System Design of Internet-of-Things for Residential Smart Grid

Internet-of-Things (IoTs) envisions to integrate, coordinate, communicate, and collaborate real-world objects in order to perform daily tasks in a more intelligent and efficient manner. To comprehend this vision, this paper studies the design of a large scale IoT system for smart grid application, which constitutes a large number of home users and has the requirement of fast response time. In particular, we focus on the messaging protocol of a universal IoT home gateway, where our cloud enabled system consists of a backend server, unified home gateway (UHG) at the end users, and user interface for mobile devices. We discuss the features of such IoT system to support a large scale deployment with a UHG and real-time residential smart grid applications. Based on the requirements, we design an IoT system using the XMPP protocol, and implemented in a testbed for energy management applications. To show the effectiveness of the designed testbed, we present some results using the proposed IoT architecture.Comment: 10 pages, 6 figures, journal pape

Development of Wi-Fi based home energy monitoring system for green internet of things

Green Internet of things (IoT) has been heralded as the “next big thing” waiting to be realized in energy-efficient ubiquitous computing. Green IoT revolves around increased machine-to-machine communications and encompasses energy-efficient wireless embedded sensors and actuators that assist in monitoring and controlling home appliances. Energy efficiency in home applications can be achieved by better monitoring of the specific energy consumption by the appliances. There are many wireless standards that can be adopted for the design of such embedded devices in IoT. These communication technologies cater to different requirements and are classified as the short-range and long-range ones. To select the best communication method, this paper surveys various IoT communication technologies and discusses the advantages and disadvantages to develop an energy monitoring system. An IoT device based on the Wi-Fi technology system is developed and tested for usage in the home energy monitoring environment. The performance of this system is then evaluated by the measurement of power consumption metrics. In the efficient deep-sleep mode, the system saves up to 0.3 W per cycle with an average power dissipation of less than 0.1 W/s. Index Terms Energy efficiency, energy monitoring, Internet of things

RF Energy Harvesting Techniques for Battery-less Wireless Sensing, Industry 4.0 and Internet of Things: A Review

As the Internet of Things (IoT) continues to expand, the demand for the use of energy-efficient circuits and battery-less devices has grown rapidly. Battery-less operation, zero maintenance and sustainability are the desired features of IoT devices in fifth generation (5G) networks and green Industry 4.0 wireless systems. The integration of energy harvesting systems, IoT devices and 5G networks has the potential impact to digitalize and revolutionize various industries such as Industry 4.0, agriculture, food, and healthcare, by enabling real-time data collection and analysis, mitigating maintenance costs, and improving efficiency. Energy harvesting plays a crucial role in envisioning a low-carbon Net Zero future and holds significant political importance. This survey aims at providing a comprehensive review on various energy harvesting techniques including radio frequency (RF), multi-source hybrid and energy harvesting using additive manufacturing technologies. However, special emphasis is given to RF-based energy harvesting methodologies tailored for battery-free wireless sensing, and powering autonomous low-power electronic circuits and IoT devices. The key design challenges and applications of energy harvesting techniques, as well as the future perspective of System on Chip (SoC) implementation, data digitization in Industry 4.0, next-generation IoT devices, and 5G communications are discussed

Investigation on Design and Development Methods for Internet of Things

The thesis work majorly focuses on the development methodologies of the Internet of Things (IoT). A detailed literature survey is presented for the discussion of various challenges in the development of software and design and deployment of hardware. The thesis work deals with the efficient development methodologies for the deployment of IoT system. Efficient hardware and software development reduces the risk of the system bugs and faults. The optimal placement of the IoT devices is the major challenge for the monitoring application. A Qualitative Spatial Reasoning (QSR) and Qualitative Temporal Reasoning (QTR) methodologies are proposed to build software systems. The proposed hybrid methodology includes the features of QSR, QTR, and traditional databased methodologies. The hybrid methodology is proposed to build the software systems and direct them to the specific goal of obtaining outputs inherent to the process. The hybrid methodology includes the support of tools and is detailed, integrated, and fits the general proposal. This methodology repeats the structure of Spatio-temporal reasoning goals. The object-oriented IoT device placement is the major goal of the proposed work. Segmentation and object detection is used for the division of the region into sub-regions. The coverage and connectivity are maintained by the optimal placement of the IoT devices using RCC8 and TPCC algorithms. Over the years, IoT has offered different solutions in all kinds of areas and contexts. The diversity of these challenges makes it hard to grasp the underlying principles of the different solutions and to design an appropriate custom implementation on the IoT space. One of the major objective of the proposed thesis work is to study numerous production-ready IoT offerings, extract recurring proven solution principles, and classify them into spatial patterns. The method of refinement of the goals is employed so that complex challenges are solved by breaking them down into simple and achievable sub-goals. The work deals with the major sub-goals e.g. efficient coverage of the field, connectivity of the IoT devices, Spatio-temporal aggregation of the data, and estimation of spatially connected regions of event detection. We have proposed methods to achieve each sub-goal for all different types of spatial patterns. The spatial patterns developed can be used in ongoing and future research on the IoT to understand the principles of the IoT, which will, in turn, promote the better development of existing and new IoT devices. The next objective is to utilize the IoT network for enterprise architecture (EA) based IoT application. EA defines the structure and operation of an organization to determine the most effective way for it to achieve its objectives. Digital transformation of EA is achieved through analysis, planning, design, and implementation, which interprets enterprise goals into an IoT-enabled enterprise design. A blueprint is necessary for the readying of IT resources that support business services and processes. A systematic approach is proposed for the planning and development of EA for IoT-Applications. The Enterprise Interface (EI) layer is proposed to efficiently categorize the data. The data is categorized based on local and global factors. The clustered data is then utilized by the end-users. A novel four-tier structure is proposed for Enterprise Applications. We analyzed the challenges, contextualized them, and offered solutions and recommendations. The last objective of the thesis work is to develop energy-efficient data consistency method. The data consistency is a challenge for designing energy-efficient medium access control protocol used in IoT. The energy-efficient data consistency method makes the protocol suitable for low, medium, and high data rate applications. The idea of energyefficient data consistency protocol is proposed with data aggregation. The proposed protocol efficiently utilizes the data rate as well as saves energy. The optimal sampling rate selection method is introduced for maintaining the data consistency of continuous and periodic monitoring node in an energy-efficient manner. In the starting phase, the nodes will be classified into event and continuous monitoring nodes. The machine learning based logistic classification method is used for the classification of nodes. The sampling rate of continuous monitoring nodes is optimized during the setup phase by using optimized sampling rate data aggregation algorithm. Furthermore, an energy-efficient time division multiple access (EETDMA) protocol is used for the continuous monitoring on IoT devices, and an energy-efficient bit map assisted (EEBMA) protocol is proposed for the event driven nodes

Ultra-Low Power Circuit Design for Miniaturized IoT Platform

This thesis examines the ultra-low power circuit techniques for mm-scale Internet of Things (IoT) platforms. The IoT devices are known for their small form factors and limited battery capacity and lifespan. So, ultra-low power consumption of always-on blocks is required for the IoT devices that adopt aggressive duty-cycling for high power efficiency and long lifespan. Several problems need to be addressed regarding IoT device designs, such as ultra-low power circuit design techniques for sleep mode and energy-efficient and fast data rate transmission for active mode communication. Therefore, this thesis highlights the ultra-low power always-on systems, focusing on energy efficient optical transmission in order to miniaturize the IoT systems. First, this thesis presents a battery-less sub-nW micro-controller for an always-operating system implemented with a newly proposed logic family. Second, it proposes an always-operating sub-nW light-to-digital converter to measure instant light intensity and cumulative light exposure, which employs the characteristics of this proposed logic family. Third, it presents an ultra-low standby power optical wake-up receiver with ambient light canceling using dual-mode operation. Finally, an energy-efficient low power optical transmitter for an implantable IoT device is suggested. Implications for future research are also provided.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145862/1/imhotep_1.pd

Privacy-Preserving Transactive Energy Management for IoT-aided Smart Homes via Blockchain

With the booming of smart grid, The ubiquitously deployed smart meters constitutes an energy internet of things. This paper develops a novel blockchain-based transactive energy management system for IoT-aided smart homes. We consider a holistic set of options for smart homes to participate in transactive energy. Smart homes can interact with the grid to perform vertical transactions, e.g., feeding in extra solar energy to the grid and providing demand response service to alleviate the grid load. Smart homes can also interact with peer users to perform horizontal transactions, e.g., peer-to-peer energy trading. However, conventional transactive energy management method suffers from the drawbacks of low efficiency, privacy leakage, and single-point failure. To address these challenges, we develop a privacy-preserving distributed algorithm that enables users to optimally manage their energy usages in parallel via the smart contract on the blockchain. Further, we design an efficient blockchain system tailored for IoT devices and develop the smart contract to support the holistic transactive energy management system. Finally, we evaluate the feasibility and performance of the blockchain-based transactive energy management system through extensive simulations and experiments. The results show that the blockchain-based transactive energy management system is feasible on practical IoT devices and reduces the overall cost by 25%.Comment: To appea

On the Role of Age of Information in the Internet of Things

In this article, we provide an accessible introduction to the emerging idea of Age of Information (AoI) that quantifies freshness of information and explore its possible role in the efficient design of freshness-aware Internet of Things (IoT). We start by summarizing the concept of AoI and its variants with emphasis on the differences between AoI and other well-known performance metrics in the literature, such as throughput and delay. Building on this, we explore freshness-aware IoT design for a network in which IoT devices sense potentially different physical processes and are supposed to frequently update the status of these processes at a destination node (such as a cellular base station). Inspired by the recent interest, we also assume that these IoT devices are powered by wireless energy transfer by the destination node. For this setting, we investigate the optimal sampling policy that jointly optimizes wireless energy transfer and scheduling of update packet transmissions from IoT devices with the goal of minimizing long-term weighted sum-AoI. Using this, we characterize the achievable AoI region. We also compare this AoI-optimal policy with the one that maximizes average throughput (throughput-optimal policy), and demonstrate the impact of system state on their structures. Several promising directions for future research are also presented.Comment: To appear in IEEE Communications Magazin

Designing Flexible, Energy Efficient and Secure Wireless Solutions for the Internet of Things

The Internet of Things (IoT) is an emerging concept where ubiquitous physical objects (things) consisting of sensor, transceiver, processing hardware and software are interconnected via the Internet. The information collected by individual IoT nodes is shared among other often heterogeneous devices and over the Internet. This dissertation presents flexible, energy efficient and secure wireless solutions in the IoT application domain. System design and architecture designs are discussed envisioning a near-future world where wireless communication among heterogeneous IoT devices are seamlessly enabled. Firstly, an energy-autonomous wireless communication system for ultra-small, ultra-low power IoT platforms is presented. To achieve orders of magnitude energy efficiency improvement, a comprehensive system-level framework that jointly optimizes various system parameters is developed. A new synchronization protocol and modulation schemes are specified for energy-scarce ultra-small IoT nodes. The dynamic link adaptation is proposed to guarantee the ultra-small node to always operate in the most energy efficiency mode, given an operating scenario. The outcome is a truly energy-optimized wireless communication system to enable various new applications such as implanted smart-dust devices. Secondly, a configurable Software Defined Radio (SDR) baseband processor is designed and shown to be an efficient platform on which to execute several IoT wireless standards. It is a custom SIMD execution model coupled with a scalar unit and several architectural optimizations: streaming registers, variable bitwidth, dedicated ALUs, and an optimized reduction network. Voltage scaling and clock gating are employed to further reduce the power, with a more than a 100% time margin reserved for reliable operation in the near-threshold region. Two upper bound systems are evaluated. A comprehensive power/area estimation indicates that the overhead of realizing SDR flexibility is insignificant. The benefit of baseband SDR is quantified and evaluated. To further augment the benefits of a flexible baseband solution and to address the security issue of IoT connectivity, a light-weight Galois Field (GF) processor is proposed. This processor enables both energy-efficient block coding and symmetric/asymmetric cryptography kernel processing for a wide range of GF sizes (2^m, m = 2, 3, ..., 233) and arbitrary irreducible polynomials. Program directed connections among primitive GF arithmetic units enable dynamically configured parallelism to efficiently perform either four-way SIMD GF operations, including multiplicative inverse, or a long bit-width GF product in a single cycle. This demonstrates the feasibility of a unified architecture to enable error correction coding flexibility and secure wireless communication in the low power IoT domain.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137164/1/yajchen_1.pd