AST Catania Lab STMicroelectronics
|
|
- Shannon Nicholson
- 6 years ago
- Views:
Transcription
1 AST Catania Lab STMicroelectronics Valeria Tomaselli Embedded Analytics Team June 2017
2 A global semiconductor leader 2016 revenues of $6.97B Who We Are 15% America 45% China and South Asia 13% Japan and Corea 27% EMEA (Europe, Middle East & Africa) Research & Development Main Sales & Marketing Front-End Back-End Approximately 43,500 employees worldwide Approximately 7,500 people working in R&D 11 manufacturing sites Over 75 sales & marketing offices Listed on New York Stock Exchange, Euronext Paris and Borsa Italiana, Milano
3 Devices Microelectronics: the development enabler 3 World Wide GDP: ~80.000B$ B$ SERVICES 1.700B$ 335B$ 6x ELECTRONICS 5x Semiconductor s 36B$ 38B$ Materials Equipment All trademarks and logos are the property of their respective owners. All rights reserved. They are used here only as conceptual examples Sources: IMF (International Monetary Found)/ SIA (Semiconductors Industry Association)/World Bank.org/ WSTS
4 Application Strategic Focus 4 The leading provider of products and solutions for Smart Driving and the Internet of Things Smart Things Smart Home & City Smart Industry Smart Driving
5 Application Strategic Focus 5 The leading provider of products and solutions for Smart Driving and the Internet of Things Smart Things Smart Home & City Smart Industry Smart Driving
6 Smart Things 6 Smart Things Making Every Thing Smarter A Smart Thing Understands the environment Manages data and transforms it into information Connects to the world Protects your data Is energy efficient
7 Smart Home & City 7 Smart Home & City Making Home & Cities Smarter Smart city infrastructure to improve traffic and municipal services Smart Grid Intelligent, adaptive street lighting Smart Buildings Smart City Smart Home Smart control of heating, air conditioning, appliances, locks and alarms Smart meters to connect homes to the smart grid More energy efficiency, convenience, comfort and security
8 Smart Industry 8 Smart Industry Enabling smarter, safer and more efficient factories and workplaces Smart Industry Factories that produce in a more efficient manner More flexibility and customization possibilities in the supply chain More sustainable production with less waste and less energy used Safer working environments for people Better man-machine cooperation in the work place Optimized usage of machines and tools
9 Smart Driving 9 Smart Driving Making driving Safer, Greener and more Connected Safer Having cars drive better than we can & always watching for threats Making driving safer for car occupants and other road users by actively avoiding accidents Greener Improving power and fuel efficiency, and helping minimize emissions and car maintenance Moving towards electric vehicles More Connected Enabling personalized car entertainment and connectivity Allowing vehicles to communicate with each other and the infrastructure (V2X)
10 The Catania site
11 A balanced structure % Function % Education R&D / Designers Manufacturing 25% 54% 36% 63% Univ Degree High school Product Management&Ad ministration 21% Others 1% More than 1000 R&D specialists, 690 of whom are graduates 3949 employees 2/3 of men and 1/3 of women Average age = 42 years Personnel Update Dec 2016
12 ST Catania: an integrated site Integrated Excellence Center: R&D, Design, Production, Marketing&Supply Chain Recognized Leadership in Discrete and Integrated Power Competencies in key and growing microelectronics sectors (Sensors, Health, Renewable Energy, ) Patents WW granted patents CT granted patents Catania Invention Disclosures 2015 Strong Partnerships with Universities and Research Centers ADG AMG AST FMT MDG
13 Collaborations with Universities and Research Centers University of Catania * University of Palermo University of Messina Politecnico of Torino * Scuola Superiore S.Anna, Pisa * University of Bologna University La Sapienza, Roma University of Calabria, Cosenza Politecnico of Bari University of Firenze INAF (Istituto Nazionale di Astrofisica) INFN (Istituto Nazionale di Fisica Nucleare) CNR (Consiglio Nazionale delle Ricerche) * CEA-LETI and Liten, Grenoble, France University of Tours, France CNES, Grenoble, France CERN, Geneva, Switzerland ESA, Brussels, Belgium IMEC, Brussels, Belgium Fraunhofer Institute, Germany VTT, Helsinki, Finland MIT, Boston, USA Johns Hopkins University, Baltimore, USA Arizona State University, Phoenix, USA IME, IMRE Labs of A*STAR, Singapore University of Tunis, Tunisia Waseda University, Tokyo, Japan (*) Laboratories in the Catania site
14 AST Catania
15 Investigate beyond state of the art Industrial R&D 15 Pave the way to next generation devices (3-5 years) Understand customers needs Support product divisions and customers Added value to ST products Marketing analysis Technology evolutions ST competitors positioning Execution Internal R&D Participation to funding projects Collaboration with academic communities Patents and papers.
16 AST: Advanced Systems Technology Automotive Surveillance AST IoT, Industrial and Home Automation, Smart Metering Sensors Data Fusion & Classification Low Power Digital Design Smart Sensing Low cost Advanced Driver Assistance Systems Digital Transceivers Health & Wearable Concrete Pressure Sensors Wireless charger Focused Product Portfolio
17 Optic / Image sensor Embedded Analytics: A long journey 17 Signal Processing Image Processing Computer Vision Machine Learning Robot Interaction Multiple sensors Sensors data fusion
18 Embedded Analytics Organization 18 Artificial Intelligence Video Analytics Applications & Platforms
19 Video Analytics 19
20 STV VG STV A smart platform for image KEY FEATURES ARM Cortex -R4 500 MHz Up to 2MB SRAM Up to 4MB Flash Real time image signal processing (HDR High Dynamic Range), 5Mpixel Still / Video compression (JPEG/H264) Embedded Video Analytics (Edge Extractor, Optical Flow)
21 STV991 is an enabler of very complex algorithms ST991 Applications 21 MOT = Moving Object Tracking MOT for Smart Mirror CTA = Cross Traffic Alert MOT for CTA in Automotive MOT for Drone Landing
22 Artificial Intelligence 22
23 Classical Representation paradigm 23 Traditional model of pattern recognition (since the late 50 s): Fixed engineered features (or fixed kernels) + trainable classifier; Deep knowledge of specific data domain was required. Hand-crafted Image Feature extractor Simple trainable classifier CAR Hand-crafted Audio Feature extractor Simple trainable classifier Rock Music
24 Representation paradigm changes: DCNNs : Deep Convolutional Neural Network (DCNN) wins at ImageNet challenge, with a huge gap over competitors Courtesy of Alex Krizhevsky et all, ImageNet Classification with Deep Convolutional Neural Networks Deep architecture: Features are learned; Everything becomes adaptive; No distinction between feature extractor and classifier; Big non-linear system trained from raw pixels to labels. Layer1 Layer2 LayerN End-to-end recognition system
25 Learning hierarchical representations 25 More than one stage of non-linear feature transformation Low-level feature Mid-level feature High-level feature Trainable classifier Feature visualization on convolutional net on ImageNet [Zeiler & Fergus 2013]
26 DCNN s spread 26 Convolutional Neural Network was not invented overnight; A similar architecture was already proposed by Le Cun et al. for handwriting recognition in 1998; This technology didn t widespread in the following years because of two main factors: the absence of very large data sets, which allow to reduce over-fitting problems; the lack of powerful architectures for performing intensive computations These two problems have been overcome in the recent past: ImageNet (14M images); powerful GPU s In the last years, CNNs have become ubiquitous
27 CDNN: Applications 27 Computer Vision domain: Image/video search; Image/video labeling; Image/video segmentation; object detection; object tracking, etc. Speech Recognition; Human action recognition using mobile sensors; Sensor data fusion SAME PARADIGM FOR DIFFERENT DOMAINS
28 Visual DCNN Example: AlexNet The Reference implementation of Convolutional Deep Neural Networks It discriminates 1000 ImageNet Classes with Top-5 Error Rate of 18.2% It consists of: - 5 Convolutional Layers - 3 Fully Connected Layers Courtesy of Alex Krizhevsky et all, ImageNet Classification with Deep Convolutional Neural Networks Original Memory Requirements: 217MB
29 Orlando Accelerating Deep Learning in Embedded Systems A configurable, scalable and design time parametric Convolutional Neural Network Processing Engine 8 Dual DSP Clusters with Instruction, Data & Shared Memory Image & DCNN Co- Processor Subsystem Orlando SoC Global Memory Subsystem ARM Corte x M4 CDNN Convolutional Layers accounts for more than 90% CDNN operations, hence 8 Convolution HW Accelerators allow high efficiency in area vs GOPS vs power consumption In addition to ARM Cortex M4, 8 DSP Clusters allow both programmability and flexible mapping of diversified, custom CDNN s Embedded Memory enable further reduction of power consumption required by IOT applications.
30 COPROCESSORS SUBSYSTEM Orlando Test Chip OTP High Speed Camer a IF PLL CHIP TO CHIP M4 (DSP) CORES AND LOCAL MEMS GLOBAL MEMORY SUBSYSTEM Technology FD-SOI 28nm Die Size (X) um (Y) um Package FBGA 15x15x1.83 Clock freq 200MHz 1.175GHz Supply voltages 0.575V 1.1V digital 1.8V I/O 4x1 MB (Global) On-chip RAM 8x192 KB (DSP) 128 KB (Host) Host ARM Cortex M4 DSPs Nr 16 Peak DSP performance (1.175GHz, 1.1V) 75 GOPS (dual 16b MAC loop) Convolutional Accelerators Nr 8 CA size (including local memory) 0.27 sqmm Max Tot CAs performance (1.175GHz, 1.1V) 676 GOPS Tot. CAs Power 0.575V (Alexnet) 41mW CAs Peak 0.575V (Alexnet) 2.9 TOPS/W (*) 1 MAC defined as 2 OPS (ADD + MUL)
31 Orlando CDNN Programming Flow 1. DCNN TRAINING 2. ORLANDO-READY DCNN CONVERSION 3. ORLANDO CONFIGURATION Training Data Base DCNN configuration s Caffe Open source deep learning frameworks DCNN Weights + Metadata Orlando Configuration Tool Model2Platform DCNN Orlando-Ready Weights AUTOMATED Test/validation image dataset Fixed point analysis Optimal fixed point precision assignment (layer-wise) Weights compression Weights layout transformation PLANNED FOR AUTOMATION Network Description to Network Topology Memory management, buffer placement DMA descriptor chains generation Optimal mapping and scheduling of network execution on HW accelerator and DSP cluster.
32 CES AlexNet classifies up to 1000 different objects categories
33 CES Expression recognition is a complex task, as every person displays emotions very differently: there are some major features for each expression but they are not shared by everyone. ST FacExp classifies up to 7 different expressions (Anger, Disgust, Fear, Happiness, Surprise, Sadness, Neutral)
34 Food Recognition: in collaboration with IPLab 34 Quite challenging application: high intra-class variability and low inter-class variability; Standard approaches (such has HOG+SVM) perform very poorly on this task; Benchmarking bw CDNN approach and UniCT Classic Approach: CDNN: Features extraction from last fc7 layer of AlexNet fine-tuned model + multi-class SVM UniCT Classic: Bag of SIFT & Bag of Textons + one-class SVM Training set: UNICTFD889 (3583) + NonFoodFlickr (3583); Test set: FoodFlickr (4008) + NonFoodFlickr (4422) DBs available at CDNN Food Non-Food Food 94.3% 5.7% Non-Food 4.5% 95.5% Accuracy = 94.9% UniCT Classic Food Non-Food Food 29% 71% Non-Food 6% 94% Accuracy = 61.5%
35 Food Recognition: Demo 35 Web demo available at: Demo running also on a PC
36 Human Activity Recognition 36 5 activities Training: 925 minutes Test: 591 minutes Development platform: STMicroelectronics SensorTile with STM32L4. We process 3-axis accelerometer data with neural networks and estimate the activity performed by the user. The following activities are classified: stationary, walking/ fast walking, running, biking, driving
37 Example with MEMS: activity recognition 37
38 Acoustic Scene Classification (ASC) 38 Acoustic Scene Classification CNNs Based on IEEE DCASE2016 Contest DataSet Developed two CNN Spectrogram based models for ASC (15 and 3 classes) starting from a reference model 15 acoustic classes: (beach, bus, cafe/restaurant, car, city_center, forest_path, grocery_store, home, library, metro_station, office, park, residential_area, train, tram) 3 acoustic classes: (indoor, outdoor, in vehicle) Complexity Estimation for Ref DCASE Model 15cl, ASC 15cl, ASC 3cl Started AST ASC Models porting on Target Platform (stile STM32L4) Collecting an AST ASC Dataset with AudioLog Application of SensorTile on usd for a 9 classes target DataSet: (bus, cafe/restaurant, car, city_center, home, office, park, residential_area, train)
39 Keyword Spotting (KWS) 39 Target: To develop a Wake Up Word solution to enable hands free triggering of consumer devices; Status: a NN based KWS solution is now available on Sensortile; Architecture: Mel Frequency Cepstral Coefficients + Multi Layer Percetron; Performance Evaluation: Train: samples; Test: samples; Accuracy on Test Set: 75% To be done: Continue the dataset words collection to better capture language variances; Consolidate the model and increase performances.
40 Arrhythmia classifier 40 Goal: to classify different cardiac arrhythmias The input is an anomalous beat Arrhythmia detector Arrhythmia classifier Arrhythmia type Body gateway electronic patch
41 Applications & Platforms 41
42 STM32 and Nucleo boards 42 A new marketing model in ST oriented to the mass market Nucleo is : A complete system for fast prototyping based on STM32 microcontrollers Very low cost Shields allow to play with ST s solutions (sensors, motor drivers, connectivity, etc.) Open Development Environment (ODE) allows simple prototyping AST is working on developing systems exploiting such devices on: Wearable IoT Drones Robot Wellness Industry 4.0
43 ST Solutions for Customers 43 Easy, Affordable and Rapid Prototyping Tool STM32 ODE Sense Connect Power Drive Move Actuate Translate Reference Design & Solution Boards Wearable Sensor Unit STEVAL-WESU1 SensorTile STEVAL-STLKT01V1 Product Eval Boards 1 W Wearable Wireless Charger STEVAL-ISB038V1 STEVAL-ISB039V1 Bluetooth Low Energy STEVAL-IDB007V1 Near Field Communication FLEX-M24LR04E Microphone Coupon Board STEVAL-MKI129V4... Presentation Mode: All blocks include hyperlinks
44 ST-Drone Prototype 1/2 44 ESC FCU PWM to PPM
45 ST-Drone Prototype 2/2 45 FCU-Demo Board STM32F756VG ARM Cortex -M7 LPS22HB Pressure Sensor LIS3MDL 3D Magnetometer LSM303AGR 3-axis e- compass LSM6DS33 6-axis IMU PX4 Open-source FW PWM RC Input 5V GND RC1 RC2 RC3 RC4 RC5 RC6 RC7 RC8 RC9 USB STM32F303 Nucleo-32 PWM to PPM Converter PPM Output GNSS Demo Board GNSS-Demo Board Teseo III GNSS location HUB High Dynamics (5 to 10Hz) Sensor Interfaces (SPI, I2C, ADC) ESC Demo Board 1 ESC Demo Board 2 ESC Demo Board 3 ESC Demo Board 4 ESC-Demo Board 30V, 20A FOC control (3 shunts) For 3s-5s batteries 5V BEC for FCU L6398 High Voltage Gate Drivers STL160NS3LLH7 Low Voltage STripFET H7 series STM32F303 ARM Cortex -M4
46 Robot Assistance 46 Started activities about Robotics elderly surveillance and assistance Using competences in Robotics and Computer Vision ST want to increase robotic performance and interaction through ST components Possibile example using Face detection and Tracking
47 Industry 4.0: Automatic Defect Classification Scope: Today, the images produced by the Scanning Electron Microscope (SEM) and showing different types of defects are manually classified by the operators. The goal of the project is to use an algorithm to automatically classify those images 47 Technical explanation: The recent improvement in Neural Network and specially Deep Learning can now be adapted to our industry to classify images of defects such as:
48 PhD & Thesis 48 Multimodal representation learning (PhD activity with IPLab): Multimodal data fusion for context and activity recognition: Audio reconstruction Video reconstruction shared representation Audio input video input Multi-modal representation learning Thesis: possibility to perform stages & thesis in all the shown application fields
49 QUESTIONS? 49
50 THANK YOU
AI Application Processing Requirements
AI Application Processing Requirements 1 Low Medium High Sensor analysis Activity Recognition (motion sensors) Stress Analysis or Attention Analysis Audio & sound Speech Recognition Object detection Computer
More informationLa ricerca e sviluppo in STMicroelectronics
La ricerca e sviluppo in STMicroelectronics Who we are 2 A global semiconductor leader The largest European semiconductor company 2013 revenues of $8.08B Approx. 45,000 employees worldwide Approx. 9,000
More informationCompany Presentation. October 2017
Company Presentation October 2017 A global semiconductor leader 2016 revenues of $6.97B Listed: NYSE, Euronext Paris and Borsa Italiana, Milan Who We are 2 Research & Development Main Sales & Marketing
More informationCompany Presentation. January 2018
Company Presentation January 2018 A global semiconductor leader 2017 revenues of $8.35B with yearon-year growth of 19.7% Listed: NYSE, Euronext Paris and Borsa Italiana, Milan Who We Are 2 Research & Development
More informationCompany Presentation. October 2018
Company Presentation October 2018 A global semiconductor leader 2017 revenues of $8.35B with yearon-year growth of 19.7% Listed: NYSE, Euronext Paris and Borsa Italiana, Milan Who We Are 2 Research & Development
More informationCompany Presentation. July 2018
Company Presentation July 2018 A global semiconductor leader 2017 revenues of $8.35B with yearon-year growth of 19.7% Listed: NYSE, Euronext Paris and Borsa Italiana, Milan Who We Are 2 Research & Development
More informationInfineon at a glance
Infineon at a glance 2017 www.infineon.com We make life easier, safer and greener with technology that achieves more, consumes less and is accessible to everyone. Microelectronics from Infineon is the
More informationMEMS Solutions For VR & AR
MEMS Solutions For VR & AR Sensor Expo 2017 San Jose June 28 th 2017 MEMS Sensors & Actuators at ST 2 Motion Environmental Audio Physical change Sense Electro MEMS Mechanical Signal Mechanical Actuate
More informationLow Power Microphone Acquisition and Processing for Always-on Applications Based on Microcontrollers
Low Power Microphone Acquisition and Processing for Always-on Applications Based on Microcontrollers Architecture I: standalone µc Microphone Microcontroller User Output Microcontroller used to implement
More informationSpeeding Up Revolution of Drones. December 2016
Speeding Up Revolution of Drones December 2016 Drones with high growth in consumer 2 Source: YOLE Drone Features 3 Propeller Control Flight Cruising Visual Navigation Power & Battery Managing Stability
More informationNeural Networks The New Moore s Law
Neural Networks The New Moore s Law Chris Rowen, PhD, FIEEE CEO Cognite Ventures December 216 Outline Moore s Law Revisited: Efficiency Drives Productivity Embedded Neural Network Product Segments Efficiency
More informationEmbedding Artificial Intelligence into Our Lives
Embedding Artificial Intelligence into Our Lives Michael Thompson, Synopsys D&R IP-SOC DAYS Santa Clara April 2018 1 Agenda Introduction What AI is and is Not Where AI is being used Rapid Advance of AI
More informationEnergy autonomous wireless sensors: InterSync Project. FIMA Autumn Conference 2011, Nov 23 rd, 2011, Tampere Vesa Pentikäinen VTT
Energy autonomous wireless sensors: InterSync Project FIMA Autumn Conference 2011, Nov 23 rd, 2011, Tampere Vesa Pentikäinen VTT 2 Contents Introduction to the InterSync project, facts & figures Design
More informationSensor & motion algorithm software pack for STM32Cube
Sensor & motion algorithm software pack for STM32Cube POSITION TRACKING ACTIVITY TRACKING FOR WRIST DEVICES ACTIVITY TRACKING FOR MOBILE DEVICES CALIBRATION ALGORITHMS Complete motion sensor and environmental
More informationExtending The Life Of 200mm Fabs And The Re-use of Second Hand Tools
Extending The Life Of 200mm Fabs And The Re-use of Second Hand Tools Gareth Bignell, FE Equipment Procurement Director SEMICON Europa 2012 Presentation Summary 2 An introduction to STMicroelectronics The
More informationHardware Platforms and Sensors
Hardware Platforms and Sensors Tom Spink Including material adapted from Bjoern Franke and Michael O Boyle Hardware Platform A hardware platform describes the physical components that go to make up a particular
More informationElettronica e Controllo degli Attuatori SMA
Elettronica e Controllo degli Attuatori SMA Adriano Basile STMicroelectronics, System LAB Content 2 STMicroelectronics: Who we are Shape Memory Alloy Brief Mechanical Considerations SMA Driving Topology
More information32-bit ARM Cortex-M0, Cortex-M3 and Cortex-M4F microcontrollers
-bit ARM Cortex-, Cortex- and Cortex-MF microcontrollers Energy, gas, water and smart metering Alarm and security systems Health and fitness applications Industrial and home automation Smart accessories
More information[Overview of the Consolidated Financial Results]
0 1 [Overview of the Consolidated Financial Results] 1. Consolidated revenue totaled 5,108.3 billion yen, increased by 581.1 billion yen (+12.8%) from the previous year. 2. Consolidated operating profit
More informationSNIOT702 Specification. Version number:v 1.0.1
Version number:v 1.0.1 Catelog 1 Product introduction... 1 1.1 Product introduction... 1 1.2 Product application... 1 1.3 Main characteristics... 2 1.4 Product advantage... 3 2 Technical specifications...
More informationDesigning with STM32F3x
Designing with STM32F3x Course Description Designing with STM32F3x is a 3 days ST official course. The course provides all necessary theoretical and practical know-how for start developing platforms based
More informationPartner for Success Secure & Smart Future Home
Partner for Success Secure & Smart Future Home Jiang Yanbing Director of Strategy and Market Development Dept. Infineon Technologies China Table of contents 1 About Infineon 2 Make Future Home Smart and
More informationRadar System Design Considerations -- System Modeling Findings (MOS-AK Conference Hangzhou 2017)
Radar System Design Considerations -- System Modeling Findings (MOS-AK Conference Hangzhou 2017) Silicon Radar GmbH Im Technologiepark 1 15236 Frankfurt (Oder) Germany Outline 1 Introduction to Short Distance
More informationMEMS Sensors as enablers for IoTS Shanghai, 17 th of March 2014 百里博 / Leopold Beer Regional President Asia Pacific
- The MEMS Technology Leader MEMS Sensors as enablers for IoTS Shanghai, 17 th of March 2014 百里博 / Leopold Beer Regional President Asia Pacific 1 Marketing 17/03/2014 GmbH 2013. All rights reserved, also
More informationA European Perspective for Electronic Industry in Latin America
A European Perspective for Electronic Industry in Latin America François Guibert Corporate Vice President, Emerging Markets Region General Manager Electronic, a Global World Security Networking Consumer
More informationDigital Transformation. A Game Changer. How Does the Digital Transformation Affect Informatics as a Scientific Discipline?
Digital Transformation A Game Changer How Does the Digital Transformation Affect Informatics as a Scientific Discipline? Manfred Broy Technische Universität München Institut for Informatics ... the change
More informationCapacitive MEMS accelerometer for condition monitoring
Capacitive MEMS accelerometer for condition monitoring Alessandra Di Pietro, Giuseppe Rotondo, Alessandro Faulisi. STMicroelectronics 1. Introduction Predictive maintenance (PdM) is a key component of
More informationVision with Precision Webinar Series Augmented & Virtual Reality Aaron Behman, Xilinx Mark Beccue, Tractica. Copyright 2016 Xilinx
Vision with Precision Webinar Series Augmented & Virtual Reality Aaron Behman, Xilinx Mark Beccue, Tractica Xilinx Vision with Precision Webinar Series Perceiving Environment / Taking Action: AR / VR Monitoring
More informationDeep Learning Overview
Deep Learning Overview Eliu Huerta Gravity Group gravity.ncsa.illinois.edu National Center for Supercomputing Applications Department of Astronomy University of Illinois at Urbana-Champaign Data Visualization
More informationSHAPING THE FUTURE OF IOT: PLATFORMS FOR CO-CREATION, RAPID PROTOTYPING AND SUCCESSFUL INDUSTRIALIZATION
SHAPING THE FUTURE OF IOT: PLATFORMS FOR CO-CREATION, RAPID PROTOTYPING AND SUCCESSFUL INDUSTRIALIZATION Dr. Julian Bartholomeyczik Head of Software Development Bosch Connected Devices and Solutions GmbH
More informationDefinitions and Application Areas
Definitions and Application Areas Ambient intelligence: technology and design Fulvio Corno Politecnico di Torino, 2013/2014 http://praxis.cs.usyd.edu.au/~peterris Summary Definition(s) Application areas
More informationADVANCED EMBEDDED MONITORING SYSTEM FOR ELECTROMAGNETIC RADIATION
98 Chapter-5 ADVANCED EMBEDDED MONITORING SYSTEM FOR ELECTROMAGNETIC RADIATION 99 CHAPTER-5 Chapter 5: ADVANCED EMBEDDED MONITORING SYSTEM FOR ELECTROMAGNETIC RADIATION S.No Name of the Sub-Title Page
More information#SMARTer2030. ICT Solutions for 21 st Century Challenges
#SMARTer2030 ICT Solutions for 21 st Century Challenges 3.8 Manufacturing Resource efficient and customer centric Smart Manufacturing The Context Recent technological developments in the scope of the Internet
More informationTHE VISIONLAB TEAM engineers - 1 physicist. Feasibility study and prototyping Hardware benchmarking Open and closed source libraries
VISIONLAB OPENING THE VISIONLAB TEAM 2018 6 engineers - 1 physicist Feasibility study and prototyping Hardware benchmarking Open and closed source libraries Deep learning frameworks GPU frameworks FPGA
More informationTraining Schedule. Robotic System Design using Arduino Platform
Training Schedule Robotic System Design using Arduino Platform Session - 1 Embedded System Design Basics : Scope : To introduce Embedded Systems hardware design fundamentals to students. Processor Selection
More informationCROSS-LAYER FEATURES IN CONVOLUTIONAL NEURAL NETWORKS FOR GENERIC CLASSIFICATION TASKS. Kuan-Chuan Peng and Tsuhan Chen
CROSS-LAYER FEATURES IN CONVOLUTIONAL NEURAL NETWORKS FOR GENERIC CLASSIFICATION TASKS Kuan-Chuan Peng and Tsuhan Chen Cornell University School of Electrical and Computer Engineering Ithaca, NY 14850
More informationNCCT IEEE PROJECTS ADVANCED ROBOTICS SOLUTIONS. Latest Projects, in various Domains. Promise for the Best Projects
NCCT Promise for the Best Projects IEEE PROJECTS in various Domains Latest Projects, 2009-2010 ADVANCED ROBOTICS SOLUTIONS EMBEDDED SYSTEM PROJECTS Microcontrollers VLSI DSP Matlab Robotics ADVANCED ROBOTICS
More information23270: AUGMENTED REALITY FOR NAVIGATION AND INFORMATIONAL ADAS. Sergii Bykov Technical Lead Machine Learning 12 Oct 2017
23270: AUGMENTED REALITY FOR NAVIGATION AND INFORMATIONAL ADAS Sergii Bykov Technical Lead Machine Learning 12 Oct 2017 Product Vision Company Introduction Apostera GmbH with headquarter in Munich, was
More informationMixed-Signal Design Innovations in FDSOI Technology. Boris Murmann April 13, 2016
Mixed-Signal Design Innovations in FDSOI Technology Boris Murmann April 13, 2016 Outline Application trends and needs Review of FDSOI advantages Examples High-speed data conversion RF transceivers Medical
More informationFirmware plugin for STSW-ESC001V1 board with ST Motor Control FOC SDK
User manual Firmware plugin for STSW-ESC001V1 board with ST Motor Control FOC SDK Introduction The STSW-ESC001V1 firmware package for the STEVAL-ESC001V1 board includes the application code to support
More informationCortex-M3 based Prepaid System with Electricity Theft Control
Research Inventy: International Journal of Engineering And Science Vol.6, Issue 4 (April 2016), PP -139-146 Issn (e): 2278-4721, Issn (p):2319-6483, www.researchinventy.com Cortex-M3 based Prepaid System
More informationIntelligent Power Economy System (Ipes)
American Journal of Engineering Research (AJER) e-issn : 2320-0847 p-issn : 2320-0936 Volume-02, Issue-08, pp-108-114 www.ajer.org Research Paper Open Access Intelligent Power Economy System (Ipes) Salman
More informationHello, and welcome to this presentation of the STM32 Digital Filter for Sigma-Delta modulators interface. The features of this interface, which
Hello, and welcome to this presentation of the STM32 Digital Filter for Sigma-Delta modulators interface. The features of this interface, which behaves like ADC with external analog part and configurable
More informationBob Krysiak. Executive Vice President President, Americas Region Global Mass Market and Online Marketing Programs
Bob Krysiak Executive Vice President President, Americas Region Global Mass Market and Online Marketing Programs Forward Looking Statements 2 Some of the statements contained in this release that are not
More informationEvaluation of Connected Vehicle Technology for Concept Proposal Using V2X Testbed
AUTOMOTIVE Evaluation of Connected Vehicle Technology for Concept Proposal Using V2X Testbed Yoshiaki HAYASHI*, Izumi MEMEZAWA, Takuji KANTOU, Shingo OHASHI, and Koichi TAKAYAMA ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
More informationHarnessing the Power of AI: An Easy Start with Lattice s sensai
Harnessing the Power of AI: An Easy Start with Lattice s sensai A Lattice Semiconductor White Paper. January 2019 Artificial intelligence, or AI, is everywhere. It s a revolutionary technology that is
More informationTransformation to Artificial Intelligence with MATLAB Roy Lurie, PhD Vice President of Engineering MATLAB Products
Transformation to Artificial Intelligence with MATLAB Roy Lurie, PhD Vice President of Engineering MATLAB Products 2018 The MathWorks, Inc. 1 A brief history of the automobile First Commercial Gas Car
More information5G R&D at Huawei: An Insider Look
5G R&D at Huawei: An Insider Look Accelerating the move from theory to engineering practice with MATLAB and Simulink Huawei is the largest networking and telecommunications equipment and services corporation
More informationTechnology & Manufacturing
Technology & Manufacturing Jean-Marc Chery Chief Operating Officer Front-End Manufacturing Unique capability 2 Technology portfolio aligned with application focus areas Flexible IDM model with foundry
More informationMATLAB DIGITAL IMAGE/SIGNAL PROCESSING TITLES
MATLAB DIGITAL IMAGE/SIGNAL PROCESSING TITLES -2018 S.NO PROJECT CODE 1 ITIMP01 2 ITIMP02 3 ITIMP03 4 ITIMP04 5 ITIMP05 6 ITIMP06 7 ITIMP07 8 ITIMP08 9 ITIMP09 `10 ITIMP10 11 ITIMP11 12 ITIMP12 13 ITIMP13
More informationComputer vision, wearable computing and the future of transportation
Computer vision, wearable computing and the future of transportation Amnon Shashua Hebrew University, Mobileye, OrCam 1 Computer Vision that will Change Transportation Amnon Shashua Mobileye 2 Computer
More informationDIGITAL TECHNOLOGIES FOR A BETTER WORLD. NanoPC HPC
DIGITAL TECHNOLOGIES FOR A BETTER WORLD NanoPC HPC EMBEDDED COMPUTER MODULES A unique combination of miniaturization & processing power Nano PC MEDICAL INSTRUMENTATION > BIOMETRICS > HOME & BUILDING AUTOMATION
More informationAN4392 Application note
Application note Using the BlueNRG family transceivers under ARIB STD-T66 in the 2400 2483.5 MHz band Introduction BlueNRG family devices are very low power Bluetooth low energy (BLE) devices compliant
More informationKÜNSTLICHE INTELLIGENZ JOBKILLER VON MORGEN?
KÜNSTLICHE INTELLIGENZ JOBKILLER VON MORGEN? Marc Stampfli https://www.linkedin.com/in/marcstampfli/ https://twitter.com/marc_stampfli E-Mail: mstampfli@nvidia.com INTELLIGENT ROBOTS AND SMART MACHINES
More informationGNSS in Autonomous Vehicles MM Vision
GNSS in Autonomous Vehicles MM Vision MM Technology Innovation Automated Driving Technologies (ADT) Evaldo Bruci Context & motivation Within the robotic paradigm Magneti Marelli chose Think & Decision
More informationINTRODUCTION. What is the LSN50
INTRODUCTION Dragino LoRa Sensor Node Dragino LoRa Sensor Node What is the LSN50 LSN50 is a Long Range LoRa Sensor Node. It is designed for outdoor use and powered by Li/SOCl2 battery for long term use
More informationRANA: Towards Efficient Neural Acceleration with Refresh-Optimized Embedded DRAM
RANA: Towards Efficient Neural Acceleration with Refresh-Optimized Embedded DRAM Fengbin Tu, Weiwei Wu, Shouyi Yin, Leibo Liu, Shaojun Wei Institute of Microelectronics Tsinghua University The 45th International
More informationAccelerating Collective Innovation: Investing in the Innovation Landscape
PCB Executive Forum Accelerating Collective Innovation: Investing in the Innovation Landscape How a Major Player Uses Internal Venture Program to Accelerate Small Players with Big Ideas Dr. Joan K. Vrtis
More informationConnected Living -- Smart Cities The Impact of Big Data for Smart Cities. Smart Cities Forum, Brussels, 6 Sept 2013
Connected Living -- Smart Cities The Impact of Big Data for Smart Cities Smart Cities Forum, Brussels, 6 Sept 2013 Smart city mobile opportunity of USD 67bn by 2020 Smart Cities market opportunity by 2020
More informationIndustry 4.0: the new challenge for the Italian textile machinery industry
Industry 4.0: the new challenge for the Italian textile machinery industry Executive Summary June 2017 by Contacts: Economics & Press Office Ph: +39 02 4693611 email: economics-press@acimit.it ACIMIT has
More informationEmbedded & Robotics Training
Embedded & Robotics Training WebTek Labs creates and delivers high-impact solutions, enabling our clients to achieve their business goals and enhance their competitiveness. With over 13+ years of experience,
More informationFrom vision to growth: Role of research in building world-class excellence in future added value electronics
From vision to growth: Role of research in building world-class excellence in future added value electronics Antti Vasara, CEO VTT Technical Research Centre of Finland Ltd Contents 1. VTT in short 2. Our
More informationDeep Learning for Human Activity Recognition: A Resource Efficient Implementation on Low-Power Devices
Deep Learning for Human Activity Recognition: A Resource Efficient Implementation on Low-Power Devices Daniele Ravì, Charence Wong, Benny Lo and Guang-Zhong Yang To appear in the proceedings of the IEEE
More informationWireless Sensor Networks for Aerospace Applications
SAE 2017 Aerospace Standards Summit th 25-26 April 2017, Cologne, Germany Wireless Sensor Networks for Aerospace Applications Dr. Bahareh Zaghari University of Southampton, UK June 9, 2017 In 1961, the
More informationUnit level 5 Credit value 15. Introduction. Learning Outcomes
Unit 46: Unit code Embedded Systems A/615/1514 Unit level 5 Credit value 15 Introduction An embedded system is a device or product which contains one or more tiny computers hidden inside it. This hidden
More informationHorizon 2020 ICT Robotics Work Programme (draft - Publication: 20 October 2015)
NCP TRAINING BRUSSELS 07 OCTOBER 2015 1 Horizon 2020 ICT Robotics Work Programme 2016 2017 (draft - Publication: 20 October 2015) Cécile Huet Deputy Head of Unit Robotics Directorate General for Communication
More informationImage Processing Architectures (and their future requirements)
Lecture 16: Image Processing Architectures (and their future requirements) Visual Computing Systems Smart phone processing resources Example SoC: Qualcomm Snapdragon Image credit: Qualcomm Apple A7 (iphone
More informationComputer Networks II Advanced Features (T )
Computer Networks II Advanced Features (T-110.5111) Wireless Sensor Networks, PhD Postdoctoral Researcher DCS Research Group For classroom use only, no unauthorized distribution Wireless sensor networks:
More informationTae-Kwang Jang. Electrical Engineering, University of Michigan
Education Tae-Kwang Jang Electrical Engineering, University of Michigan E-Mail: tkjang@umich.edu Ph.D. in Electrical Engineering, University of Michigan September 2013 November 2017 Dissertation title:
More informationBIM, CIM, IOT: the rapid rise of the new urban digitalism.
NEXUS FORUM BIM, CIM, IOT: the rapid rise of the new urban digitalism. WHAT MATTERS IN THE GLOBAL CHALLENGE FOR SMART, SUSTAINABLE CITIES AND WHAT IT MEANS NEXUS IS A PARTNER OF GLOBAL FUTURES GROUP FOR
More informationMultiband NFC for High-Throughput Wireless Computer Vision Sensor Network
Multiband NFC for High-Throughput Wireless Computer Vision Sensor Network Fei Y. Li, Jason Y. Du 09212020027@fudan.edu.cn Vision sensors lie in the heart of computer vision. In many computer vision applications,
More information* Intelli Robotic Wheel Chair for Specialty Operations & Physically Challenged
ADVANCED ROBOTICS SOLUTIONS * Intelli Mobile Robot for Multi Specialty Operations * Advanced Robotic Pick and Place Arm and Hand System * Automatic Color Sensing Robot using PC * AI Based Image Capturing
More informationCMOS MT9D111Camera Module 1/3.2-Inch 2-Megapixel Module Datasheet
CMOS MT9D111Camera Module 1/3.2-Inch 2-Megapixel Module Datasheet Rev 1.0, Mar 2013 Table of Contents 1 Introduction... 2 2 Features... 2 3 Block Diagram... 3 4 Application... 4 5 Pin Definition... 6 6
More informationWifiBotics. An Arduino Based Robotics Workshop
WifiBotics An Arduino Based Robotics Workshop WifiBotics is the workshop designed by RoboKart group pioneers in this field way back in 2014 and copied by many competitors. This workshop is based on the
More informationAsia Conference Singapore
Fujitsu World Tour 2017 Asia Conference Singapore Human Centric Innovation: Digital Co-Creation Yoshikuni Takashige Vice President, Marketing Strategy and Vision Fujitsu Limited Fujitsu Technology and
More informationAudio in ecall and Cluster. Clancy Soehren MSA Applications FAE Summit 2016
Audio in ecall and Cluster Clancy Soehren MSA Applications FAE Summit 2016 1 Agenda Audio Architecture Audio Quality Diagnostics and Protection Efficiency EMI/EMC 2 Audio Architecture 3 Cluster Mid-Range
More informationMEMS Oscillators: Enabling Smaller, Lower Power IoT & Wearables
MEMS Oscillators: Enabling Smaller, Lower Power IoT & Wearables The explosive growth in Internet-connected devices, or the Internet of Things (IoT), is driven by the convergence of people, device and data
More informationThe rise of always-listening sensors integrated in energy-scarce devices such as watches and remotecontrols
Context-Aware Hierarchical Information-Sensing in a 6 µw 9nm CMOS Voice Activity Detector Komail Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst KU Leuven, Leuven, Belgium The rise of always-listening
More informationOECD s Innovation Strategy: Key Findings and Policy Messages
OECD s Innovation Strategy: Key Findings and Policy Messages 2010 MIT Europe Conference, Brussels, 12 October Dirk Pilat, OECD dirk.pilat@oecd.org Outline 1. Why innovation matters today 2. Why policies
More informationAgilent N8480 Series Thermocouple Power Sensors. Technical Overview
Agilent N8480 Series Thermocouple Power Sensors Technical Overview Introduction The new N8480 Series power sensors replace and surpass the legacy 8480 Series power sensors (excluding the D-model power
More informationSilicon radars and smart algorithms - disruptive innovation in perceptive IoT systems Andy Dewilde PUBLIC
Silicon radars and smart algorithms - disruptive innovation in perceptive IoT systems Andy Dewilde PUBLIC Fietser in levensgevaar na ongeval met vrachtwagen op Louizaplein Het Laatste Nieuws 16/06/2017
More informationSMART SENSORS AND MEMS
2 SMART SENSORS AND MEMS Dr. H. K. Verma Distinguished Professor (EEE) Sharda University, Greater Noida (Formerly: Deputy Director and Professor of Instrumentation Indian Institute of Technology Roorkee)
More informationThe Advantages of Integrated MEMS to Enable the Internet of Moving Things
The Advantages of Integrated MEMS to Enable the Internet of Moving Things January 2018 The availability of contextual information regarding motion is transforming several consumer device applications.
More informationIoT Market Perspective: India Market
IoT Market Perspective: India Market IoT Week 2007, Geneva EU India Cooperation Platform in Future Internet & Electronic Media Project Abhishek Sharma, Beyond Evolution Tech Solutions (bets) Partners:
More informationImage Processing Architectures (and their future requirements)
Lecture 17: Image Processing Architectures (and their future requirements) Visual Computing Systems Smart phone processing resources Qualcomm snapdragon Image credit: Qualcomm Apple A7 (iphone 5s) Chipworks
More informationRobust Positioning for Urban Traffic
Robust Positioning for Urban Traffic Motivations and Activity plan for the WG 4.1.4 Dr. Laura Ruotsalainen Research Manager, Department of Navigation and positioning Finnish Geospatial Research Institute
More informationKeysight Technologies Achieving Accurate E-band Power Measurements with E8486A Waveguide Power Sensors. Application Note
Keysight Technologies Achieving Accurate E-band Power Measurements with Waveguide Power Sensors Application Note Introduction The 60 to 90 GHz spectrum, or E-band, has been gaining more millimeter wave
More informationPresentation at Salland Engineering Test Symposium Sept 14 th 2018
Low Power RF / Wireless IC design Presentation at Salland Engineering Test Symposium Sept 14 th 2018 Martin Valfridsson, CEO ShortLink Holding AB Johan Grumer, Design Engineer ASIC & RF, Production Manager
More informationSeparately Excited DC Motor for Electric Vehicle Controller Design Yulan Qi
6th International Conference on Sensor etwork and Computer Engineering (ICSCE 2016) Separately Excited DC Motor for Electric Vehicle Controller Design ulan Qi Wuhan Textile University, Wuhan, China Keywords:
More informationCOMPUTER SCIENCE AND ENGINEERING
COMPUTER SCIENCE AND ENGINEERING Internet of Thing Cloud Computing Big Data Analytics Network Security Distributed System Image Processing Data Science Business Intelligence Wireless Sensor Network Artificial
More informationARTEMIS The Embedded Systems European Technology Platform
ARTEMIS The Embedded Systems European Technology Platform Technology Platforms : the concept Conditions A recipe for success Industry in the Lead Flexibility Transparency and clear rules of participation
More informationEmbedded Robotics. Software Development & Education Center
Software Development & Education Center Embedded Robotics Robotics Development with ARM µp INTRODUCTION TO ROBOTICS Types of robots Legged robots Mobile robots Autonomous robots Manual robots Robotic arm
More informationINTRODUCTION TO DEEP LEARNING. Steve Tjoa June 2013
INTRODUCTION TO DEEP LEARNING Steve Tjoa kiemyang@gmail.com June 2013 Acknowledgements http://ufldl.stanford.edu/wiki/index.php/ UFLDL_Tutorial http://youtu.be/ayzoubkuf3m http://youtu.be/zmnoatzigik 2
More informationLeading-Edge Cluster it's OWL Günter Korder, Managing Director it s OWL Clustermanagement GmbH 16 th November
Leading-Edge Cluster it's OWL Günter Korder, Managing Director it s OWL Clustermanagement GmbH 16 th November 2018 www.its-owl.de Intelligent Technical Systems The driving force behind Industry 4.0 and
More informationDistributed Robotics: Building an environment for digital cooperation. Artificial Intelligence series
Distributed Robotics: Building an environment for digital cooperation Artificial Intelligence series Distributed Robotics March 2018 02 From programmable machines to intelligent agents Robots, from the
More informationTechnology Transfers Opportunities, Process and Risk Mitigation. Radhika Srinivasan, Ph.D. IBM
Technology Transfers Opportunities, Process and Risk Mitigation Radhika Srinivasan, Ph.D. IBM Abstract Technology Transfer is quintessential to any technology installation or semiconductor fab bring up.
More informationVisvesvaraya Technological University, Belagavi
Time Table for M.TECH. Examinations, June / July 2017 M. TECH. 2010 Scheme 2011 Scheme 2012 Scheme 2014 Scheme 2016 Scheme [CBCS] Semester I II III I II III I II III I II IV I II Time Date, Day 14/06/2017,
More informationTeleoperated Robot Controlling Interface: an Internet of Things Based Approach
Proc. 1 st International Conference on Machine Learning and Data Engineering (icmlde2017) 20-22 Nov 2017, Sydney, Australia ISBN: 978-0-6480147-3-7 Teleoperated Robot Controlling Interface: an Internet
More informationJoint Open Lab and PHD proposal
GRUPPO TELECOM ITALIA Joint Open Lab and PHD proposal Politecnico di Torino Aprile 2015 Joint Open Lab : Project at a glance Joint Open Labs are research and innovation laboratories set up within university
More informationFramework Programme 7
Framework Programme 7 1 Joining the EU programmes as a Belarusian 1. Introduction to the Framework Programme 7 2. Focus on evaluation issues + exercise 3. Strategies for Belarusian organisations + exercise
More information