An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a System-on-Chip based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with secured remote recognition in 5.74pJ/op; and seizure detection with encrypted data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE Transactions on Circuits and Systems - I: Regular Paper

Optimizing Embedded Software of Self-Powered IoT Edge Devices for Transient Computing

IoT edge computing becomes increasingly popular as it can mitigate the burden of cloud servers significantly by offloading tasks from the cloud to the edge which contains the majority of IoT devices. Currently, there are trillions of edge devices all over the world, and this number keeps increasing. A vast amount of edge devices work under power-constrained scenarios such as for outdoor environmental monitoring. Considering the cost and sustainability, in the long run, self-powering through energy harvesting technology is preferred for these IoT edge devices. Nevertheless, a common and critical drawback of self-powered IoT edge devices is that their runtime states in volatile memory such as SRAM will be lost during the power outage. Thanks to the state-of-the-art non-volatile processor (NVP), the runtime volatile states can be saved into the on-chip non-volatile memory before the power outage and recovered when harvesting power becomes available. Yet the potential of a self-powered IoT edge device is still hindered by the intrinsic low energy efficiency and reliability. In order to fully exert the potentials of existing self-powered IoT edge devices, this dissertation aims at optimizing the energy efficiency and reliability of self-powered IoT edge devices through several software approaches. First, to prevent execution progress loss during the power outage, NVP-aware task schedulers are proposed to maximize the overall task execution progress especially for the atomic tasks of which the unfinished progress is subjected to loss regardless of having been checkpointed. Second, to minimize both the time and energy overheads of checkpointing operations on non-volatile memory, an intelligent checkpointing scheme is proposed which can not only ensure a successful checkpointing but also predict the necessity of conducting checkpointing to avoid excessive checkpointing overhead. Third, to avoid inappropriate runtime CPU clock frequency with low energy utility, a CPU frequency modulator is proposed which adjusts the runtime CPU clock frequency adaptively. Finally, to thrive in ultra-low harvesting power scenarios, a light-weight software paradigm is proposed to help maximize the energy extraction rate of the energy harvester and power regulator bundle. Besides, checkpointing is also optimized for more energy-efficient and light-weight operation

Emerging embedded nonvolatile memory solution for ultra low power microcontroller systems

13301甲第4810号博士（工学）金沢大学博士論文本文Full 以下に掲載および掲載予定：1.IEEE Journal of Solid-State Circuits 27(4) pp.569-573 1992. IEEE. 共著者：M. Hayashikoshi, H. Hidaka, K. Arimoto, K. Fujishima 2.IEEE Transactions on Multi-Scale Computing Systems IEEE. 共著者：M. Hayashikoshi, H. Noda, H. Kawai, Y. Murai, S. Otani, K. Nii, Y. Matsuda, H. Kond

Home Security and Monitoring System

Práce se zabývá implementací bezdrátového bezpečnostního systému rodinného domu. Bezdrátová komunikace je realizována rádii na bázi standardu IEEE 802.15.4, konkrétně využívá komunikační protokol ZigBee. Na začátku práce je sepsána specifikace systému, následuje rozbor technologií pro získávání energie z prostředí a přehled současné nabídky tzv. single board computer řešení, s elaborací jejich vhodnosti pro realizaci řídícího uzlu senzorové sítě. Dále pak práce popisuje samotný proces návrhu, implementace a testování jednotlivých komponent bezpečnostního systému. V závěru jsou zhodnoceny dosažené výsledky a navržena možná vylepšení stávající implementace. Výstupem práce jsou vyhotovená bezdrátové zařízení implementující senzory, řídicí jednotka senzorové sítě a implementace grafického uživatelského rozhraní pro její správu.The thesis elaborates on an implementation of wireless home security system. The wireless communication utilizes IEEE 802.15.4 radios and ZigBee communication protocol. The beginning of the thesis provides specification of the intended system followed by an evaluation of usable energy harvesting solutions and later by consideration of single board computer systems suitable for implementation of the control node of the sensor network. The rest of the thesis describes design, implementation and testing of particular components of the security system. Conclusion evaluates the achieved goals and offers suggestions for future work. The end products of the thesis are physical devices implementing wireless sensor nodes, control unit of the security system as well as a graphical user interface for the system management.

A Heterogeneous System Architecture for Low-Power Wireless Sensor Nodes in Compute-Intensive Distributed Applications

Wireless Sensor Networks (WSNs) combine embedded sensing and processing capabilities with a wireless communication infrastructure, thus supporting distributed monitoring applications. WSNs have been investigated for more than three decades, and recent social and industrial developments such as home automation, or the Internet of Things, have increased the commercial relevance of this key technology. The communication bandwidth of the sensor nodes is limited by the transportation media and the restricted energy budget of the nodes. To still keep up with the ever increasing sensor count and sampling rates, the basic data acquisition and collection capabilities of WSNs have been extended with decentralized smart feature extraction and data aggregation algorithms. Energy-efficient processing elements are thus required to meet the ever-growing compute demands of the WSN motes within the available energy budget. The Hardware-Accelerated Low Power Mote (HaLoMote) is proposed and evaluated in this thesis to address the requirements of compute-intensive WSN applications. It is a heterogeneous system architecture, that combines a Field Programmable Gate Array (FPGA) for hardware-accelerated data aggregation with an IEEE 802.15.4 based Radio Frequency System-on-Chip for the network management and the top-level control of the applications. To properly support Dynamic Power Management (DPM) on the HaLoMote, a Microsemi IGLOO FPGA with a non-volatile configuration storage was chosen for a prototype implementation, called Hardware-Accelerated Low Energy Wireless Embedded Sensor Node (HaLOEWEn). As for every multi-processor architecture, the inter-processor communication and coordination strongly influences the efficiency of the HaLoMote. Therefore, a generic communication framework is proposed in this thesis. It is tightly coupled with the DPM strategy of the HaLoMote, that supports fast transitions between active and idle modes. Low-power sleep periods can thus be scheduled within every sampling cycle, even for sampling rates of hundreds of hertz. In addition to the development of the heterogeneous system architecture, this thesis focuses on the energy consumption trade-off between wireless data transmission and in-sensor data aggregation. The HaLOEWEn is compared with typical software processors in terms of runtime and energy efficiency in the context of three monitoring applications. The building blocks of these applications comprise hardware-accelerated digital signal processing primitives, lossless data compression, a precise wireless time synchronization protocol, and a transceiver scheduling for contention free information flooding from multiple sources to all network nodes. Most of these concepts are applicable to similar distributed monitoring applications with in-sensor data aggregation. A Structural Health Monitoring (SHM) application is used for the system level evaluation of the HaLoMote concept. The Random Decrement Technique (RDT) is a particular SHM data aggregation algorithm, which determines the free-decay response of the monitored structure for subsequent modal identification. The hardware-accelerated RDT executed on a HaLOEWEn mote requires only 43 % of the energy that a recent ARM Cortex-M based microcontroller consumes for this algorithm. The functionality of the overall WSN-based SHM system is shown with a laboratory-scale demonstrator. Compared to reference data acquired by a wire-bound laboratory measurement system, the HaLOEWEn network can capture the structural information relevant for the SHM application with less than 1 % deviation

Sistemas de deteção por infravermelhos de muito baixo consumo

Engenharia Eletrónica e TelecomunicaçõesA e ciência energética e cada vez mais uma preocupação de engenheiros e da população em geral. Em sistemas alimentados a baterias, esta preocupação torna-se mais evidente quando as pessoas interagem com estes diariamente. É então frustrante quando a uma bateria descarregada impossibilita a utilização destes sistemas. Um caso particular de sistemas que muitas vezes são alimentados por baterias são as torneiras automáticas. Estes sistemas necessitam de constante manutenção, quer devido a descarga das baterias, quer devido a falhas na deteção de presença. O princípio de funcionamento destes sistemas baseia-se essencialmente numa deteção por infravermelhos com recurso a um pequeno circuito de ativação de uma electro-válvula. Nesta dissertação foi proposta uma implementação semelhante com algumas alterações. Utilizaram-se técnicas de baixo consumo, algoritmos de deteção por infravermelhos e ainda recolha de energia para aumentar a duração da bateria. Ao usar um microcontrolador para executar as tarefas requeridas, foi adicionada ao sistema alguma inteligência. Foi ainda estudada a possibilidade de tornar o sistema completamente autónomo em termos de geração e consumo de energia. Embora a auto-su ciência não tenha sido alcançada, foram obtidos resultados importantes que poderão contribuir para melhorar o desempenho dos sistemas deste género.Energy consumption is one of the major concerns amongst engineers and general population. In battery powered systems, when people interact with them in a daily basis, this concern is even more evident. It is frustrating when a depleted battery makes impossible its normal use. A particular case of a battery powered system is the automatic faucet. These need constant maintenance to replace dead batteries and even due to failures in presence detection. The working principle of these systems is essentially based in an infrared detection followed by a activation circuit of an electro-valve. In this dissertation a similar, with some changes, implementation was proposed. The use low-power techniques, infrared detection algorithms and energy harvesting to increase battery duration. By using a microcontroller to perform the required operations, some intelligence was given to the system. It was also veri ed the possibility to make the system self sustainable in therms of energy consumption and harvesting. Although self-sustainability was not achieved, several important results were obtained which can contribute to improve the performance of similar systems

Cost effective technology applied to domotics and smart home energy management systems

Premio extraordinario de Trabajo Fin de Máster curso 2019/2020. Máster en Energías Renovables DistribuidasIn this document is presented the state of art for domotics cost effective technologies available on market nowadays, and how to apply them in Smart Home Energy Management Systems (SHEMS) allowing peaks shaving, renewable management and home appliance controls, always in cost effective context in order to be massively applied. Additionally, beyond of SHEMS context, it will be also analysed how to apply this technology in order to increase homes energy efficiency and monitoring of home appliances. Energy management is one of the milestones for distributed renewable energy spread; since renewable energy sources are not time-schedulable, are required control systems capable of the management for exchanging energy between conventional sources (power grid), renewable sources and energy storage sources. With the proposed approach, there is a first block dedicated to show an overview of Smart Home Energy Management Systems (SMHEMS) classical architecture and functional modules of SHEMS; next step is to analyse principles which has allowed some devices to become a cost-effective technology. Once the technology has been analysed, it will be reviewed some specific resources (hardware and software) available on marked for allowing low cost SHEMS. Knowing the “tools” available; it will be shown how to adapt classical SHEMS to cost effective technology. Such way, this document will show some specific applications of SHEMS. Firstly, in a general point of view, comparing the proposed low-cost technology with one of the main existing commercial proposals; and secondly, developing the solution for a specific real case.En este documento se aborda el estado actual de la domótica de bajo coste disponible en el mercado actualmente y cómo aplicarlo en los sistemas inteligentes de gestión energética en la vivienda (SHEMS) permitiendo el recorte de las puntas de demanda, gestión de energías renovables y control de electrodomésticos, siempre en el contexto del bajo coste, con el objetivo de lograr la máxima difusión de los SHEMS. Adicionalmente, más allá del contexto de la tecnología SHEMS, se analizará cómo aplicar esta tecnología para aumentar la eficiencia energética de los hogares y para la supervisión de los electrodomésticos. La gestión energética es uno de los factores principales para lograr la difusión de las energías renovables distribuidas; debido a que las fuentes de energía renovable no pueden ser planificadas, se requieren sistemas de control capaces de gestionar el intercambio de energía entre las fuentes convencionales (red eléctrica de distribución), energías renovables y dispositivos de almacenamiento energético. Bajo esta perspectiva, este documento presenta un primer bloque en el que se exponen las bases de la arquitectura y módulos funcionales de los sistemas inteligentes de gestión energética en la vivienda (SHEMS); el siguiente paso será analizar los principios que han permitido a ciertos dispositivos convertirse en dispositivos de bajo coste. Una vez analizada la tecnología, nos centraremos en los recursos (hardware y software) existentes que permitirán la realización de un SHEMS a bajo coste. Conocidas las “herramientas” a nuestra disposición, se mostrará como adaptar un esquema SHEMS clásico a la tecnología de bajo coste. Primeramente, comparando de modo genérico la tecnología de bajo coste con una de las principales propuestas comerciales de SHEMS, para seguidamente desarrollar la solución de bajo coste a un caso específico real

Flexi-WVSNP-DASH: A Wireless Video Sensor Network Platform for the Internet of Things

abstract: Video capture, storage, and distribution in wireless video sensor networks (WVSNs) critically depends on the resources of the nodes forming the sensor networks. In the era of big data, Internet of Things (IoT), and distributed demand and solutions, there is a need for multi-dimensional data to be part of the Sensor Network data that is easily accessible and consumable by humanity as well as machinery. Images and video are expected to become as ubiquitous as is the scalar data in traditional sensor networks. The inception of video-streaming over the Internet, heralded a relentless research for effective ways of distributing video in a scalable and cost effective way. There has been novel implementation attempts across several network layers. Due to the inherent complications of backward compatibility and need for standardization across network layers, there has been a refocused attention to address most of the video distribution over the application layer. As a result, a few video streaming solutions over the Hypertext Transfer Protocol (HTTP) have been proposed. Most notable are Apple’s HTTP Live Streaming (HLS) and the Motion Picture Experts Groups Dynamic Adaptive Streaming over HTTP (MPEG-DASH). These frameworks, do not address the typical and future WVSN use cases. A highly flexible Wireless Video Sensor Network Platform and compatible DASH (WVSNP-DASH) are introduced. The platform's goal is to usher video as a data element that can be integrated into traditional and non-Internet networks. A low cost, scalable node is built from the ground up to be fully compatible with the Internet of Things Machine to Machine (M2M) concept, as well as the ability to be easily re-targeted to new applications in a short time. Flexi-WVSNP design includes a multi-radio node, a middle-ware for sensor operation and communication, a cross platform client facing data retriever/player framework, scalable security as well as a cohesive but decoupled hardware and software design.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201