3,474 research outputs found

    Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

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    Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

    Low-Cost UAV Swarm for Real-Time Object Detection Applications

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    With unmanned aerial vehicles (UAVs), also known as drones, becoming readily available and affordable, applications for these devices have grown immensely. One type of application is the use of drones to fly over large areas and detect desired entities. For example, a swarm of drones could detect marine creatures near the surface of the ocean and provide users the location and type of animal found. However, even with the reduction in cost of drone technology, such applications result costly due to the use of custom hardware with built-in advanced capabilities. Therefore, the focus of this thesis is to compile an easily customizable, low-cost drone design with the necessary hardware for autonomous behavior, swarm coordination, and on-board object detection capabilities. Additionally, this thesis outlines the necessary network architecture to handle the interconnection and bandwidth requirements of the drone swarm. The drone on-board system uses a PixHawk 4 flight controller to handle flight mechanics, a Raspberry Pi 4 as a companion computer for general-purpose computing power, and a NVIDIA Jetson Nano Developer Kit to perform object detection in real-time. The implemented network follows the 802.11s standard for multi-hop communications with the HWMP routing protocol. This topology allows drones to forward packets through the network, significantly extending the flight range of the swarm. Our experiments show that the selected hardware and implemented network can provide direct point-to-point communications at a range of up to 1000 feet, with extended range possible through message forwarding. The network also provides sufficient bandwidth for bandwidth intensive data such as live video streams. With an expected flight time of about 17 minutes, the proposed design offers a low-cost drone swarm solution for mid-range aerial surveillance applications

    Overlay networks for smart grids

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    Design and implementation of a cognitive node for heterogeneous wireless ad-hoc

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    In this thesis, the design of a cognitive network layer solution for a scenario with mobile devices is presented. Cognitive networks are able to sense the environment and adapt in order to find the best performance of the network at any moment. The final objective is to carry out a design of a node of the network which has incorporated in it up to three different technologies, which are WLAN, Bluetooth and ZigBee. The node is able to determine whether a technology should be used or not based on the network state. In order to find out the network state, a routing protocol based on Link State to provide the full view of the network is designed. Adaptive routing metrics have been designed in order to determine the best performance of the network to meet the QoS requirements considering what service is being required by the application and therefore to choose what technology is more appropriated for the connection. Those metrics are based on the capacity of the link, which takes into account the technology, the delay and the packet error rate of itself, and the utilization level. Then, Dijkstras’ algorithm is computed to solve the routing problem based on the adaptive weights instead of using the traditional hop-based count as a cost function. Furthermore, a heterogeneous cognitive wireless ad-hoc network testbed is implemented to analyze the behavior of the cognitive network when different types of services are used. On top of the cognitive network layer, an application to arrange meetings is implemented. Meeting rooms offer two different type of service for the guests, video and data service. Thus, clients are able to configure a video conference with the meeting room in case they cannot attend the meeting
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