Internet-of-Things (IoT) Analytics refers to the process of transforming vast amounts of information from heterogeneous internet-connected objects, data sources and devices (e.g., sensors, appliances, cyber-physical systems, Machine-to-Machine systems) to business and application intelligence. Several tools and techniques for IoT analytics have their roots in conventional web analytics, which process and combine data streams from web-connected computers, cell phones and web databases. However, IoT analytics broaden the scope of web analytics on the basis of the collection, processing and analysis of information produced by internet-connected devices, thus enhancing the scope and functionalities of related applications.

The iKaaS (intelligent Knowledge-as-a-Service) platform unitarily manages the data on existing cloud systems, which allows applications to access their desired data scattered all over the world transparently. Hidano et al. have proposed an access control mechanism suitable for the iKaaS platform to resolve privacy issues on the transfer of personal data to the applications in different countries. They introduced the concept of a privacy certificate authority (CA) to provide support for confirming the validity of the application. The privacy CA is established for each country as the executive agency responsible for the national regulations governing the handling of personal data. In this paper, we design a hierarchical model of multiple privacy CAs responsible for regulations where the areas governed by these regulations are different. The data transfer can be thereby controlled not only for different countries, but also for different economic or political blocs (e.g., European Union) or cities. In addition, focusing on a town management application as a use case of the iKaaS platform, we present how our access control mechanism works.

Reports on initiatives to promote and develop the Internet of Things in Africa.

Over the last years, the Internet of Things (IoT) has moved from being a futuristic vision to market reality. It is not a question any more whether IoT will be surpassing the hype, it is already there and the race between IoT industry stakeholders has already begun. The IoT revolution comes with trillions of connected devices; however the real value of IoT is in the advanced processing of the collected data. By nature, IoT data is more dynamic, heterogeneous and unstructured than typical business data. It demands more sophisticated, IoTspecific analytics to make it meaningful. The exploitation in the Cloud of data obtained in real time from sensors is therefore very much a necessity. This data processing leads to advanced proactive and intelligent applications and services. The connection of IoT and BigData can offer: i) deep understanding of the context and situation; ii) real-time actionable insight; iii) performance optimization; and iv) proactive and predictive knowledge. Cloud technologies offer decentralized and scalable information processing and analytics, and data management capabilities. This chapter describes a Cloud based IoT and BigData platform, together with their requirements. This includes multiple sensors and devices, BigData analytics, cloud data management, edge-heavy computing, machine learning and virtualization. In this chapter, Section 2.2 introduces the characteristics of an online Cloud IoT platform. Section 2.3 shows the challenge posed by the huge amount of data to be processed, from the point of view of the quality and quantity of data. It gives an overview of the technologies able to address those challenges.

ICT developments in Sub-Saharan Africa has the potential to cut across traditional sectors: notable examples are the introduction of micro-health insurance and health-savings accounts through mobile devices; index-based crop insurance; crowd-sourcing to monitor and manage the delivery of public services. These innovative applications recognize and leverage commonalities between sectors, blur traditional lines, and open up a new field of opportunities. The opportunity for ICT intervention in Africa is huge especially of IoT and big data: those technologies are promising a big wave of innovation for our daily life. The era of IoT can connect billions of sensors, devices, equipment, systems. In turn, the challenge is about driving business outcomes, consumer benefits, and the creation of new value. The new mantras for the IoT era is the collection, convergence and exploitation of data. The information collection involves data from sensors, devices, gateways, edge equipment and networks. This information allows increasing process efficiency through automation while reducing downtime and improving people productivity. The WAZIUP project will show:

Long-range radio are promising technologies to deploy low-cost Low Power WAN for a large variety of IoT applications. There are however many issues that must be considered before deploying IoT solutions for low-income developing countries. This article will present these issues and show how they can be addressed in the context of African rural applications. We then describe the WAZIUP low-cost and long-range IoT framework. The framework takes cost of hardware and services as the main challenge to be addressed as well as offering quick appropriation and customization possibilities by third-parties.

IoT has not fully diffused in Africa to address various challenges faced by African people. To address the emergence and pervasiveness of IoT in Africa, we present an open IoT, and big data platform as an innovation platform to accelerate innovations in rural Africa. However, the technology is not dedicated to the rural cases; it is designed for any IoT application. The platform will allow to develop IoT applications coupled with Big Data capacities. Moreover, the platform can be tailored to the specific requirements and constraints of African users. In this paper, we give an overview of the proposed IoT and Big Data platform, detail its technical aspects, and finally introduce three use case deployments to prove the validity of platform architecture.

Informed consent is an essential element of data protection for information and communication technology (ICT) systems as the consent of a data subject (e.g., the citizen) is often necessary for a third party to legitimately process personal data. To provide informed consent regarding the use of personal data, the citizen must have a clear understanding of how his/her personal data will be used by ICT applications. This may not be an easy task, especially for a citizen with a limited understanding of the complexities of ICT systems, as End User License Agreements (EULAs) are often either too complex or too generic to be easily understood. This issue is likely to become more critical in the Internet of Things (IoT) where the collection of personal data can happen in various ways, which are often not evident to the user. There is a need to define new models of informed consent that (a) address the different capabilities and features of the user of IoT systems and applications and (b) make the provision of informed consent easier. In this chapter, we describe an approach to informed consent founded on a policybased framework whereby policies that are more suited to the complexities of IoT and that can be refined on the basis of the specific features of the user or categories of users can be used to implement EULAs or more sophisticated forms of informed consent.

The iKaaS (intelligent Knowledge-as-a-Service) platform integrates the data on multiple local cloudsystems organically and provides the data to various types of applications as knowledge while takingsecurity and privacy fully into account. However, access control on the iKaaS platform is not withoutcomplications because the application may access personal data in different countries from the onewhere the application exists. Hidano et al. thus designed a security gateway that is set at the entranceof each local cloud and controls access to the cross-border applications while interpreting regulationsrelated to personal data for both countries. In order to help the security gateway confirm the validityof the application, they introduced the concept of the privacy certificate authority (CA), which isbuilt for each country as an executive agency responsible for the national regulations governing thehandling of personal data. In this paper, we design a hierarchical model of multiple privacy CAsresponsible for regulations where the effective areas are different. The security gateway can therebycontrol the transfer of data not only to different countries, but also to different unions or cities.

The Informed Consent of a data subject (e.g., citizen) is often necessary to allow the legitimate processing of personal data by a third party application. The current implementation of Informed Consent based on End User License Agreements (EULA) has many limitations, which are likely to become more critical in future IoT applications, where the collection of personal data can happen in various ways and is not evident to the user. There is the need to define more sophisticated models of Informed Consent for IoT, which address the specific features of IoT, improve on the EULA approach, and protect the flow of personal data from the IoT sensors. In this paper, we propose an agent-based design for Informed Consent in IoT, where access to personal data is regulated through usage control policies, which can be tailored for the specific features of the user and the context. Policies are associated to users, service providers, and smart spaces containing IoT devices in a privacy-friendly way using pseudonyms. The main design concepts are described and applied to a smart city scenario, to evaluate the feasibility of the framework and the related deployment aspects.

60GHz wireless local area networks (WLANs) standards (e.g., IEEE 802.11ad and IEEE 802.15.3c) employ hybrid MAC protocols consisting of contention based access using CSMA/CA as well as dedicated service periods using time division multiple access (TDMA). To provide the channel access in the contention part of the protocol, quasi omni (QO) antenna patterns are defined which span over the particular spatial directions and cover a limited area around access points. In this paper, we propose an algorithm to determine the beamwidth of each QO level. The proposed algorithm takes into account the spatial distribution of nodes to allocate the beamwidth of each QO level in an adaptive fashion in order to maximizes the channel utilization and satisfy the required link budget criterion. Since the proposed algorithm minimizes the collisions, it also minimizes the average time required to transmit total packets in a QO level. Proposed algorithm improves the average channel utilization up to 20-30% and reduces the time required to transmit total packets up to 40-50% for the given network parameters.

In the domain of Internet of Things (IoT), applications are modeled to understand and react based on existing contextual and situational parameters. This work implements a management flow for the abstraction of real world objects and virtual composition of those objects to provide IoT services. We also present a real world knowledge model that aggregates constraints defining a situation, which is then used to detect and anticipate future potential situations. It is implemented based on reasoning and machine learning mechanisms. This work showcases a prototype implementation of the architectural framework in a smart home scenario, targeting two functionalities: actuation and automation based on the imposed constraints and thereby responding to situations and also adapting to the user preferences. It thus provides a productive integration of heterogeneous devices, IoT platforms, and cognitive technologies to improve the services provided to the user.

The success of the IoT world requires service provision attributed with ubiquity, reliability, high-performance, efficiency, and scalability. In order to accomplish this attribution, future business and research vision is to merge the Cloud Computing and IoT concepts, i.e., enable an “Everything as a Service” model: specifically, a Cloud ecosystem, encompassing novel functionality and cognitive-IoT capabilities, will be provided. Hence the paper will describe an innovative IoT centric Cloud smart infrastructure addressing individual IoT and Cloud Computing challenges.

Recently 60GHz communication has emerged as a potential candidate for high speed, short range radio communication. However, since the range of 60GHz is too small, a radio over fiber (RoF) based wireless personal area network (WPAN)employing IEEE 802.15.3c MAC for 60GHz frequency band is proposed in this paper. This hybrid network is known Fi- Wi. Based on detailed performance analysis of MAC, suitability of IEEE 802.15.3c in RoF indoor networks is examined carefully. Limitations of using IEEE 802.15.3c, due to the additional delay introduced by fiber distribution network are highlighted. Analysis of different acknowledgment (ACK) mechanisms in different physical channel conditions are performed, which is helpful in selecting appropriate ACK policy based on the requirements of applications. We provide a complete and thorough analysis of Fi- WiWPAN architecture based on IEEE 802.15.3c. This is expected to help designers and practitioners.

The Internet of Things (IoT) is expected to substantially support sustainable development of future smart cities. This article identifies the main issues that may prevent IoT from playing this crucial role, such as the heterogeneity among connected objects and the unreliable nature of associated services. To solve these issues, a cognitive management framework for IoT is proposed, in which dynamically changing real-world objects are represented in a virtualized environment, and where cognition and proximity are used to select the most relevant objects for the purpose of an application in an intelligent and autonomic way. Part of the framework is instantiated in terms of building blocks and demonstrated through a smart city scenario that horizontally spans several application domains. This preliminary proof of concept reveals the high potential that self-reconfigurable IoT can achieve in the context of smart cities.

Devices in future Internet of Things (IoT) will be scavenging energy from the ambiance for all their operations. They face challenges in various aspects of network organization and operation due to the nature of ambient energy sources such as, solar insolation, vibration and motion. In this paper we analyze the classical two-way algorithm for neighbor discovery (ND) in an energy harvesting IoT. Through analysis, we outline the parameters that play an important role in ND performance such as node density, duty cycle, beamwidth and energy profile. We also provide simulation results to understand the impact of the energy storage element of energy harvesting devices in the ND process. We demonstrate that there exist trade-offs in choices for antenna beamwidth and node duty cycle, given node density and energy arrival rate. We show that the variations in energy availability impact ND performance. We also demonstrate that the right size of the storage buffer can smooth the effects of energy variability.

In this article, a cognitive management framework is proposed for ensuring exploitation of the Future Internet of Things (FIoT). Cognitive systems offer self-x and learning. A cognitive system has the ability to dynamically select its behavior through self-management/awareness functionality, taking into account information and knowledge on the context of the operations as well as policies and including the generation of the context itself. The framework is based on the principle that any real world object and any digital object that is available, accessible, observable or controllable can have a virtual representation in the Future Internet, which is called Virtual Object (VO). Basic VOs can be composed in a more sophisticated way by forming Composite VOs (CVOs), which provide services to high-level applications and end-users. The described paradigm is applied to various applications scenarios: smart home, smart office, smart city and smart business. This paper presents some background in IoT, identifies the requirements and challenges, and sets the directions that should be followed. © 2012 SCPE.

This paper presents a framework for the virtualization of real world objects and the cognitive management of their virtual counterparts. The framework consists of three levels of functionality and each level comprises cognitive entities that provide the means for self-management and learning, allowing for smart, flexible applications and objects. The presented framework enables the abstraction of the heterogeneity that derives from the vast amount of diverse objects/devices, while enhancing reliability and facilitates the consideration of the views of various users/stakeholders (owners of objects & communication means) for ensuring proper application provision, business integrity and, therefore, maximization of exploitation opportunities. The paper also presents a corresponding prototype that has been developed for the validation of the proposed approach, in a real-life fire detection scenario in a Smart Home.

Software Defined Radio (SDR) and Cognitive Radio (CR) are promising technologies, which can be used to alleviate the spectrum shortage problem or the barriers to communication interoperability in various application domains. The successful deployment of SDR and CR technologies will depend on the design and implementation of essential security mechanisms to ensure the robustness of networks and terminals against security attacks. SDR and CR may introduce entirely new classes of security threats and challenges including download of malicious software, licensed user emulation and selfish misbehaviors. An attacker could disrupt the basic functions of a CR network, cause harmful interference to licensed users or deny communication to other CR nodes. The research activity in this area has started only recently and many challenges are still to be resolved. This paper presents a survey of security aspects in SDR and CR. We identify the requirements for the deployment of SDR and CR, the main security threats and challenges and the related protection techniques. This paper provides an overview of the SDR and CR certification process and how it is related to the security aspects. Finally, this paper summarizes the most critical challenges in the context of the future evolution of SDR/CR technologies.