the S 2 aaS ecosystem and design challenges.

Software Engineering for IoT-Driven Data Analytics Applications

“…In an IoT context, the concept of data fusion, i.e., things and devices producing, consuming, and exchanging large sets of data (volume, velocity, and variety of it) give rise to big data [21,22]. IoT supported big data is the key enabler for data-driven intelligence that provide foundations for sustainable computing environments in the form of intelligent systems and smart cities [3]. In recent years, a number of research studies have focused on applying SE processes (principle and practices) focused on architectures, patterns, frameworks, and tool support to engineer IoTbased software systems [2,3,28].…”

“…IoT supported big data is the key enabler for data-driven intelligence that provide foundations for sustainable computing environments in the form of intelligent systems and smart cities [3]. In recent years, a number of research studies have focused on applying SE processes (principle and practices) focused on architectures, patterns, frameworks, and tool support to engineer IoTbased software systems [2,3,28]. A recently published road map to software engineering in IoT era suggests that SE research and development have mainly focused on addressing issues that relate to the development of IoTs in the context of smart systems and cities [11].…”

“…IoT as a network of interconnected devices has emerged as a disruptive technology and an enabling platform that interconnects heterogeneous things such as humans, systems, services, and devices in a smart environment [1,2,3]. A recent survey by Gartner predicts that by the year 2020, the world will become home to 20 billion internet-connected things with data produced, consumed, and processed by IoTs will funnel through IoT-DA platforms [1].…”

“…A rapid proliferation of IoT systems is primarily due to portable devices that unify hardware (embedded sensors) software (applications that manipulate sensors) and network (protocols that connect sensors) to enable things that collect, process, and exchange contextualised data [2]. Typical example of such contextualised data includes crowd-sensed traffic congestions or environmental pollution that can be captured by embedded sensors of mobile devices, manipulated by mobile applications, and transmitted over wireless networks [3]. IoT systems in general and IoT-DA applications in particular act as the backbone for data-driven smart cities and infrastructure initiatives across the globe such as in United States [4], Europe, and Asia [5,6].…”

Authentic Caller: Self-Enforcing Authentication in a Next-Generation Network

“…human involvement [1]. The Internet of Things (IoT) and Cyber-Physical system (CPS) are the major driving forces in the smart interconnected environment.…”