Integration of IEEE C37.118 and publish/subscribe communication

IEEE C37.118 is the current standard for synchrophasor measurements in power systems. It defines the measurement method and communication protocols for the entities in a synchrophasor network. The standard offers two different modes for client-server communication, but cannot be used unchanged over publish/subscribe communication architectures, whose major advantage is simplified and incremental integration of new applications. This work reviews the communication part of IEEE C37.118, and provides an adapter-based solution to easily connect and integrate entities in a synchrophasor network over a publish/subscribe communication architecture. The proposed adapters offer standard-compliant communication between the synchrophasor measurement network entities to facilitate the exchange of measurement data

Middleware architectures for the smart grid: A survey on the state-of-the-art, taxonomy and main open issues

The integration of small-scale renewable energy sources in the smart grid depends on several challenges that must be overcome. One of them is the presence of devices with very different characteristics present in the grid or how they can interact among them in terms of interoperability and data sharing. While this issue is usually solved by implementing a middleware layer among the available pieces of equipment in order to hide any hardware heterogeneity and offer the application layer a collection of homogenous resources to access lower levels, the variety and differences among them make the definition of what is needed in each particular case challenging. This paper offers a description of the most prominent middleware architectures for the smart grid and assesses the functionalities they have, considering the performance and features expected from them in the context of this application domain

Recent advances in information-centric networking based internet of things (ICN-IoT)

Information-Centric Networking (ICN) is being realized as a promising approach to accomplish the shortcomings of current IP-address based networking. ICN models are based on naming the content to get rid of address-space scarcity, accessing the content via name-based-routing, caching the content at intermediate nodes to provide reliable, efficient data delivery and self-certifying contents to ensure better security. Obvious benefits of ICN in terms of fast and efficient data delivery and improved reliability raises ICN as highly promising networking model for Internet of Things (IoTs) like environments. IoT aims to connect anyone and/or anything at any time by any path on any place. From last decade, IoTs attracts both industry and research communities. IoTs is an emerging research field and still in its infancy. Thus, this paper presents the potential of ICN for IoTs by providing state-of-the-art literature survey. We discuss briefly the feasibility of ICN features and their models (and architectures) in the context of IoT. Subsequently, we present a comprehensive survey on ICN based caching, naming, security and mobility approaches for IoTs with appropriate classification. Furthermore, we present operating systems (OS) and simulation tools for ICN-IoT. Finally, we provide important research challenges and issues faced by ICN for IoTs

An Optimized Hybrid Encryption Framework for Smart Home Healthcare: Ensuring Data Confidentiality and Security

This study proposes an optimized hybrid encryption framework combining ECC-256r1 with AES-128 in EAX mode, tailored for smart home healthcare environments, and conducts a comprehensive investigation to validate its performance. Our framework addresses current limitations in securing sensitive health data and demonstrates resilience against emerging quantum computing threats. Through rigorous experimental evaluation, we show that the proposed configuration outperforms existing solutions by delivering unmatched security, processing speed, and energy efficiency. It employs a robust yet streamlined approach, meticulously designed to ensure simplicity and practicality, facilitating seamless integration into existing systems without imposing undue complexity. Our investigation affirms the framework's capability to resist common cybersecurity threats like MITM, replay, and Sybil attacks while proactively considering quantum resilience. The proposed method excels in processing speed (0.006 seconds for client and server) and energy efficiency (3.65W client, 95.4W server), offering a quantum-resistant security level comparable to AES-128. This represents a security-efficiency ratio of 21.33 bits per millisecond, a 25.6% improvement in client-side processing speed, and up to 44% reduction in server-side energy consumption compared to conventional RSA-2048 methods. These improvements enable real-time encryption of continuous health data streams in IoT environments, making it ideal for IoT devices where AES-128′s smaller footprint is advantageous. By prioritizing high-grade encryption alongside ease of use and implementation, the proposed framework presents a future-proof solution that anticipates the trajectory of cryptographic standards amid advancing quantum computing technologies, signifying a pivotal advancement in safeguarding IoT-driven healthcare data

Air Force Institute of Technology Research Report 2020

This Research Report presents the FY20 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Identification and manipulation of lily bulbs for an automated lily bulb planting system

Automation in agriculture is growing year by year. The goal of automating processes is to provide inexpensive and more effective solutions for everyday problems present in the industry. Automation in agriculture adds value to the product and in turn, to the farmer's infrastructure. This automation also aims to provide higher skill labour for workers that the automation processes substitute. Using machine vision as a means of automating processes is very common in factory environments and is being adapted for the external agriculture environments (i.e. automated detection for produce harvesting). Machine vision and manipulation techniques for a lily bulb plantation were presented. The techniques were investigated to determine the feasibility of using an autonomous, machine vision based approach to manipulate and plant lily bulbs from a provided source, to pre-augered holes produced by a pre-defined autonomous platform. The machine vision approach involved taking a top down image of the bulbs and identifying the head positions and what orientation they were facing relative to their root structures. This was achieved using various standard machine vision techniques like segmenting using global thresholding and identification of heads using the Hough circular transform. The investigated manipulation method involved applying the above mentioned vision system to a standard ABB IRB-120 universal manipulator with a three bellow suction gripper to pick up the detected bulbs and manipulate the bulbs in the orientation perceived by the vision system. It was found that the machine vision algorithm provided a 75 per cent success rate when providing an optimal region of interest within the bulbs head. The success rate is a considerably successful result as the detection algorithm not only needed to detect the location of the bulbs, but the centroid of its head and also determine the approximate orientation relative to each samples individual root structure. The manipulation results showed that the engagement of the suction gripper was a significant component of failure during testing. The observed success rate was at 41 per cent. This high failure rate means that further improvements should be made before a successful end effector and manipulation pair would be achieved. Improving suction rate or developing a specialized gripper for the specific amorphous bulbs would have to be investigated further before there is confirmation of a satisfactory solution for the Automated Lily Planter. Further work could be done to improve the algorithm and fine-tune the output provided. Improvements could be made to optimise the detection algorithm like improved lighting and better contrast between the bulbs colour gradient and that of the platform's background. Further development on the manipulators approach should also be conducted for validation

DFT-based Synchrophasor Estimation Algorithms and their Integration in Advanced Phasor Measurement Units for the Real-time Monitoring of Active Distribution Networks

The increasing penetration of Distributed Energy Resources (DERs) at the low and medium-voltage levels is determining major changes in the operational procedures of distribution networks (DNs) that are evolving from passive to active power grids. Such evolution is causing non-negligible problems to DN operators (DNOs) and calls for advanced monitoring infrastructures composed by distributed sensing devices capable of monitoring voltage and current variations in real-time. In this respect, Phasor Measurement Units (PMUs) definitely represent one of the most promising technologies. Their higher accuracy and reporting rates compared to standard monitoring devices, together with the possibility of reporting time-tagged measurements of voltage and current phasors, enable the possibility to obtain frequent and accurate snapshots of the status of the monitored grid. Nevertheless, the applicability of such technology to DNs has not been demonstrated yet since PMUs where originally conceived for transmission network applications. Within this context, this thesis first discusses and derives the requirements for PMUs expected to operate at power distribution level. This study is carried out by analyzing typical operating conditions of Active Distribution Networks (ADNs). Then, based on these considerations, an advanced synchrophasor estimation algorithm capable of matching the accuracy requirements of ADNs is formulated. The algorithm, called iterative-interpolated DFT (i-IpDFT) improves the performances of the Interpolated-DFT (IpDFT) method by iteratively compensating the effects of the spectral interference produced by the negative image of the spectrum and at the same time allows to reduce the window length up to two periods of a signal at the nominal frequency of the power system. In order to demonstrate the low computational complexity of such an approach, the developed algorithm has been subsequently optimized to be deployed into a dedicated FPGA-based PMU prototype. The influence of the PMU hardware components and particularly the effects of the stability and reliability of the adopted UTC-time synchronization technology have been verified. The PMU prototype has been metrologically characterized with respect to the previously defined operating conditions of ADNs using a dedicated PMU calibrator developed in collaboration with the Swiss Federal Institute of Metrology (METAS). The experimental validation has verified the PMU compliance with the class-P requirements defined in the IEEE Std. C37.118 and with most of the accuracy requirements defined for class-M PMUs with the exception of out of band interference tests