Securing Iot: Hardware Vs Software
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Monitoring Dan Kontrol Sistem Irigasi Berbasis Iot Menggunakan Banana Pi
JURNAL TEKNIK ITS Vol. 7, No. 2, (2018) ISSN: 2337-3539 (2301-9271 Print) A288 Monitoring dan Kontrol Sistem Irigasi Berbasis IoT Menggunakan Banana Pi Andrie Wijaya, dan Muhammad Rivai Departemen Teknik Elektro, Fakultas Teknologi Elektro, Institut Teknologi Sepuluh Nopember (ITS) e-mail: [email protected] Abstrak— Saat ini metode pengaliran air atau irigasi dilakukan memperhatikan kondisi kelembaban tanah juga mengakibatkan secara manual. Petani harus menyiram tanaman satu persatu penggunaan air yang tidak tepat. Penggunaan air yang sehingga tidak efisien dalam hal energi, waktu, dan ketersediaan berlebihan akan mempengaruhi ketersediaan sumber air yang air sehingga dapat menurukan hasil panen. Internet of Things semakin menurun. merupakan konsep dan metode untuk kontrol jarak jauh, Tugas akhir ini bertujuan untuk menciptakan sistem monitoring, pengiriman data, dan berbagai tugas lainnya. IoT terhubung dengan suatu jaringan sehingga dapat di akses di irigasi berbasis internet of things [2][3], dan [4]. Pada sistem mana saja yang dapat mempermudah berbagai hal. IoT dapat ini petani dapat memonitoring kondisi kelembaban tanah dan dimanfaatkan di berbagai bidang, salah satunya adalah bidang mengkontrol debit air yang akan disiram pada tanaman pertanian. Pada bidang ini IoT dapat digunakan untuk memantau Sehingga meningkatkan hasil panen dan mengoptimalkan dan mengatur berbagai hal untuk menunjang pertanian. Pada penggunaan air. penelitian ini akan dibuat suatu peralatan yang digunakan untuk Sistem ini menggunakan sensor kelembaban tanah atau monitoring dan kontrol sistem irigasi berbasis IOT. Single Board higrometer [5][6]yang akan di proses di Single Board Computer Banana Pi digunakan sebagai prosesor utama yang Computer (SBC) Banana Pi [7]. SBC yang terhubung dengan terhubung dengan jaringan internet yang mengirim data dari sensor ke pengguna. -
User Manual - S.USV Solutions Compatible with Raspberry Pi, up Board and Tinker Board Revision 2.2 | Date 07.06.2018
User Manual - S.USV solutions Compatible with Raspberry Pi, UP Board and Tinker Board Revision 2.2 | Date 07.06.2018 User Manual - S.USV solutions / Revision 2.0 Table of Contents 1 Functions .............................................................................................................................................. 3 2 Technical Specification ........................................................................................................................ 4 2.1 Overview ....................................................................................................................................... 5 2.2 Performance .................................................................................................................................. 6 2.3 Lighting Indicators ......................................................................................................................... 6 3 Installation Guide................................................................................................................................. 7 3.1 Hardware ...................................................................................................................................... 7 3.1.1 Commissioning S.USV ............................................................................................................ 7 3.1.2 Connecting the battery .......................................................................................................... 8 3.1.3 Connecting the external power supply ................................................................................. -
Building a Distribution: Openharmony and Openmandriva
Two different approaches to building a distribution: OpenHarmony and OpenMandriva Bernhard "bero" Rosenkränzer <[email protected]> FOSDEM 2021 -- February 6, 2021 1 MY CONTACT: [email protected], [email protected] Way more important than that, he also feeds LINKEDIN: dogs. https://www.linkedin.com/in/berolinux/ Bernhard "bero" Rosenkränzer I don't usually do "About Me", but since it may be relevant to the topic: Principal Technologist at Open Source Technology Center since November 2020 President of the OpenMandriva Association, Contributor since 2012 - also a contributor to Mandrake back in 1998/1999 2 What is OpenHarmony? ● More than an operating system: Can use multiple different kernels (Linux, Zephyr, ...) ● Key goal: autonomous, cooperative devices -- multiple devices form a distributed virtual bus and can share resources ● Initial target devices: Avenger 96 (32-bit ARMv7 Cortex-A7+-M4), Nitrogen 96 (Cortex-M4) ● Built with OpenEmbedded/Yocto - one command builds the entire OS ● Fully open, developed as an Open Source project instead of an inhouse product from the start. ● For more information, visit Stefan Schmidt's talk in the Embedded devroom, 17.30 and/or talk to us at the Huawei OSTC stand. 3 What is OpenMandriva? ● A more traditional Linux distribution - controlled by the community, continuing where Mandriva left off after the company behind it went out of business in 2012. Its roots go back to the first Mandrake Linux release in 1998. ● Originally targeting only x86 PCs - Support for additional architectures (aarch64, armv7hnl, RISC-V) added later ● Repositiories contain 17618 packages, built and updated individually, assembled into an installable product with omdv-build-iso or os-image-builder. -
A Highly Modular Router Microarchitecture for Networks-On-Chip
A Highly Modular Router Microarchitecture for Networks-on-Chip Item Type text; Electronic Dissertation Authors Wu, Wo-Tak Publisher The University of Arizona. Rights Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author. Download date 01/10/2021 08:12:16 Link to Item http://hdl.handle.net/10150/631277 A HIGHLY MODULAR ROUTER MICROARCHITECTURE FOR NETWORKS-ON-CHIP by Wo-Tak Wu Copyright c Wo-Tak Wu 2019 A Dissertation Submitted to the Faculty of the DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY In the Graduate College THE UNIVERSITY OF ARIZONA 2019 THE UNIVERSITY OF ARIZONA GRADUATE COLLEGE As members of the Dissertation Committee, we certify that we have read the dissertation prepared by Wo-Tak Wu, titled A HIGHLY MODULAR ROUTER MICROARCHITECTURE FOR NETWORKS-ON-CHIP and recommend that it be accepted as fulfilling the dissertation requirement for the Degree of Doctor of Philosophy. Dr. Linda Powers --~-__:::::____ ---?---- _________ Date: August 7, 2018 Dr. Roman Lysecky Final approval and acceptance of this dissertation is contingent upon the candidate's submission of the final copies of the dissertation to the Graduate College. I hereby certify that I have read this dissertation prepared under my direction and recommend that it be accepted as fulfilling the dissertation requirement. _____(/2 __·...... ~"--------\;-~=--------- · __ Date: August 7, 2018 Dissertation Director: Dr. -
Jumpstarting the Onion Omega2
Jumpstarting the Onion Omega2 An Introduction to a New Low-Cost Internet of Things Computer WOLFRAM DONAT JUMPSTARTING the Onion Omega2 AN INTRODUCTION TO A NEW LOW-COST INTERNET OF THINGS COMPUTER Wolfram Donat Maker Media, Inc. San Francisco Copyright © 2018 Wolfram Donat. All rights reserved. Published by Maker Media, Inc. 1700 Montgomery Street, Suite 240 San Francisco, CA 94111 Maker Media books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (safari- booksonline.com). For more information, contact our corporate/institutional sales department: 800-998-9938 or [email protected]. Editorial Director: Roger Stewart Editor: Patrick DiJusto Copy Editor: Elizabeth Welch, Happenstance Type-O-Rama Proofreader: Scout Festa, Happenstance Type-O-Rama Cover and Interior Designer: Maureen Forys, Happenstance Type-O-Rama All the circuit and component diagrams in this book are created using Fritz- ing (http://fritzing.org/home). June 2018: First Edition Revision History for the First Edition 2018-06-18 First Release See oreilly.com/catalog/errata.csp?isbn=9781680455229 for release details. Make:, Maker Shed, and Maker Faire are registered trademarks of Maker Media, Inc. The Maker Media logo is a trademark of Maker Media, Inc. Jumpstarting the Onion Omega2 and related trade dress are trademarks of Maker Media, Inc. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and Maker Media, Inc. was aware of a trademark claim, the designations have been printed in caps or initial caps. While the publisher and the author have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the author disclaim all responsibility for errors or omis- sions, including without limitation responsibility for damages resulting from the use of or reliance on this work. -
DM3730, DM3725 Digital Media Processors Datasheet (Rev. D)
DM3730, DM3725 www.ti.com SPRS685D–AUGUST 2010–REVISED JULY 2011 DM3730, DM3725 Digital Media Processors Check for Samples: DM3730, DM3725 1 DM3730, DM3725 Digital Media Processors 1.1 Features 123456 • DM3730/25 Digital Media Processors: • Load-Store Architecture With – Compatible with OMAP™ 3 Architecture Non-Aligned Support – ARM® Microprocessor (MPU) Subsystem • 64 32-Bit General-Purpose Registers • Up to 1-GHz ARM® Cortex™-A8 Core • Instruction Packing Reduces Code Size Also supports 300, 600, and 800-MHz • All Instructions Conditional operation • Additional C64x+TM Enhancements • NEON™ SIMD Coprocessor – Protected Mode Operation – High Performance Image, Video, Audio – Expectations Support for Error (IVA2.2TM) Accelerator Subsystem Detection and Program Redirection • Up to 800-MHz TMS320C64x+TM DSP Core – Hardware Support for Modulo Loop Also supports 260, 520, and 660-MHz Operation operation – C64x+TM L1/L2 Memory Architecture • Enhanced Direct Memory Access (EDMA) • 32K-Byte L1P Program RAM/Cache Controller (128 Independent Channels) (Direct Mapped) • Video Hardware Accelerators • 80K-Byte L1D Data RAM/Cache (2-Way – POWERVR SGX™ Graphics Accelerator Set- Associative) (DM3730 only) • 64K-Byte L2 Unified Mapped RAM/Cache • Tile Based Architecture Delivering up to (4- Way Set-Associative) 20 MPoly/sec • 32K-Byte L2 Shared SRAM and 16K-Byte • Universal Scalable Shader Engine: L2 ROM Multi-threaded Engine Incorporating Pixel – C64x+TM Instruction Set Features and Vertex Shader Functionality • Byte-Addressable (8-/16-/32-/64-Bit Data) -
A Low-Cost Deep Neural Network-Based Autonomous Car
DeepPicar: A Low-cost Deep Neural Network-based Autonomous Car Michael G. Bechtely, Elise McEllhineyy, Minje Kim?, Heechul Yuny y University of Kansas, USA. fmbechtel, elisemmc, [email protected] ? Indiana University, USA. [email protected] Abstract—We present DeepPicar, a low-cost deep neural net- task may be directly linked to the safety of the vehicle. This work based autonomous car platform. DeepPicar is a small scale requires a high computing capacity as well as the means to replication of a real self-driving car called DAVE-2 by NVIDIA. guaranteeing the timings. On the other hand, the computing DAVE-2 uses a deep convolutional neural network (CNN), which takes images from a front-facing camera as input and produces hardware platform must also satisfy cost, size, weight, and car steering angles as output. DeepPicar uses the same net- power constraints, which require a highly efficient computing work architecture—9 layers, 27 million connections and 250K platform. These two conflicting requirements complicate the parameters—and can drive itself in real-time using a web camera platform selection process as observed in [25]. and a Raspberry Pi 3 quad-core platform. Using DeepPicar, we To understand what kind of computing hardware is needed analyze the Pi 3’s computing capabilities to support end-to-end deep learning based real-time control of autonomous vehicles. for AI workloads, we need a testbed and realistic workloads. We also systematically compare other contemporary embedded While using a real car-based testbed would be most ideal, it computing platforms using the DeepPicar’s CNN-based real-time is not only highly expensive, but also poses serious safety control workload. -
D I E B Ü C H S E D E R P a N D O R a Seite 1
D i e B ü c h s e d e r P a n d o r a Infos zur griechischen Mythologie siehe: http://de.wikipedia.org/wiki/B%C3%BCchse_der_Pandora ______________________________________________________________________________________________________________________________________________________ „Das Öffnen der Büchse ist absolute Pflicht, um die Hoffnung in die Welt zu lassen!“ Nachdruck und/oder Vervielfältigungen, dieser Dokumentation ist ausdrücklich gestattet. Quellenangabe: Der Tux mit dem Notebook stammt von der Webseite: http://www.openclipart.org/detail/60343 1. Auflage , © 9-2012 by Dieter Broichhagen | Humboldtstraße 106 | 51145 Köln. e-Mail: [email protected] | Web: http://www.broichhagen.de | http://www.illugen-collasionen.com Satz, Layout, Abbildungen (wenn nichts anderes angegeben ist): Dieter Broichhagen Alle Rechte dieser Beschreibung liegen beim Autor Gesamtherstellung: Dieter Broichhagen Irrtum und Änderungen vorbehalten! Seite 1 - 12 D i e B ü c h s e d e r P a n d o r a Infos zur griechischen Mythologie siehe: http://de.wikipedia.org/wiki/B%C3%BCchse_der_Pandora ______________________________________________________________________________________________________________________________________________________ Hinweis: Weitere Abbildungen von meiner „Büchse der Pandora“ finden Sie unter http://broichhagen.bplaced.net/ilco3/images/Pandora-X1.pdf Bezeichnungen • SheevaPlug ist kein Katzenfutter und kein Ausschlag • DreamPlug ist kein Auslöser für Alpträume • Raspberry Pi ist kein Himbeer-Kuchen • Pandaboard ist kein Servbrett für Pandabären • Die „Büchse der Pandora“ ist keine Legende Was haben SheevaPlug, DreamPlug, Raspberry Pi und Pandaboard gemeinsam? Sie haben einen ARM und sind allesamt Minicomputer. Wer einen ARM hat, ist nicht arm dran. Spaß bei Seite oder vielmehr, jetzt geht der Spaß erst richtig los. Am Anfang war der ... SheevaPlug Das Interesse wurde durch Matthias Fröhlich geweckt, der einen SheevaPlug- Minicomputer vor 2 Jahren im Linux- Workshop vorstellte. -
Building a Datacenter with ARM Devices
Building a Datacenter with ARM Devices Taylor Chien1 1SUNY Polytechnic Institute ABSTRACT METHODS THE CASE CURRENT RESULTS The ARM CPU is becoming more prevalent as devices are shrinking and Physical Custom Enclosure Operating Systems become embedded in everything from medical devices to toasters. Build a fully operational environment out of commodity ARM devices using Designed in QCAD and laser cut on hardboard by Ponoko Multiple issues exist with both Armbian and Raspbian, including four However, Linux for ARM is still in the very early stages of release, with SBCs, Development Boards, or other ARM-based systems Design was originally only for the Raspberry Pis, Orange Pi Ones, Udoo critical issues that would prevent them from being used in a datacenter many different issues, challenges, and shortcomings. Have dedicated hard drives and power system for mass storage, including Quads, PINE64, and Cubieboard 3 multiple drives for GlusterFS operation, and an Archive disk for backups and Issue OS In order to test what level of service commodity ARM devices have, I Each device sits on a tray which can be slid in and out at will rarely-used storage Kernel and uboot are not linked together after a Armbian decided to build a small data center with these devices. This included Cable management and cooling are on the back for easy access Build a case for all of these devices that will protect them from short circuits version update building services usually found in large businesses, such as LDAP, DNS, Designed to be solid and not collapse under its own weight and dust Operating system always performs DHCP request Raspbian Mail, and certain web applications such as Roundcube webmail, Have devices hooked up to a UPS for power safety Design Flaws Allwinner CPUs crash randomly when under high Armbian ownCloud storage, and Drupal content management. -
End-To-End Learning for Autonomous Driving Robots
End-to-End Learning for Autonomous Driving Robots Anthony Ryan 21713293 Supervisor: Professor Thomas Bräunl GENG5511/GENG5512 Engineering Research Project Submitted: 25th May 2020 Word Count: 8078 Faculty of Engineering and Mathematical Sciences School of Electrical, Electronic and Computer Engineering 1 Abstract This thesis presents the development of a high-speed, low cost, end-to-end deep learning based autonomous robot driving system called ModelCar-2. This project builds on a previous project undertaken at the University of Western Australia called ModelCar, where a robotics driving system was first developed with a single LIDAR scanner as its only sensory input as a baseline for future research into autonomous vehicle capabilities with lower cost sensors. ModelCar-2 is comprised of a Traxxas Stampede RC Car, Wide-Angle Camera, Raspberry Pi 4 running UWA’s RoBIOS software and a Hokuyo URG-04LX LIDAR Scanner. ModelCar-2 aims to demonstrate how the cost of producing autonomous driving robots can be reduced by replacing expensive sensors such as LIDAR with digital cameras and combining them with end-to-end deep learning methods and Convolutional Neural Networks to achieve the same level of autonomy and performance. ModelCar-2 is a small-scale application of PilotNet, developed by NVIDIA and used in the DAVE-2 system. ModelCar-2 uses TensorFlow and Keras to recreate the same neural network architecture as PilotNet which features 9 layers, 27,000,000 connections and 252,230 parameters. The Convolutional Neural Network was trained to map the raw pixels from images taken with a single inexpensive front-facing camera to predict the speed and steering angle commands to control the servo and drive the robot. -
Ten (Or So) Small Computers
Ten (or so) Small Computers by Jon "maddog" Hall Executive Director Linux International and President, Project Cauã 1 of 50 Copyright Linux International 2015 Who Am I? • Half Electrical Engineer, Half Business, Half Computer Software • In the computer industry since 1969 – Mainframes 5 years – Unix since 1980 – Linux since 1994 • Companies (mostly large): Aetna Life and Casualty, Bell Labs, Digital Equipment Corporation, SGI, IBM, Linaro • Programmer, Systems Administrator, Systems Engineer, Product Manager, Technical Marketing Manager, University Educator, Author, Businessperson, Consultant • Taught OS design and compiler design • Extremely large systems to extremely small ones • Pragmatic • Vendor and a customer Warnings: • This is an overview guide! • Study specifications of each processor at manufacturer's site to make sure it meets your needs • Prices not normally listed because they are all over the map...shop wisely Definitions • Microcontroller vs Microprocessor • CPU vs “Core” • System On a Chip (SoC) • Hard vs Soft Realtime • GPIO Pins – Digital – Analog • Printed Circuit Board (PCB) • Shield, Cape, etc. • Breadboard – Patch cables Definitions (Cont.) • Disks – IDE – SATA – e-SATA • Graphical Processing Unit (GPU) • Field Programmable Gate Array (FPGA) • Digital Signal Processing Chips (DSP) • Unless otherwise specified, all microprocessors are ARM-32 bit Still More Definitions! • Circuit Diagrams • Surface Mount Technology – large robots – Through board holes in PCBs – Surface mount • CAD Files – PCB layout – “Gerbers” for -
FD-V15N3.Pdf
SILICON COMPOSERS INC FAST Forth Native-Language Embedded Computers DUP >R R> Harris RTX 2000"" l&bit Forth Chip SC32"" 32-bit Forth Microprocessor 08 or 10 MHz operation and 15 MIPS speed. 08 or 10 MHz operation and 15 MIPS speed. 1-cycle 16 x 16 = 32-bi multiply. 1-clock cycle instruction execution. 1-cycle 1&prioritized interrupts. *Contiguous 16 GB data and 2 GB code space. *two 256-word stack memories. *Stack depths limited only by available memory. -&channel 1/0 bus & 3 timer/counters. *Bus request/bus grant lines with on-chip tristate. SC/FOX PCS (Parallel Coprocessor System) SC/FOX SBC32 (Single Board Computer32) *RTX 2000 industrial PGA CPU; 8 & 10 MHz. 032-bi SC32 industrial grade Forth PGA CPU. *System speed options: 8 or 10 MHz. *System speed options: 8 or 10 MHz. -32 KB to 1 MB 0-wait-state static RAM. 42 KB to 512 KB 0-wait-state static RAM. *Full-length PC/XT/AT plug-in (&layer) board. .100mm x 160mm Eurocard size (+layer) board. SC/FOX VME SBC (Single Board Computer) SC/FOX PCS32 (Parallel Coprocessor Sys) *RTX 2000 industrial PGA CPU; 8, 10, 12 MHz. 032-bi SC32 industrial grade Forth PGA CPU. *Bus Master, System Controller, or Bus Slave. *System speed options: 8 or 10 MHz. Up to 640 KB 0-wait-state static RAM. 064 KB to 1 MB 0-wait-state static RAM. -233mm x 160mm 6U size (Slayer) board. *FulClength PC/XT/AT plug-in (Slayer) board. SC/FOX CUB (Single Board Computer) SC/FOX SBC (Single Board Computer) *RTX 2000 PLCC or 2001A PLCC chip.