484,084 research outputs found

    A Middleware for the Internet of Things

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    The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as things to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things, or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.Comment: 20 pages, International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.2, March 201

    Recent advances in industrial wireless sensor networks towards efficient management in IoT

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    With the accelerated development of Internet-of- Things (IoT), wireless sensor networks (WSN) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for wireless sensor networks design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross layer design of lightweight and cloud-based RESTful web service

    Powering Systems From Ambient Energy Sources

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    Ambient intelligence and the Internet of Things will require flexible and energy efficient hardware platforms to implement the long-term deployed wireless devices that form the physical substrate for these emerging cyberphysical systems. Energy harvesting from environmental sources such as light and mechanical vibration can extend battery life for devices as long as efficient power management circuits are available. Self-timed circuits, power-on resets, integrated switched-capacitor DC/DC converters and adaptively-biased linear regulators are complementary circuit techniques that can reduce cost and power consumption for microwatt energy harvesting and energy scalable systems. Low power and low voltage analog and digital circuits for sampling, digitizing, and processing external signals are essential for powering systems from ambient energy sources. This talk presents an overview of these topics and describes how exploiting the relationship between system requirements, circuits, and environmental energy sources can enable the emergence of the Internet of Things

    Efficient energy management for the internet of things in smart cities

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    The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities

    Authentication Of the Internet of Things Devices Over ZigBee Networks

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    IOT, or the Internet of Things, is the inter-networking smart devices, buildings and other embedded systems to enable them to transfer data between them. This data can be used for various uses such as power management and home automation. Current projections of the Internet of Things predicate that the use of this technology will increase dramatically within the foreseeable future. Many of these devices are currently being implemented using protocol such as Bluetooth and ZigBee. ZigBee is a wireless communication protocol based on the IEEE 802.11.4 standard. ZigBee was created for low power devices, such as those that run on batteries, with the industrial settings being among the common implementation of ZigBee enabled devices. The project focuses on improving the ZigBee protocol, specifically in the authentication section of the protocol.https://ecommons.udayton.edu/stander_posters/2237/thumbnail.jp

    SIW antennas as hybrid energy harvesting and power management platforms for the internet of things

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    A novel antenna-harvester co-design paradigm is presented for wireless nodes operating in an Internet of Things context. The strategy leads to compact and highly-integrated units, which are able to set up a reliable and energy-efficient wireless communication link, and to simultaneously harvest energy from up to three different sources, including thermal body energy, solar, and artificial light. The core of the unit consists of a substrate-integrated-waveguide (SIW) antenna. Its surface serves as a platform for the flexible energy-harvesting hardware, which also comprises the power management system. To demonstrate the approach, two different SIW cavity-backed slot antennas and a novel compact dual linearly polarized SIW antenna are presented. These topologies facilitate the integration of additional hardware without degrading performance. In the meantime, they enable comfortable integration into garments or unobtrusive embedding into floors or walls. Measurements on prototypes validate the integration procedure by verifying that the integrated hardware has a negligible influence on the performance of all discussed SIW antennas. Finally, measurements in four well-chosen indoor scenarios demonstrate that a hybrid energy-harvesting approach is necessary to obtain a more continuous flow and a higher amount of scavenged energy, leading to a higher system autonomy and/or reduced battery size

    Idleness-aware dynamic power mode selection on the i.Mx 7ULP iot edge processor

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    Power management is a crucial concern in micro-controller platforms for the Internet of Things (IoT) edge. Many applications present a variable and difficult to predict workload profile, usually driven by external inputs. The dynamic tuning of power consumption to the application requirements is indeed a viable approach to save energy. In this paper, we propose the implementation of a power management strategy for a novel low-cost low-power heterogeneous dual-core SoC for IoT edge fabricated in 28 nm FD-SOI technology. Ss with more complex power management policies implemented on high-end application processors, we propose a power management strategy where the power mode is dynamically selected to ensure user-specified target idleness. We demonstrate that the dynamic power mode selection introduced by our power manager allows achieving more than 43% power consumption reduction with respect to static worst-case power mode selection, without any significant penalty in the performance of a running application

    On Link Estimation in Dense RPL Deployments

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    The Internet of Things vision foresees billions of devices to connect the physical world to the digital world. Sensing applications such as structural health monitoring, surveillance or smart buildings employ multi-hop wireless networks with high density to attain sufficient area coverage. Such applications need networking stacks and routing protocols that can scale with network size and density while remaining energy-efficient and lightweight. To this end, the IETF RoLL working group has designed the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL). This paper discusses the problems of link quality estimation and neighbor management policies when it comes to handling high densities. We implement and evaluate different neighbor management policies and link probing techniques in Contiki’s RPL implementation. We report on our experience with a 100-node testbed with average 40-degree density. We show the sensitivity of high density routing with respect to cache sizes and routing metric initialization. Finally, we devise guidelines for design and implementation of density-scalable routing protocols
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