A gap analysis of Internet-of-Things platforms

We are experiencing an abundance of Internet-of-Things (IoT) middleware solutions that provide connectivity for sensors and actuators to the Internet. To gain a widespread adoption, these middleware solutions, referred to as platforms, have to meet the expectations of different players in the IoT ecosystem, including device providers, application developers, and end-users, among others. In this article, we evaluate a representative sample of these platforms, both proprietary and open-source, on the basis of their ability to meet the expectations of different IoT users. The evaluation is thus more focused on how ready and usable these platforms are for IoT ecosystem players, rather than on the peculiarities of the underlying technological layers. The evaluation is carried out as a gap analysis of the current IoT landscape with respect to (i) the support for heterogeneous sensing and actuating technologies, (ii) the data ownership and its implications for security and privacy, (iii) data processing and data sharing capabilities, (iv) the support offered to application developers, (v) the completeness of an IoT ecosystem, and (vi) the availability of dedicated IoT marketplaces. The gap analysis aims to highlight the deficiencies of today's solutions to improve their integration to tomorrow's ecosystems. In order to strengthen the finding of our analysis, we conducted a survey among the partners of the Finnish IoT program, counting over 350 experts, to evaluate the most critical issues for the development of future IoT platforms. Based on the results of our analysis and our survey, we conclude this article with a list of recommendations for extending these IoT platforms in order to fill in the gaps.Comment: 15 pages, 4 figures, 3 tables, Accepted for publication in Computer Communications, special issue on the Internet of Things: Research challenges and solution

Investigating IoT Middleware Platforms for Smart Application Development

With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement

CamFlow: Managed Data-sharing for Cloud Services

A model of cloud services is emerging whereby a few trusted providers manage the underlying hardware and communications whereas many companies build on this infrastructure to offer higher level, cloud-hosted PaaS services and/or SaaS applications. From the start, strong isolation between cloud tenants was seen to be of paramount importance, provided first by virtual machines (VM) and later by containers, which share the operating system (OS) kernel. Increasingly it is the case that applications also require facilities to effect isolation and protection of data managed by those applications. They also require flexible data sharing with other applications, often across the traditional cloud-isolation boundaries; for example, when government provides many related services for its citizens on a common platform. Similar considerations apply to the end-users of applications. But in particular, the incorporation of cloud services within `Internet of Things' architectures is driving the requirements for both protection and cross-application data sharing. These concerns relate to the management of data. Traditional access control is application and principal/role specific, applied at policy enforcement points, after which there is no subsequent control over where data flows; a crucial issue once data has left its owner's control by cloud-hosted applications and within cloud-services. Information Flow Control (IFC), in addition, offers system-wide, end-to-end, flow control based on the properties of the data. We discuss the potential of cloud-deployed IFC for enforcing owners' dataflow policy with regard to protection and sharing, as well as safeguarding against malicious or buggy software. In addition, the audit log associated with IFC provides transparency, giving configurable system-wide visibility over data flows. [...]Comment: 14 pages, 8 figure

Unleashing the Potential of the Internet of Things in Transforming Libraries into Intelligent Hubs of Digital Knowledge

Internet of Things (IoT) is a rapidly evolving technology that has the potential to transform the way libraries operate and provide services to their patrons. By connecting devices and systems to the internet, libraries can gain access to real-time data and automate many of their processes, leading to more efficient and effective operations. This paper explores the use of IoT in libraries, specifically focusing on how it can enable smart libraries in the digital era. The paper will discuss the benefits and challenges of implementing IoT in libraries and provide examples of how libraries are currently using IoT to improve their services. The paper will also explore the future possibilities of IoT in libraries and how it can be used to enhance the user experience and support the development of new services. Overall, this paper will provide an overview of the IoT technology and its potential to revolutionize the way libraries operate and provide services to their patrons in the digital era

Cyber-Physical Manufacturing Metrology Model (CPM3) for Sculptured Surfaces - Turbine Blade Application

Cyber-Physical Manufacturing (CPM) and digital manufacturing represent the key elements for implementation of Industry 4.0 framework. Worldwide, Industry 4.0 becomes national research strategy in the field of engineering for the following ten years. The International Conference USA-EU-Far East-Serbia Manufacturing Summit was held from 31st May to 2nd June 2016 in Belgrade, Serbia. The result of the conference was the development of Industry 4.0 Model for Serbia as a framework for New Industrial Policy - Horizon 2020/2030. Implementation of CPM in manufacturing systems generates " smart factory". Products, resources, and processes within smart factory are realized and controlled through CPM model. This leads to significant advantages with respect to high product/process quality, real-time applications, savings in resources consumption, as well as, lower costs in comparison with classical manufacturing systems. Smart factory is designed in accordance with sustainable and service-oriented best business practices/models. It is based on optimization, flexibility, self-adaptability and learning, fault tolerance, and risk management. Complete manufacturing digitalization and digital factory are the key elements of Industry 4.0 Program. In collaborative research, which we carry out in the field of quality control and manufacturing metrology at University of Belgrade, Faculty of Mechanical Engineering in Serbia and at Department of Mechanical Engineering, University of Texas, Austin in USA, three research areas are defined: (a) Digital manufacturing - towards Cloud Manufacturing Systems (as a basis for CPS), in which quality and metrology represent integral parts of process optimization based on Taguchi model, and (sic) Cyber-Physical Quality Model (CPQM) - our approach, in which we have developed and tested intelligent model for prismatic parts inspection planning on CMM (Coordinate Measuring Machine). The third research area directs our efforts to the development of framework for Cyber-Physical Manufacturing Metrology Model (CPM3). CPM3 framework will be based on integration of digital product metrology information through metrology features recognition, and generation of global/local inspection plan for free-form surfaces; we will illustrate our approach using turbine blade example. This paper will present recent results of our research on CPM3

Integration of heterogeneous devices and communication models via the cloud in the constrained internet of things

As the Internet of Things continues to expand in the coming years, the need for services that span multiple IoT application domains will continue to increase in order to realize the efficiency gains promised by the IoT. Today, however, service developers looking to add value on top of existing IoT systems are faced with very heterogeneous devices and systems. These systems implement a wide variety of network connectivity options, protocols (proprietary or standards-based), and communication methods all of which are unknown to a service developer that is new to the IoT. Even within one IoT standard, a device typically has multiple options for communicating with others. In order to alleviate service developers from these concerns, this paper presents a cloud-based platform for integrating heterogeneous constrained IoT devices and communication models into services. Our evaluation shows that the impact of our approach on the operation of constrained devices is minimal while providing a tangible benefit in service integration of low-resource IoT devices. A proof of concept demonstrates the latter by means of a control and management dashboard for constrained devices that was implemented on top of the presented platform. The results of our work enable service developers to more easily implement and deploy services that span a wide variety of IoT application domains

Understanding packet loss for sound monitoring in a smart stadium IoT testbed

The Smart Stadium for Smarter Living project provides an end-to-end testbed for IoT innovation through a collaboration between Croke Park Stadium in Dublin, Ireland and Dublin City University, Intel and Microsoft. This enables practical evaluations of IoT solutions in a controlled environment that is small enough to conduct trials but large enough to prove and challenge the technologies. An evaluation of sound monitoring capabilities during the 2016 sporting finals was used to test the capture, transfer, storage and analysis of decibel level sound monitoring. The purpose of the evaluation was to use existing sound level microphones to measure crowd response to pre-determined events for display on big screens at half-time and to test the end-to-end performance of the testbed. While this is not the specific original purpose of the sound level microphones, it provided a useful test case and produced engaging content for the project. Analysis of the data streams showed significant packet loss during the events and further investigations were conducted to understand where and how this loss occurred. This paper describes the smart stadium testbed configuration using Intel gateways linking with the Azure cloud platform and analyses the performance of the system during the sound monitoring evaluation